Broadview Underpriced & OverpricedIntroducing the groundbreaking Broadview Underpriced & Overpriced indicator—a convergence of science, technology, and mathematical finance. This cutting-edge development takes the highly acclaimed Overbought & Oversold Heatmap and elevates it to an entirely new level by infusing it with price trends through the application of special moving averages. The result is a revolutionary approach to asset classification, allowing traders, investors, and institutions to categorize assets into four distinct categories: Underpriced, Overpriced, Discounted, and Inflated.
The Broadview Underpriced & Overpriced indicator combines the power of the Overbought & Oversold Heatmap with a sophisticated methodology that leverages special moving averages. These unique moving averages enhance the precision and accuracy of the asset classification process, providing traders with unparalleled insights into market conditions.
Under the Broadview Underpriced & Overpriced framework, assets that are deemed oversold and positioned below the special moving average are identified as Underpriced. This designation implies that the asset's current price is undervalued relative to its intrinsic worth, presenting an opportune moment to consider initiating a buying position. Underpriced assets are represented by a vibrant purple color on the indicator, symbolizing the potential for significant buying opportunities.
Conversely, assets that are considered overbought and situated above the special moving average are labeled as Overpriced. This classification indicates that the asset's current price has exceeded its intrinsic value, suggesting a favorable moment to contemplate selling or reducing exposure to the asset. Overpriced assets are visually depicted by a striking teal color, signifying the potential for optimal selling opportunities.
Moreover, the Broadview Underpriced & Overpriced indicator recognizes a third category known as Discounted assets. These assets are characterized by being positioned above the special moving average while simultaneously experiencing oversold conditions. This classification suggests that although the asset's price may be above its average value, it is currently available at a discounted price relative to its long-term potential. Discounted assets are represented by a deep purple hue, indicating an opportunity for buyers to consider making purchases with a lower aggression dollar-cost averaging (DCA) strategy.
Lastly, the indicator identifies Inflated assets as those positioned below the special moving average while concurrently exhibiting overbought conditions. This classification implies that the asset's price may be temporarily inflated compared to its intrinsic worth. Inflated assets are depicted by a rich teal color, representing an indication for trend traders or those looking to capitalize on consolidations.
The Broadview Underpriced & Overpriced indicator brings forth a groundbreaking evolution in asset classification, meticulously combining the Overbought & Oversold Heatmap with the influence of special moving averages. Through this unique fusion, traders and investors gain access to an unprecedented level of insight, enabling them to make informed decisions based on a comprehensive evaluation of market trends.
The Broadview Underpriced & Overpriced indicator represents a paradigm shift in asset classification, uniting science, technology, and mathematical finance to deliver an innovative and comprehensive trading tool. By leveraging special moving averages in conjunction with the Overbought & Oversold Heatmap, this indicator enables traders, investors, and institutions to categorize assets as Underpriced, Overpriced, Discounted, or Inflated. Its visually captivating color scheme and strategic insights empower market participants to navigate market trends with precision, enhancing their ability to capitalize on optimal buying and selling opportunities while employing various trading strategies.
Recherche dans les scripts pour "averages"
Gate Signal by Market yogiThis indicator is made by Nischay Rana (Market Yogi)
How to use this Indicator
This is simple group of 8 moving averages, which can be configured in various ways according to your trading requirement.
1. moving average ribbon
2.moving average channel
3.moving average gate signal
4.This indicator has bonus indicator of bollinger bands inbuilt.
Logic:
As price has tendency to get closer to their moving averages. The logic behind this indicator is to use the contraction and expansion concepts of moving averages to find best entry exit points.
This nature of Price action is use to capture the big move after the convergence of all moving averages.
CAUTION : Do not blindly trade the gates as gate has tendency to break out on either side. So use this indicator in confluence with price action and other technical analysis to capture bigger moves.
Higher the gate width more gates are found. Similarly lesser the gate width less gate are found. i.e. Tight squeeze of all the moving averages.
"ENJOY HAPPY TRADING.."
Truly Yours Market Yogi
Sword of a Thousand Truths (Wyckoff Sniper)This identifies hidden pivot points in price action by uniquely identifying Wyckoff patterns and signatures.
If you aren't familiar with Wyckoff, it is strongly advised that you at a minimum learn about accumulation and distribution (school.stockcharts.com)
Settings and Configs
Scanning Length -- this is how many candles are considered into each phase of Wyckoff accumulation or distribution. The longer you set this length, the more certainty in the indicators signals. You can think of this akin to that of a higher time frame.
Green/Red Clouds are Wyckoff regions of accumulation and distribution (supports, resistances) -- if price enters into these regions, it is likely to experience volatility in the opposite direction. However , if the price escapes these regions, it will most likely dip or rip in the opposite direction. (e.g., if the price is riding within the distribution region in an upward trend, and then breaksout, this is a confirmed distribution and upward price movement will typically ensue)
Red/green lines are the moving averages of accumulation and distribution. These lines are absolutely critical to keep an eye on, because they are the gateway to a greater macro-trend. When any interaction takes place with these lines (e.g., price, accum./dist. regions, etc), there is a greater force at play, presenting itself. Just like a MACD represents two different moving averages... any cross is significant... this principal also applies to the clouds of accum./dist. and their EMA lines.
Green/Red Lines are the exponential moving averages (200) of each confirmed Wyckoff Spring /UTAD occurrences. When price interacts w/ this line, it will either cause volatility . If price recovers off of the spring EMA , it is a sign of strength. If it is rejected off of the UTAD EMA , it is a sign of weakness or an SOS (sign of strength)
Buy/sell signals (red/green arrows) are signals that confirm trend. You can interpret these as buy/sell signals. But you should always be aware of what the greater macro trend is. If your 4h chart is showing a resistance at the 200 dist. EMA, but your 5 minute is showing a resistance, you should interpret this bearishly. But again, this is all contextual.
Other tidbits and utterances
Remember to determine the macro-trend before committing to any ideas of what your security is likely to do.
It is highly recommended that you use multiple instances of this script to gain a composite-view of what the security is doing. To do this, add another instance, and set your scanning length to a different value than the others. When you combine multiple instances of this, you can gain an even greater insight. For example, when accumulation regions overlap, this is a bullish signal. (The practical translation is: if accumulation regions overlap from 2 different timeframes, then typically a MM/Institution will seek a higher range to accumulate, later distribute, because 2 different timeframes have no more range to the downside to accumulate)
Be sure to use your utmost curiosity when factoring this script into your analysis, there are tons of interactions that the data of this script presents. (i.e., spring and UTAD clouds will sometimes bounce right off of each other in succession, which is a golden-occurrence and can lead to significant upside. (You can see this on the 1d, 1w chart of BTC )
All feedback, critiques, observations, etc, are welcomed and requested.
Cheers
Momentum Explosion 2CCI RSI"Momentum Explosion Template for Mobile Metatrader", that is a trading system trend momentum based on two Commodity Channel Index (CCI) , RSI and two Moving Averages.The trading signals are generated by the crossing of the moving averages confirmed by the agreement of the two CCIs and the RSI.
Two Moving averages Filtered by double CCI and RSI
Credit is to Dimitri Author Beejay (Forex Factory)
Trading Rules Momentum Explosion
Buy
EMA 8 crosses upward SMA 26.
CCI 34 periods > 0
CCI 55 periods > 0
RSI 26 > 48.
Sell
EMA 8 crosses downward SMA 26.
CCI 34 periods < 0
CCI 55 periods < 0
RSI 26 < 48.
Triangular Moving Average (TRIMA)The Triangular Moving Average (TRIMA) is a technical indicator that applies a triangular weighting scheme to price data, providing enhanced smoothing compared to simpler moving averages. Originating in the early 1970s as technical analysts sought more effective noise filtering methods, the TRIMA was first popularized through the work of market technician Arthur Merrill. Its formal mathematical properties were established in the 1980s, and the indicator gained widespread adoption in the 1990s as computerized charting became standard. TRIMA effectively filters out market noise while maintaining important trends through its unique center-weighted calculation method.
## Core Concepts
* **Double-smoothing process:** TRIMA can be viewed as applying a simple moving average twice, creating more effective noise filtering
* **Triangular weighting:** Uses a symmetrical weight distribution that emphasizes central data points and reduces emphasis toward both ends
* **Constant-time implementation:** Two $O(1)$ SMA passes with circular buffers preserve exact triangular weights while keeping update cost constant per bar
* **Market application:** Particularly effective for identifying the underlying trend in noisy market conditions where standard moving averages generate too many false signals
* **Timeframe flexibility:** Works across multiple timeframes, with longer periods providing cleaner trend signals in higher timeframes
The core innovation of TRIMA is its unique triangular weighting scheme, which can be viewed either as a specialized weight distribution or as a twice-applied simple moving average with adjusted period. This creates more effective noise filtering without the excessive lag penalty typically associated with longer-period averages. The symmetrical nature of the weight distribution ensures zero phase distortion, preserving the timing of important market turning points.
## Common Settings and Parameters
| Parameter | Default | Function | When to Adjust |
|-----------|---------|----------|---------------|
| Length | 14 | Controls the lookback period | Increase for smoother signals in volatile markets, decrease for responsiveness |
| Source | close | Price data used for calculation | Consider using hlc3 for a more balanced price representation |
**Pro Tip:** For a good balance between smoothing and responsiveness, try using a TRIMA with period N instead of an SMA with period 2N - you'll get similar smoothing characteristics but with less lag.
## Calculation and Mathematical Foundation
**Simplified explanation:**
TRIMA calculates a weighted average of prices where the weights form a triangle shape. The middle prices get the most weight, and weights gradually decrease toward both the recent and older ends. This creates a smooth filter that effectively removes random price fluctuations while preserving the underlying trend.
**Technical formula:**
TRIMA = Σ(Price × Weight ) / Σ(Weight )
Where the triangular weights form a symmetric pattern:
- Weight = min(i, n-1-i) + 1
- Example for n=5: weights =
- Example for n=4: weights =
Alternatively, TRIMA can be calculated as:
TRIMA(source, p) = SMA(SMA(source, (p+1)/2), (p+1)/2)
> 🔍 **Technical Note:** The double application of SMA explains why TRIMA provides better smoothing than a single SMA or WMA. This approach effectively applies smoothing twice with optimal period adjustment, creating a -18dB/octave roll-off in the frequency domain compared to -6dB/octave for a simple moving average, and the current implementation achieves $O(1)$ complexity through circular buffers and NA-safe warmup compensation.
## Interpretation Details
TRIMA can be used in various trading strategies:
* **Trend identification:** The direction of TRIMA indicates the prevailing trend
* **Signal generation:** Crossovers between price and TRIMA generate trade signals with fewer false alarms than SMA
* **Support/resistance levels:** TRIMA can act as dynamic support during uptrends and resistance during downtrends
* **Trend strength assessment:** Distance between price and TRIMA can indicate trend strength
* **Multiple timeframe analysis:** Using TRIMAs with different periods can confirm trends across different timeframes
## Limitations and Considerations
* **Market conditions:** Like all moving averages, less effective in choppy, sideways markets
* **Lag factor:** More lag than WMA or EMA due to center-weighted emphasis
* **Limited adaptability:** Fixed weighting scheme cannot adapt to changing market volatility
* **Response time:** Takes longer to reflect sudden price changes than directionally-weighted averages
* **Complementary tools:** Best used with momentum oscillators or volume indicators for confirmation
## References
* Ehlers, John F. "Cycle Analytics for Traders." Wiley, 2013
* Kaufman, Perry J. "Trading Systems and Methods." Wiley, 2013
* Colby, Robert W. "The Encyclopedia of Technical Market Indicators." McGraw-Hill, 2002
Heikin-Ashi Mean Reversion Oscillator [Alpha Extract]The Heikin-Ashi Mean Reversion Oscillator combines the smoothing characteristics of Heikin-Ashi candlesticks with mean reversion analysis to create a powerful momentum oscillator. This indicator applies Heikin-Ashi transformation twice - first to price data and then to the oscillator itself - resulting in smoother signals while maintaining sensitivity to trend changes and potential reversal points.
🔶 CALCULATION
Heikin-Ashi Transformation: Converts regular OHLC data to smoothed Heikin-Ashi values
Component Analysis: Calculates trend strength, body deviation, and price deviation from mean
Oscillator Construction: Combines components with weighted formula (40% trend strength, 30% body deviation, 30% price deviation)
Double Smoothing: Applies EMA smoothing and second Heikin-Ashi transformation to oscillator values
Signal Generation: Identifies trend changes and crossover points with overbought/oversold levels
Formula:
HA Close = (Open + High + Low + Close) / 4
HA Open = (Previous HA Open + Previous HA Close) / 2
Trend Strength = Normalized consecutive HA candle direction
Body Deviation = (HA Body - Mean Body) / Mean Body * 100
Price Deviation = ((HA Close - Price Mean) / Price Mean * 100) / Standard Deviation * 25
Raw Oscillator = (Trend Strength * 0.4) + (Body Deviation * 0.3) + (Price Deviation * 0.3)
Final Oscillator = 50 + (EMA(Raw Oscillator) / 2)
🔶 DETAILS Visual Features:
Heikin-Ashi Candlesticks: Smoothed oscillator representation using HA transformation with vibrant teal/red coloring
Overbought/Oversold Zones: Horizontal lines at customizable levels (default 70/30) with background highlighting in extreme zones
Moving Averages: Optional fast and slow EMA overlays for additional trend confirmation
Signal Dashboard: Real-time table showing current oscillator status (Overbought/Oversold/Bullish/Bearish) and buy/sell signals
Reference Lines: Middle line at 50 (neutral), with 0 and 100 boundaries for range visualization
Interpretation:
Above 70: Overbought conditions, potential selling opportunity
Below 30: Oversold conditions, potential buying opportunity
Bullish HA Candles: Green/teal candles indicate upward momentum
Bearish HA Candles: Red candles indicate downward momentum
MA Crossovers: Fast EMA above slow EMA suggests bullish momentum, below suggests bearish momentum
Zone Exits: Price moving out of extreme zones (above 70 or below 30) often signals trend continuation
🔶 EXAMPLES
Mean Reversion Signals: When the oscillator reaches extreme levels (above 70 or below 30), it identifies potential reversal points where price may revert to the mean.
Example: Oscillator reaching 80+ levels during strong uptrends often precedes short-term pullbacks, providing profit-taking opportunities.
Trend Change Detection: The double Heikin-Ashi smoothing helps identify genuine trend changes while filtering out market noise.
Example: When oscillator HA candles change from red to teal after oversold readings, this confirms potential trend reversal from bearish to bullish.
Moving Average Confirmation: Fast and slow EMA crossovers on the oscillator provide additional confirmation of momentum shifts.
Example: Fast EMA crossing above slow EMA while oscillator is rising from oversold levels provides strong bullish confirmation signal.
Dashboard Signal Integration: The real-time dashboard combines oscillator status with directional signals for quick decision-making.
Example: Dashboard showing "Oversold" status with "BUY" signal when HA candles turn bullish provides clear entry timing.
🔶 SETTINGS
Customization Options:
Calculation: Oscillator period (default 14), smoothing factor (1-50, default 2)
Levels: Overbought threshold (50-100, default 70), oversold threshold (0-50, default 30)
Moving Averages: Toggle display, fast EMA length (default 9), slow EMA length (default 21)
Visual Enhancements: Show/hide signal dashboard, customizable table position
Alert Conditions: Oversold bounce, overbought reversal, bullish/bearish MA crossovers
The Heikin-Ashi Mean Reversion Oscillator provides traders with a sophisticated momentum tool that combines the smoothing benefits of Heikin-Ashi analysis with mean reversion principles. The double transformation process creates cleaner signals while the integrated dashboard and multiple confirmation methods help traders identify high-probability entry and exit points during both trending and ranging market conditions.
Triple Exponential Moving Average (TEMA)The Triple Exponential Moving Average (TEMA) is an advanced technical indicator designed to significantly reduce the lag inherent in traditional moving averages while maintaining signal quality. Developed by Patrick Mulloy in 1994 as an extension of his DEMA concept, TEMA employs a sophisticated triple-stage calculation process to provide exceptionally responsive market signals.
TEMA's mathematical approach goes beyond standard smoothing techniques by using a triple-cascade architecture with optimized coefficients. This makes it particularly valuable for traders who need earlier identification of trend changes without sacrificing reliability. Since its introduction, TEMA has become a key component in many algorithmic trading systems and professional trading platforms.
▶️ **Core Concepts**
Triple-stage lag reduction: TEMA uses a three-level EMA calculation with optimized coefficients (3, -3, 1) to dramatically minimize the delay in signal generation
Enhanced responsiveness: Provides significantly faster reaction to price changes than standard EMA or even DEMA, while maintaining reasonable smoothness
Strategic signal processing: Employs mathematical techniques to extract the underlying trend while filtering random price fluctuations
Timeframe effectiveness: Performs well across multiple timeframes, though particularly valued in short to medium-term trading
TEMA achieves its enhanced responsiveness through an innovative triple-cascade architecture that strategically combines three levels of exponential moving averages. This approach effectively removes the lag component inherent in EMA calculations while preserving the essential smoothing benefits.
▶️ **Common Settings and Parameters**
Length: Default: 12 | Controls sensitivity/smoothness | When to Adjust: Increase in choppy markets, decrease in strongly trending markets
Source: Default: Close | Data point used for calculation | When to Adjust: Change to HL2/HLC3 for more balanced price representation
Corrected: Default: false | Adjusts internal EMA smoothing factors for potentially faster response | When to Adjust: Set to true for a modified TEMA that may react quicker to price changes. false uses standard TEMA calculation
Visualization: Default: Line | Display format on charts | When to Adjust: Use filled cloud to see divergence from price more clearly
Pro Tip: For optimal trade signals, many professional traders use two TEMAs (e.g., 8 and 21 periods) and look for crossovers, which often provide earlier signals than traditional moving average pairs.
▶️ **Calculation and Mathematical Foundation**
Simplified explanation:
TEMA calculates three levels of EMAs, then combines them using a special formula that amplifies recent price action while reducing lag. This triple-processing approach effectively eliminates much of the delay found in traditional moving averages.
Technical formula:
TEMA = 3 × EMA₁ - 3 × EMA₂ + EMA₃
Where:
EMA₁ = EMA(source, α₁)
EMA₂ = EMA(EMA₁, α₂)
EMA₃ = EMA(EMA₂, α₃)
The smoothing factors (α₁, α₂, α₃) are determined as follows:
Let α_base = 2/(length + 1)
α₁ = α_base
If corrected is false:
α₂ = α_base
α₃ = α_base
If corrected is true:
Let r = (1/α_base)^(1/3)
α₂ = α_base * r
α₃ = α_base * r * r = α_base * r²
The corrected = true option implements a variation that uses progressively smaller alpha values for the subsequent EMA calculations. This approach aims to optimize the filter's frequency response and phase lag.
Alpha Calculation for corrected = true:
α₁ (alpha_base) = 2/(length + 1)
r = (1/α₁)^(1/3) (cube root relationship)
α₂ = α₁ * r = α₁^(2/3)
α₃ = α₂ * r = α₁^(1/3)
Mathematical Rationale for Corrected Alphas:
1. Frequency Response Balance:
The standard TEMA (where α₁ = α₂ = α₃) can lead to an uneven frequency response, potentially over-smoothing high frequencies or creating resonance artifacts. The geometric progression of alphas (α₁ > α₁^(2/3) > α₁^(1/3)) in the corrected version aims to create a more balanced filter cascade. Each stage contributes more proportionally to the overall frequency response.
2. Phase Lag Optimization:
The cube root relationship between the alphas is designed to minimize cumulative phase lag while maintaining smoothing effectiveness. Each subsequent EMA stage has a progressively smaller impact on phase distortion.
3. Mathematical Stability:
The geometric progression (α₁, α₁^(2/3), α₁^(1/3)) can enhance numerical stability due to constant ratios between consecutive alphas. This helps prevent the accumulation of rounding errors and maintains consistent convergence properties.
Practical Impact of corrected = true:
This modification aims to achieve:
Potentially better lag reduction for a similar level of smoothing
A more uniform frequency response across different market cycles
Reduced overshoot or undershoot in trending conditions
Improved signal-to-noise ratio preservation
Essentially, the cube root relationship in the corrected TEMA attempts to optimize the trade-off between responsiveness and smoothness that can be a challenge with uniform alpha values.
🔍 Technical Note: Advanced implementations apply compensation techniques to all three EMA stages, ensuring TEMA values are valid from the first bar without requiring a warm-up period. This compensation corrects initialization bias and prevents calculation errors from compounding through the cascade.
▶️ **Interpretation Details**
TEMA excels at identifying trend changes significantly earlier than traditional moving averages, making it valuable for both entry and exit signals:
When price crosses above TEMA, it often signals the beginning of an uptrend
When price crosses below TEMA, it often signals the beginning of a downtrend
The slope of TEMA provides insight into trend strength and momentum
TEMA crossovers with price tend to occur earlier than with standard EMAs
When multiple-period TEMAs cross each other, they confirm significant trend shifts
TEMA works exceptionally well as a dynamic support/resistance level in trending markets
For optimal results, traders often use TEMA in combination with momentum indicators or volume analysis to confirm signals and reduce false positives.
▶️ **Limitations and Considerations**
Market conditions: The high responsiveness can generate false signals during highly choppy, sideways markets
Overshooting: More aggressive lag reduction leads to more pronounced overshooting during sharp reversals
Parameter sensitivity: Changes in length have more dramatic effects than in simpler moving averages
Calculation complexity: Triple cascaded EMAs make behavior less predictable and more resource-intensive
Complementary tools: Should be used with confirmation tools like RSI, MACD or volume indicators
▶️ **References**
Mulloy, P. (1994). "Smoothing Data with Less Lag," Technical Analysis of Stocks & Commodities .
Mulloy, P. (1995). "Comparing Digital Filters," Technical Analysis of Stocks & Commodities .
NQ/MNQ Futures Delta+ with Price Action EntriesNQ/MNQ Futures Delta+ with Price Action Entries
Description: This TradingView indicator combines Futures Delta analysis with advanced price action techniques to provide an enhanced trading strategy for the NQ/MNQ futures market. The script analyzes the market using a variety of methods including Delta, volume analysis, and candlestick patterns, while also incorporating price action factors like support/resistance levels and breakouts to offer more refined buy and sell signals.
Key Features:
Delta Analysis:
The Delta calculation tracks the difference between buying and selling pressure within each market bar. The indicator calculates delta based on different modes (Classic, Volume Based, Tick Based), and then applies cumulative delta for trend analysis.
The Cumulative Delta is calculated using one of the three available modes:
Total: Tracks the cumulative delta over time.
Periodic: Measures delta over a defined period (user-configurable).
EMA: Applies an Exponential Moving Average to smooth the delta values.
Volume Confirmation:
The script includes volume analysis to confirm price movements. A volume spike is used to validate buy/sell signals, ensuring that price movements are supported by significant trading volume.
Price Action-Based Entries:
Support and Resistance: Dynamic support and resistance levels are calculated based on the lowest low and highest high of the last 20 bars. These levels are used to identify breakout points, providing context for potential buy/sell entries.
Candlestick Patterns: The script recognizes Bullish Engulfing and Bearish Engulfing candlestick patterns. These patterns signal potential reversals in price direction and are used to confirm trade entries.
Breakout Logic: Buy signals are triggered when the price breaks above resistance, and sell signals are triggered when the price breaks below support, providing high-probability entry points during trend reversals or continuations.
Moving Average Trend Confirmation:
The script uses two moving averages:
9-period Exponential Moving Average (EMA): Short-term trend indicator.
21-period Exponential Moving Average (EMA): Longer-term trend indicator.
Trades are only considered in the direction of the prevailing trend:
A bullish signal is confirmed if the price is above both EMAs.
A bearish signal is confirmed if the price is below both EMAs.
Buy/Sell Signal Triggers:
Buy Signal: A buy signal is triggered when:
A bullish divergence is confirmed with volume support.
A bullish engulfing candlestick pattern forms.
The price breaks above resistance.
The price is above both the 9 EMA and 21 EMA, indicating an uptrend.
Sell Signal: A sell signal is triggered when:
A bearish divergence is confirmed with volume support.
A bearish engulfing candlestick pattern forms.
The price breaks below support.
The price is below both the 9 EMA and 21 EMA, indicating a downtrend.
Visualization:
Delta Candles: The cumulative delta is plotted as a candlestick on the chart, with green and red coloring to show buying or selling dominance.
Support and Resistance Levels: Support and resistance zones are plotted to show key levels where price action may react.
Moving Averages: The 9 EMA and 21 EMA are plotted to show short-term and long-term trend direction.
Signal Markers: Buy and sell signals are marked on the chart with green triangles (buy) and red triangles (sell) for easy visualization of trade opportunities.
Alerts:
Alerts can be set up for buy and sell signals, enabling you to be notified when the script identifies potential trade opportunities based on Delta analysis, volume confirmation, and price action.
How to Use This Script:
Market: This script is optimized for NQ and MNQ futures contracts but can be adapted for other markets as well.
Signal Interpretation: Use the buy and sell signals for trend-following or counter-trend trades. These signals are particularly useful for 1-minute or 5-minute charts but can be adjusted to fit other timeframes.
Support/Resistance: Pay close attention to the dynamic support and resistance levels, as these are key price action points where significant price movements can occur.
Trend Confirmation: Ensure that trades are aligned with the overall trend confirmed by the 9 EMA and 21 EMA. The script prioritizes signals that align with the broader market trend.
Breakouts: Use the breakout logic to catch price moves when the market breaks key support or resistance levels. These can often lead to strong moves in the direction of the breakout.
Pro Volume By TradeINskiOverview
The Pro Volume By TradeINski indicator is a comprehensive trading tool designed to enhance volume analysis, position sizing, and trend identification. It integrates multiple trading metrics into a single dashboard, helping traders make informed decisions based on volume dynamics, momentum bursts, trend intensity, and risk management.
Key Features
1. Position Size Calculator
Helps traders determine optimal position sizes based on risk parameters:
Capital & Risk Amount: Set account size and risk per trade.
Lot Size Adjustments: Automatically calculates nearest lot size for futures trading.
Stop Loss-Based Quantity: Computes position size based on distance from stop-loss levels (LOD or mid-price).
Standard Stop Losses: Predefined stop-loss levels (1%, 1.25%, 1.5%, 1.75%) for quick risk assessment.
Reverse Pyramiding: Enhances position sizing with adjustable risk multipliers (25%, 50%).
Closing Range & Range Expansion: Measures price strength and volatility expansion.
2. Volume Analysis & Bar Coloring
Default Bar Colors: Green for bullish bars, red for bearish bars.
Dry Volume Detection: Highlights low-volume bars (below 20-period SMA) in gray.
3. Momentum Burst (MB)
Identifies high-momentum moves:
Bullish Momentum: Volume surge + price rise ≥ user-defined threshold (default: 4%).
Bearish Momentum: Volume surge + price drop ≥ user-defined threshold (default: -4%).
4. Trend Intensity (TI)
Measures trend strength using moving averages:
Fast MA (7) vs. Slow MA (65): Highlights strong bullish/bearish trends when deviation exceeds sensitivity threshold (default: 5%).
5. Anticipation (ANTS)
Detects consolidation before potential breakouts:
Price Change Range: Filters minor price fluctuations (default: -0.4% to +0.4%).
Trend Confirmation: Requires TI_65 sensitivity (default: 5%) for validation.
6. Episodic Pivot (EP)
Flags unusually high-volume bars (default: 9M+ volume) as potential trend reversal or continuation signals.
7. Data Metrics Table
Displays key trading metrics:
Trend Intensity (TI): 21-period SMA comparison.
Industry & Sector: Stock classification.
Market Cap & Free Float: Fundamental liquidity metrics.
Volume × Price (VP): Monetary value of traded volume.
Relative Volume (RV): Today’s volume vs. previous day.
Persistent Intensity (PI): Count of consecutive up closes (default: 21-period).
Use Cases for Traders
✅ Day Traders: Identify momentum bursts and high-volume breakouts.
✅ Swing Traders: Use trend intensity and episodic pivots to confirm trends.
✅ Position Traders: Optimize risk with dynamic position sizing.
✅ Risk Managers: Set stop-loss levels and reverse pyramiding for controlled exposure.
Settings & Customization Overview
The Pro Volume By TradeINski indicator is a comprehensive trading tool designed to enhance volume analysis, position sizing, and trend identification. It integrates multiple trading metrics into a single dashboard, helping traders make informed decisions based on volume dynamics, momentum bursts, trend intensity, and risk management.
Key Features
1. Position Size Calculator
Helps traders determine optimal position sizes based on risk parameters:
Capital & Risk Amount: Set account size and risk per trade.
Lot Size Adjustments: Automatically calculates nearest lot size for futures trading.
Stop Loss-Based Quantity: Computes position size based on distance from stop-loss levels (LOD or mid-price).
Standard Stop Losses: Predefined stop-loss levels (1%, 1.25%, 1.5%, 1.75%) for quick risk assessment.
Reverse Pyramiding: Enhances position sizing with adjustable risk multipliers (25%, 50%).
Closing Range & Range Expansion: Measures price strength and volatility expansion.
2. Volume Analysis & Bar Coloring
Default Bar Colors: Green for bullish bars, red for bearish bars.
Dry Volume Detection: Highlights low-volume bars (below 20-period SMA) in gray.
3. Momentum Burst (MB)
Identifies high-momentum moves:
Bullish Momentum: Volume surge + price rise ≥ user-defined threshold (default: 4%).
Bearish Momentum: Volume surge + price drop ≥ user-defined threshold (default: -4%).
4. Trend Intensity (TI)
Measures trend strength using moving averages:
Fast MA (7) vs. Slow MA (65): Highlights strong bullish/bearish trends when deviation exceeds sensitivity threshold (default: 5%).
5. Anticipation (ANTS)
Detects consolidation before potential breakouts:
Price Change Range: Filters minor price fluctuations (default: -0.4% to +0.4%).
Trend Confirmation: Requires TI_65 sensitivity (default: 5%) for validation.
6. Episodic Pivot (EP)
Flags unusually high-volume bars (default: 9M+ volume) as potential trend reversal or continuation signals.
7. Data Metrics Table
Displays key trading metrics:
Trend Intensity (TI): 21-period SMA comparison.
Industry & Sector: Stock classification.
Market Cap & Free Float: Fundamental liquidity metrics.
Volume × Price (VP): Monetary value of traded volume.
Relative Volume (RV): Today’s volume vs. previous day.
Persistent Intensity (PI): Count of consecutive up closes (default: 21-period).
Use Cases for Traders
✅ Day Traders: Identify momentum bursts and high-volume breakouts.
✅ Swing Traders: Use trend intensity and episodic pivots to confirm trends.
✅ Position Traders: Optimize risk with dynamic position sizing.
✅ Risk Managers: Set stop-loss levels and reverse pyramiding for controlled exposure.
Settings & Customization
Trade Direction: Long, Short, or Both (auto-detects based on % change).
Table Positioning: Adjust location (Top/Middle/Bottom, Left/Center/Right).
Color Customization: Modify bar colors, table lines, and background.
Trade Direction: Long, Short, or Both (auto-detects based on % change).
Table Positioning: Adjust location (Top/Middle/Bottom, Left/Center/Right).
Color Customization: Modify bar colors, table lines, and background.
Uptrick: Oscillator SpectrumUptrick: Oscillator Spectrum is a versatile trading tool designed to bring together multiple aspects of technical analysis—oscillators, momentum signals, divergence checks, correlation insights, and more—into one script. It includes customizable overlays and alert conditions intended to address a wide range of market conditions and trading styles.
Developed in Pine Script™, Uptrick: Oscillator Spectrum represents an extended version of the classic Ultimate Oscillator concept. It consolidates short-, medium-, and long-term momentum readings, applies correlation analysis across different symbols, and offers optional table-based metrics to provide traders with a more structured overview of potential trade setups. Whether used alongside your existing charts or as a standalone toolkit, it aims to build on and enhance the functionality of the standard Ultimate Oscillator.
### A Few Key Features
- Momentum Insights: Multiple timeframes for oscillators, plus buy/sell signal modes for flexible identification of overbought/oversold situations or crossovers.
- Divergence Detection: Automated checks for bullish/bearish divergences, aiming to help traders spot potential shifts in momentum.
- Correlation Meter: A visual histogram summarizing how selected assets are collectively trending. It is useful for tracking the bigger market picture.
- Gradient Overlays & Bar Coloring: Dynamic color transitions designed to emphasize changes in momentum, trend shifts, and overall sentiment without cluttering the chart.
- Money Flow Tracker: Tracks the flow of money into and out of the market using a smoothed Money Flow Index (MFI). Highlights overbought/oversold conditions with dynamic bar coloring and visual gradient fills, helping traders assess volume-driven sentiment shifts.
- Advanced Table Metrics: An optional table showing return on investment (ROI), collateral risk, and other contextual metrics for supported assets.
- Alerts & Automation: Configurable alerts covering divergence events, crossing of critical levels, and more, helping to keep traders informed of developments in real time.
### Intended Usage
- For Multiple Markets: Works on various markets (cryptocurrencies, forex pairs, stocks) to deliver a consistent view of momentum, potential entry/exit signals, and correlation.
- Adaptable Trading Styles: With customizable input settings, you can enable or disable specific features to align with your preferred strategies—intraday scalping, swing trading, or position holding.
By combining these elements under one indicator, Uptrick: Oscillator Spectrum allows traders to streamline analysis workflows, helping them stay focused on interpreting market moves and making informed decisions rather than juggling multiple scripts.
Purpose
Purpose of the “Uptrick: Oscillator Spectrum” Indicator
The “Uptrick: Oscillator Spectrum” indicator is intended to bring together several technical analysis elements into one tool. It combines oscillator-based momentum readings across different lookback periods, checks for potential divergences, provides optional buy/sell signal triggers, and offers correlation-based insights across multiple symbols. Additionally, it includes features such as bar coloring, gradient visualization, and user-configurable alerts to help highlight various market conditions.
By consolidating these functions, the script aims to help users systematically observe changing momentum, identify when prices reach user-defined overbought or oversold levels, detect when oscillator movements diverge from price, and examine whether different assets are aligning or diverging in their trends. The indicator also allows for optional advanced metric tables, which can supply further context on risk, ROI calculations, or other factors for supported assets. Overall, the script’s purpose is to organize multiple layers of technical analysis so that users have a structured way to evaluate potential trade opportunities and market behavior.
## Usage Guide
Below is an outline of how you can utilize the various components and features of Uptrick: Oscillator Spectrum in your charting workflow.
---
### 1. Using the Core Oscillator
- Basic View: By default, the script calculates a multi-timeframe oscillator (commonly displayed as the “Ultimate Oscillator”). This oscillator combines short-, medium-, and long-term measurements of buying pressure and true range.
- Overbought/Oversold Zones: You can configure thresholds (e.g., 70 for overbought, 30 for oversold) to help identify potential turning points. When the oscillator crosses these levels, it may indicate that price is extended in one direction.
- You can use the colors of the main oscillator to help you take short-term trades as well: cyan : Buy , red: Sell
- Alerts: If you enable alerts, the indicator can notify you when the oscillator crosses above or below your chosen overbought/oversold boundaries or when you get buy/sell signals.
---
### 2. Buy/Sell Signals in Overlay Modes
Uptrick: Oscillator Spectrum provides several signal modes and a choice between overlay true and overlay false or both. Additionally, you can pick which “line” (data source) the script uses to generate signals. This is set in the “Line to Analyze” dropdown, which includes Oscillator, HMA of Oscillator, and Moving Average. The following sections describe how each piece fits together.
---
#### Line to Analyze - Overlay Flase: Oscillator / HMA of Oscillator / Moving Average
1. Oscillator
- The core momentum reading, reflecting short-, medium-, and long-term periods combined.
2. HMA of Oscillator
- Applies a Hull Moving Average to the oscillator, creating a smoother but still responsive curve.
- Signals will be derived from this smoothed line. Some traders find it filters out minor fluctuations while remaining quicker to react than standard averages.
3. Moving Average
- Uses a user-selected MA type (SMA, EMA, WMA, etc.) over the oscillator values, rather than the raw oscillator itself.
- Tends to be more stable than the raw oscillator, but might delay signals more depending on the chosen MA settings.
---
#### Signal Modes
Regardless of which line you choose to analyze, you can use one of the following seven signal modes in overlay being true:
1. Overbought/Oversold (Pyramiding)
- What It Does:
- Buy signal when the chosen line crosses below the oversold threshold.
- Sell signal when it crosses above the overbought threshold.
- Pyramiding:
- Allows multiple triggers within the same overbought/oversold event.
2. Overbought/Oversold (Non Pyramiding)
- What It Does:
- Same thresholds but only one signal per oversold or overbought event.
- Use Case:
- Prevents repeated signals and chart clutter.
3. Smoothed MA Middle Crossover
- What It Does:
- Uses an MA defined by the user.
- Buy when crossing above the midpoint (50), Sell when crossing below.
- Use Case:
- Generates fewer signals, focusing on broader momentum shifts. There is no pyramiding.
In this image ,for example, the VWMA is used with length of 14 to identify buy sell signals.
4. Crossing Above Overbought/Below Oversold (Non Pyramiding)
- What It Does:
- Buy occurs if the line exits oversold territory by crossing back above it.
- Sell occurs if the line exits overbought territory by crossing back below it.
- Non Pyramiding:
- Restricts repeated signals until conditions reset.
5. Crossing Above Overbought/Below Oversold (Pyramiding)
- What It Does:
- Same thresholds, but allows multiple signals if the line repeatedly dips in and out of overbought or oversold.
- Use Case:
- More frequent entries/exits for active traders.
6. Divergence (Non Pyramiding)
- What It Does:
- Identifies bullish or bearish divergences using the chosen line vs. price.
- Buy for bullish divergence (higher low on the line vs. lower low on price), Sell for bearish divergence.
- Single Trigger:
- Only one signal per identified divergence event. (non pyramiding)
7. Divergence (Pyramiding)
- What It Does:
- Same divergence logic but triggers multiple times if the script sees repeated divergence in the same direction.
- Use Case:
- Could suit traders who layer positions during sustained divergence scenarios.
#### Overlay Modes: True vs. False
1. Overlay True
- Buy/sell arrows or labels plot directly on the main price chart, often at or near candlesticks.
- Bar Coloring:
- Can turn the candlestick bars green (buy) or red (sell), with intensity reflecting signal recency if bar coloring is enabled for this mode. (read below.)
- Advantage:
- Everything (price, signals, bar colors) is in one spot, making it straightforward to associate signals with current market action. You can adjust the periods of the main oscillator or lookback periods of divergences or overbought/oversold thresholds, to play around with your signals.
2. Overlay False
- Signal Placement:
- Signals appear in a sub-window or oscillator panel, leaving the main price chart uncluttered.
- Bar Coloring:
- You may still enable bar colors on the main chart (green for buy, red for sell) if desired.
- Alternatively, you can keep them neutral if you prefer a completely separate display of signals.
- Advantage:
- Clear separation of price action from signals, useful for cleaner charts or if using multiple overlay-based tools.
At the bottom are the signals for overlay being false and on the chart are the signals for overlay being true:
#### Bar Color Adjustments
1. Coloring Logic
- Bars typically go green on buy signals, red on sell signals.
- The opacity or brightness can vary to indicate signal freshness. When a new signal is formed, the color gets brighter. When there is no signal for a longer period of time, then the color slowly fades.
2. Enabling Bar Coloring
- In the indicator’s settings, turn on Bar Coloring.
- Choose “Signals Overlay True” or “Signals Overlay False” from the “Color should depend on:” dropdown, depending on which overlay approach you want to drive your bar colors. You can also chose the cloud fill in overlay false, correlation meter and smoothed HMA to color bars. Read more below:
### Bar Color Options:
When you enable bar coloring in Uptrick: Oscillator Spectrum, you can select which component or signal logic drives the color changes. Below are the five available choices:
---
#### Option 1: Overlay True Signals
- What It Does:
- Uses signals generated under the Overlay True mode to color the bars on your main chart.
- If a buy signal is triggered, bars turn green. If a sell signal occurs, bars turn red.
- Color Intensity:
- Bars appear brighter (more opaque) immediately after a new signal fires, then gradually fade over subsequent bars if no new signal appears.
---
#### Option 2: Overlay False Signals
- What It Does:
- Links bar coloring to signals generated when Overlay False mode is active.
- Buy/sell labels typically plot in a separate sub-window instead of the main chart, but your price bars can still change color based on these signals.
- Color Intensity:
- Similar to Overlay True, new buy/sell signals yield stronger color intensity, which fades over time.
- Use Case:
- Helps maintain a clean main chart (with signals off-chart) while still providing an immediate color-coded indication of a buy or sell state.
- Particularly useful if you prefer less clutter from signal markers on your price chart yet still want a visual representation of signal timing.
In this example normal divergence Pyramiding Signals are used in the overlay being true and the signals in overlay false are signals that analyze the HMA. This can help clear out noise (using a combo of both).
Option 3: Money Flow Tracker
What It Does:
The Money Flow Tracker uses the Money Flow Index (MFI), a volume-weighted oscillator, to measure the strength of money flowing into or out of an asset. The script smooths the raw MFI data using an EMA for a more responsive and visually intuitive output.
The feature also includes dynamic color gradients and bar coloring that highlight whether money flow is positive or negative.
Green Fill/Bar Color: Indicates positive money flow, suggesting potential accumulation.
Red Fill/Bar Color: Indicates negative money flow, signaling potential distribution.
Overbought and oversold thresholds are dynamically emphasized with transparency, making it easier to identify high-confidence zones.
Use Case:
Ideal for traders focusing on volume-driven sentiment to identify turning points or confirm existing trends.
Suitable for assessing broader market conditions when used alongside other indicators like oscillators or correlation analysis.
Provides additional clarity in spotting areas of accumulation or distribution, making it a valuable complement to price action and momentum studies.
---
#### Option 4: Correlation Meter
- What It Does:
- Colors the bars based on the indicator’s Correlation Meter output. The script checks multiple chosen tickers and sums up how many are trending positively or negatively.
- If the meter indicates an overall bullish bias (e.g., more than three assets in uptrend), bars turn green; if it’s bearish, bars turn red.
- Trend Readings:
- The correlation meter typically plots a histogram of bullish/neutral/bearish states. The bar color option links your chart’s candlestick coloring to that higher-level market sentiment.
- Use Case:
- Useful for traders wanting a quick visual prompt of whether the broader market (or a selection of related assets) is bullish or bearish at any given time.
- Helps avoid signals that conflict with the market majority.
#### Option 5: Smoothed HMA
- What It Does:
- Bar colors are driven by the slope or state of the Hull Moving Average (HMA) of the oscillator, rather than individual buy/sell triggers or correlation data.
- If the HMA indicates a strong upward slope (possibly darkening), bars may turn green; if the slope is downward (purple in the HMA line), bars turn red.
- Use Case:
- Ideal for those who focus on momentum continuity rather than discrete signals like overbought/oversold or divergence.
- May help identify smoother, more sustained moves, as the HMA filters out minor oscillations.
---
### 3. Using the Hull Moving Average (HMA) of the Oscillator
- HMA Calculation: You can enable a dedicated Hull Moving Average (HMA) for the oscillator. This creates a smoother line of the same underlying momentum reading, typically responding more quickly than classic moving averages.
- Color Intensity: As the HMA sustains an uptrend or downtrend, the script can adjust the line’s color. When slope momentum persists in one direction, the color appears more opaque. This intensification can hint that the existing direction may be well-established.
- Reversal Potential: If you observe the HMA color shifting or darkening after multiple bars of slope in the same direction, it may indicate increasing momentum. Conversely, a sudden flattening or change in color can be a clue that momentum is waning.
---
### 4. Moving Average Overlays & Gradient Cloud
- Oscillator MA: The script allows you to apply moving average types (SMA, EMA, SMMA, WMA, or VWMA) to the core oscillator, rather than to price. This can smooth out noise in the oscillator, potentially highlighting more consistent momentum shifts.
- Gradient Cloud: You can also enable a cloud in overlay true between two moving averages (for instance, a Hull MA and a Double EMA) on the price chart. The cloud fills with different colors, depending on which MA is above the other. This can provide a quick visual reference to bullish or bearish areas.
---
### 5. Divergence Detection
- Bullish & Bearish Divergence: By toggling “Calculate Divergence,” the script looks for oscillator pivots that contrast with price pivots (e.g., price making a lower low while the oscillator makes a higher low).
- A divergence is when the price makes an opposite pivot to the indicator value. E.g. Price makes lower low but indicator does higher low - This suggests a bullish divergence. THe opposite is for a bearish divergence.
- Visual Labels: When a divergence is found, labels (such as “Bull” or “Bear”) appear on the oscillator. This helps you see if the oscillator’s momentum patterns differ from the price movement.
- Filtering Signals: You can combine divergence signals with other features like overbought/oversold or the HMA slope to refine potential entries or exits.
---
### 6. Correlation & Multi-Ticker Analysis
- Correlation Meter: You can select up to five tickers in the settings. The script calculates a slope-based metric for each, then combines those metrics to show an overall bullish or bearish tendency (displayed as a histogram).
- Bar Coloring & Overlay: If you activate correlation-based bar coloring, it will reflect the broader trend alignment among the selected assets, potentially indicating when most are trending in the same direction.
- Use Case: If you trade multiple markets, the correlation histogram can help you quickly see if several major assets support the same market bias or are diverging from one another.
—
### 7. Money Flow Tracker
Money Flow Calculation: The Money Flow Tracker calculates the Money Flow Index (MFI) based on price and volume data, factoring in buying pressure and selling pressure. The output is smoothed using a low-lag EMA to reduce noise and enhance usability.
Visual Features:
Dynamic Gradient Fill:
The space between the smoothed MFI line and the midline (set at 50) is filled with a gradient.
Above 50: Green gradient, with intensity increasing as the MFI moves further above the midline.
Below 50: Red gradient, with intensity increasing as the MFI moves further below the midline.
This gradient provides a clear visual representation of money flow strength and direction, making it easier to assess sentiment shifts at a glance.
Overbought/Oversold Levels: Default thresholds are set at 70 (overbought) and 30 (oversold). When the MFI crosses these levels, it signals potential reversals or trend continuations.
Bar Coloring:
Bars turn green for positive money flow and red for negative money flow.
Color intensity fades over time, ensuring recent signals stand out while older ones remain visible without dominating the chart.
Alerts:
Alerts are triggered when the Money Flow Tracker crosses into overbought or oversold zones, keeping traders informed of critical conditions without constant monitoring.
Practical Applications:
Trend Confirmation: Use the Money Flow Tracker alongside the oscillator or HMA to confirm trends or identify potential reversals.
Volume-Based Reversal Signals: Spot turning points where price action aligns with shifts in money flow direction.
Sentiment Analysis: Gauge whether market participants are accumulating (positive flow) or distributing (negative flow) assets, offering an additional layer of insight into price movement.
(Space for an example chart: “Money Flow Tracker with gradient fills and overbought/oversold levels”)
### 8. Putting It All Together
- Combining Signals: A practical approach might be to watch for a bullish divergence in the oscillator, confirm it with a shift in the HMA slope color, and then wait for the price to be near or below oversold conditions. The correlation histogram may further confirm if the broader market is also leaning bullish at that time.
- Visual Cues: Bar coloring adds another layer, making your chart easier to interpret at a glance. You can also set alerts to ensure you don’t miss key events like divergences, crossovers, or moving average flips.
- Flexibility: Not every feature needs to be used simultaneously. You might opt to focus on divergences and overbought/oversold signals, or you could emphasize the correlation histogram and bar colors. The settings let you enable or disable each module to suit your style.
---
### 9. Tips for Customization
- Adjust Periods: Shorter periods can yield more signals but also more noise. Longer periods may provide steadier, but fewer, signals.
- Set Appropriate Alert Conditions: Only alert on events most relevant to your strategy to avoid overload.
- Explore Different MAs: Depending on the instrument, some moving average types may give a smoother or more responsive indication.
- Monitor Risk Management: As with any tool, these signals do not guarantee performance, so consider position sizing and stop-loss strategies.
---
By toggling and experimenting with the features described above—buy/sell signals, divergences, moving averages, dynamic gradient clouds, and correlation analysis—you can tailor Uptrick: Oscillator Spectrum to your specific trading approach. Each module is designed to give you a clearer, structured view of potential momentum shifts, overbought or oversold states, and the alignment or divergence of multiple assets.
## Features Explanation
Below is a detailed overview of key features in Uptrick: Oscillator Spectrum. Each component is designed to provide different angles of market analysis, allowing you to customize the tool to your preferences.
---
### 1. Main Oscillator
- Purpose: The primary oscillator in this script merges short-, medium-, and long-term views of buying pressure and true range into a single line.
- Calculation: It weights each period’s contribution (e.g., a heavier focus on the short period if desired) and normalizes the result on a 0–100 scale, where higher readings may suggest more robust momentum. (like from the classic Ultimate Oscillator)
- Practical Use:
- Traders can watch for overbought/oversold conditions at user-defined thresholds (e.g., 70/30).
- It can also provide a straightforward momentum reading for those who prefer to see if momentum is rising, falling, or leveling off.
---
### 2. HMA of the Smoothed Oscillator
- What It Is: A Hull Moving Average (HMA) applied to the main oscillator values. The HMA is often more responsive than standard MAs, offering smoother lines while preserving relatively quick reaction to changes.
- How It Works:
- The script takes the oscillator’s output and processes it through a Hull MA calculation.
- The HMA’s slope and color can change more dynamically, highlighting sharper momentum shifts.
- Why It’s Useful:
- By smoothing out minor fluctuations, the HMA can highlight trends in the oscillator’s trajectory.
- If you see an extended run in the HMA slope, it may indicate a more persistent trend in momentum.
- Color Intensity:
- As the HMA continues in one direction for several bars, the script can intensify the color, signaling stronger or more sustained momentum in that direction.
- Sudden changes in color or slope can signal the start of a new momentum swing.
---
### 3. Gradient Fill
This script uses two gradient-based visual elements:
1. Shining/Layered Gradient on the Main Oscillator
- Purpose: Adds multiple layers around the oscillator line (above and below) to emphasize slope changes and highlight how quickly the oscillator is moving up or down.
- Color Changes:
- When the oscillator rises, it uses a color scheme (e.g., aqua/blue) that intensifies as the slope grows.
- When the oscillator declines, it uses a distinct color (e.g., red/pink).
- User Benefit: Makes it easier to see at a glance if momentum is accelerating or decelerating, beyond just the numerical reading.
2. Dynamic Cloud Fill (Between MAs)
- Purpose: Allows you to plot two moving averages (for example, a short-term Hull MA and a longer-term DEMA) and fill the area between them with a color gradient.
- Bullish vs. Bearish:
- When the short MA is above the long MA, the cloud might appear in a greenish hue.
- When the short MA is below the long MA, the cloud can switch to red or another color.
- Transparency/Intensity:
- The fill can get more opaque if the difference between the two MAs is large, indicating a stronger trend but a higher probability of a reversal.
- User Benefit: Helps visualize changes in trend or momentum across multiple time horizons, all within a single chart overlay.
---
### 4. Correlation Meter & Symbol Inputs
- What It Is: This feature looks at multiple user-selected symbols (e.g., BTC, ETH, BNB, etc.) and computes each symbol’s short-term slope. It then aggregates these slopes into an overall “trend” score.
- Inputs Configuration:
1. Ticker Inputs: You can specify up to five different tickers.
2. Timeframe: Decide whether to pull data from different chart timeframes for each symbol.
3. Slope Calculation: The script may compute, for instance, a 5-period SMA minus a 20-period SMA to gauge if each symbol is trending up or down.
- Market Trend Histogram:
- Displays a column that goes above/below zero depending on how many symbols are bullish or bearish.
- If more than three (out of five) symbols are bullish, the histogram can show a green bar at +1; if fewer than three are bullish, it can show red at –1.
- How to Use:
- Quick Glance: Lets you know if most correlated assets are aligning or diverging.
- Bar Coloring (Optional): If enabled, your main chart’s bars can reflect the aggregated correlation, turning green or red depending on the meter’s reading.
---
### 5. Advanced Metrics Table
- What It Is: An optional table displaying additional metrics for several cryptocurrencies (or any symbols you define).
- Metrics Included:
1. ROI (30D): Calculates return relative to the lowest price in a 30-day period.
2. Collateral Risk: Uses standard deviation to assess volatility (higher risk if standard deviation is large).
3. Liquidity Recovery: A rolling average of volume, aiming to show how liquidity flows might recover over time.
4. Weakening (Rate of Change): Reflects how quickly price is changing compared to previous bars.
5. Monetary Bias (SMA): A simple average of recent prices. If price is below this SMA, it might be seen as undervalued relative to the short term.
6. Risk Phase: Categorizes risk as low, medium, or high based on the standard deviation figure.
7. DCA Signal: Suggests “Accumulate” or “Do Not Accumulate” by checking if the current price is below or above the SMA.
- Why It’s Useful:
- Offers a concise view of multiple assets in one place—helpful for portfolio-level insight.
- DCA (Dollar-Cost Averaging) suggestions can guide longer-term strategies, while volatility (collateral risk) helps gauge how aggressive the price swings might be.
---
### 6. Other Vital Aspects
- Alerts & Notifications:
- The script can trigger alerts for various conditions—crossovers, divergence detections, overbought/oversold transitions, or correlation-based signals.
- Useful for automating watchlists or ensuring you don’t miss a key setup while away from the screen.
- Customization:
- Each module (oscillator settings, divergence detection, correlation meter, advanced metrics table, etc.) can be enabled or disabled based on your preferences.
- You can fine-tune parameters (e.g., periods, smoothing lengths, alert triggers) to align the indicator with different trading styles—scalping, swing, or position trading.
- Combining Features:
- One might watch the main oscillator for momentum extremes, confirm via the HMA slope, check if correlation supports the same bias, and look at the table for risk-phase validation.
- This multi-layer approach can help develop a more structured and informed trading view.
(Space for an example chart: “A fully configured layout showing oscillator, HMA, gradient cloud, correlation meter, and table all in use.”)
7. Money Flow Tracker
Purpose: The Money Flow Tracker adds a volume-based perspective to the indicator suite by incorporating the Money Flow Index (MFI), which assesses buying and selling pressure over a defined period. By smoothing the MFI using an exponential moving average (EMA), the feature highlights the directional flow of capital into and out of the market with greater clarity and reduced noise.
Dynamic Gradient Visualization:
The Money Flow Tracker enhances visual analysis with gradient fills that reflect the MFI’s relationship to the midline (50).
Above 50: A green gradient emerges, intensifying as the MFI moves higher, indicating stronger positive money flow.
Below 50: A red gradient appears, with deeper shades signifying increasing selling pressure.
Transparency dynamically adjusts based on the MFI’s proximity to the midline, making high-confidence zones (closer to 0 or 100) visually distinct.
Directional Sensitivity:
The Tracker emphasizes the importance of overbought (above 70) and oversold (below 30) zones. These thresholds help traders identify when an asset might be overextended, signaling potential reversals or trend continuations.
The inclusion of a midline (50) as a neutral zone helps gauge shifts between accumulation (money flowing in) and distribution (money flowing out).
Bar Integration:
By enabling bar coloring linked to the Money Flow Tracker, traders can visualize its impact directly on price bars.
Green bars reflect positive money flow (above 50), signaling bullish conditions.
Red bars indicate negative money flow (below 50), highlighting bearish sentiment.
Intensity adjustments ensure that recent signals are more visually prominent, while older signals gradually fade for a clean, non-cluttered chart.
Key Advantages:
Volume-Informed Context: Traditional oscillators often focus solely on price; the Money Flow Tracker incorporates volume, adding a crucial dimension for analyzing market behavior.
Adaptive Filtering: The EMA-smoothing feature ensures that sudden, insignificant spikes in volume don’t trigger false signals, providing a clearer and more actionable representation of money flow trends.
Early Warning System: Divergences between price movement and the Money Flow Tracker’s trends can signal potential turning points, helping traders anticipate reversals before they occur.
Practical Use Cases:
Trend Confirmation: Pair the Money Flow Tracker with the oscillator or HMA to confirm bullish or bearish trends. For example, a rising oscillator with positive money flow indicates strong buying interest.
Identifying Entry/Exit Zones: Use overbought/oversold conditions as entry/exit points, particularly when combined with other features like divergence detection.
Market Sentiment Analysis: The Tracker’s ability to dynamically assess buying and selling pressure provides a clear picture of market sentiment, helping traders adjust their strategies to align with broader trends.
By understanding these features—main oscillator readings, the HMA’s smoothing capabilities, gradient-based visual highlights, correlation insights, advanced metrics, and the money flow tracker—you can tailor Uptrick: Oscillator Spectrum to your specific needs, whether you’re focusing on quick trades, longer-term market moves, or broad portfolio health.
Originality of the “Uptrick: Oscillator Spectrum” Indicator
While it includes elements of standard momentum analysis, Uptrick: Oscillator Spectrum sets itself apart by adding an array of features that broaden the typical oscillator’s scope:
1. Slope Coloring & Layered Gradient Effects
- Beyond just plotting a single line, the indicator visually highlights momentum shifts using color changes and gradient fills.
- As the oscillator’s slope becomes steeper or flatter, these gradients intensify or fade, helping users see at a glance when momentum is accelerating, slowing, or reversing.
2. Mean Reversion & Divergence Detection
- The script offers optional logic for marking potential mean reversion points (e.g., overbought/oversold crossovers) and flagging divergences between price and the oscillator line.
- These divergence signals come with adjustable lookback parameters, giving traders control over how recent or extended the pivots should be for detection.
- This functionality can reveal subtle momentum discrepancies that a basic oscillator might overlook.
3. Integrated Multi-Asset Correlation Meter
- In addition to monitoring a single symbol, the indicator can fetch data for multiple tickers. It aggregates each symbol’s slope into a histogram showing whether the broader market (or a group of assets) leans bullish or bearish.
- This cross-market insight moves beyond standard “one-symbol, one-oscillator” usage, adding a bigger-picture perspective in one tool.
4. Advanced Metrics Table
- Users can enable a table that covers ROI calculations, volatility-based risk (“Collateral Risk”), liquidity checks, DCA signals, and more.
- Rather than just seeing an oscillator value, traders can view additional metrics for selected assets in one place, helping them judge overall market conditions or assess multiple instruments simultaneously.
5. Flexible Overlay & Bar Coloring
- Signals can be displayed directly on the price chart (Overlay True) or in a sub-window (Overlay False).
- Bars themselves may change color (e.g., green for bullish or red for bearish) according to different rules—signals, dynamic cloud fill, correlation meter states, etc.
- This adaptability allows traders to keep the chart as simple or as info-rich as they prefer.
6. Custom Smoothing Options & HMA Extensions
- The oscillator can be processed further with a Hull Moving Average (HMA) to reduce noise while still reacting quickly to market changes.
- Slope-based coloring on the HMA provides an additional layer of visual feedback, which is not common in a standard oscillator.
By blending traditional momentum checks with slope-based color feedback, mean reversion triggers, divergence signals, correlation analysis, and an optional metrics table, Uptrick: Oscillator Spectrum offers a more rounded approach than a typical oscillator. It integrates multiple market insights—both visual and analytical—into one script, giving users a broader toolkit for studying potential reversals, gauging momentum strength, and assessing multi-asset trends.
## Conclusion
Uptrick: Oscillator Spectrum brings together multiple layers of analysis—oscillator momentum, divergence detection, correlation insights, HMA smoothing, and more—into one adaptable toolkit. It aims to streamline your charting process by offering meaningful visual cues (such as gradient fills and bar color shifts), advanced tables for broader market data, and flexible alerts to keep you informed of potential setups.
Traders can choose the specific features that suit their style, whether they prefer to focus on raw oscillator signals, multi-ticker correlation, or smooth trend cues from the HMA. By centralizing these different methods in one place, Uptrick: Oscillator Spectrum can help users build more structured approaches to spotting trend shifts and extended conditions, while also remaining compatible with additional analysis techniques.
---
### Disclaimer
This script is provided for informational purposes only and does not constitute financial or investment advice. Past performance is not indicative of future results, and all trading involves risk. You should carefully consider your objectives, risk tolerance, and financial situation before making any trading decisions.
[blackcat] L1 Abnormal Volume Monitor█ OVERVIEW
The script is an indicator designed to monitor abnormal volume patterns in the market. It calculates and plots moving average volumes, identifies triple volume bars, and detects potential large order entries based on specific conditions.
█ FEATURES
• Input Parameters: The script defines parameters M1, M2, and lbk which control the calculation of moving averages and the lookback period for detecting abnormal volume.
• Calculations: The script calculates two moving averages of volume (MAVOL1 and MAVOL2), a smoothed price level (mm), and identifies conditions for triple volume bars and large order entries.
• Plotting: The script plots volume histograms for up and down bars, moving average volumes, and highlights triple volume bars with and without large order entries.
• Conditional Statements: The script uses conditional statements to determine when to plot certain data points and labels based on the calculated conditions.
█ LOGICAL FRAMEWORK
• xfl(cond, lbk): This function checks if a condition (cond) has been true within a specified lookback period (lbk). It returns true if the condition has been met and false otherwise.
• Parameters: cond (condition to check), lbk (lookback period).
• Return Value: outb (boolean indicating if the condition was met within the lookback period).
• abnormal_vol_monitor(close, open, high, low, volume, M1, M2, lbk): This function calculates moving average volumes, identifies triple volume bars, and detects large order entries.
• Parameters: close, open, high, low, volume (price and volume data), M1, M2 (periods for moving averages), lbk (lookback period).
• Return Value: A tuple containing MAVOL1, MAVOL2, xa (large order entry condition), and tripleVolume (triple volume condition).
█ KEY POINTS AND TECHNIQUES
• Moving Averages: The script uses simple moving averages (sma) and exponential moving averages (ema) to smooth volume data.
• Volume Analysis: The script identifies triple volume bars and large order entries based on specific conditions, such as volume doubling and price increases.
• Lookback Period: The xfl function uses a lookback period to ensure the accuracy of the detected conditions.
• Plotting Techniques: The script uses different plot styles and colors to distinguish between up bars, down bars, moving averages, and abnormal volume patterns.
█ EXTENDED KNOWLEDGE AND APPLICATIONS
• Modifications: The script could be modified to include additional conditions for detecting other types of abnormal volume patterns or to adjust the sensitivity of the detection.
• Extensions: Similar techniques could be applied to other financial instruments or timeframes to identify unusual trading activity.
• Related Concepts: The script utilizes concepts such as moving averages, exponential moving averages, and conditional plotting, which are fundamental in Pine Script and technical analysis.
Multiple SMA, EMA, and VWAP CrossoversMultiple SMA, EMA, and VWAP Crossovers with Alerts
Overview : The "Multiple SMA, EMA, and VWAP Crossovers" script is designed for traders who want to monitor various simple moving averages (SMAs), exponential moving averages (EMAs), and the volume-weighted average price (VWAP) to identify potential buy and sell opportunities. This script allows you to visualize key moving averages on your chart and create custom alerts for specific crossover events.
Detail s: This script plots the following moving averages:
Simple Moving Averages (SMA): 5, 10, 20, 50, 100, 200, and 325 periods
Exponential Moving Average (EMA): 9 periods
Volume-Weighted Average Price (VWAP)
It includes options to display these moving averages and set alerts for their crossovers.
Available Crossovers:
20/50 SMA, 20/100 SMA, 20/200 SMA, 20/325 SMA
50/100 SMA, 50/200 SMA, 50/325 SMA
100/200 SMA, 100/325 SMA
200/325 SMA
VWAP/20 SMA, VWAP/50 SMA, VWAP/100 SMA, VWAP/200 SMA, VWAP/325 SMA
Optional Lines to Add to the Chart:
9 EMA, 5 SMA, 10 SMA, 20 SMA, 50 SMA, 100 SMA, 200 SMA, 325 SMA, VWAP
How to Use:
Enable Indicators: Use the input options to select which SMAs, EMA, and VWAP you want to display on your chart.
Set Alerts: Choose the specific crossover events you want to monitor. For example, you can set an alert for the 20/50 SMA crossover or the VWAP/100 SMA crossover.
Monitor the Chart: The script will plot the selected moving averages on your chart. When a selected crossover event occurs, an alert will be triggered, notifying you of the potential trade opportunity.
Usage Tips:
Trending Market: Use the buy and sell alerts in trending markets where the moving averages can help confirm the direction of the trend.
Key Support and Resistance Levels: Combine crossover alerts with key support and resistance levels for more reliable trading signals.
Volume Confirmation: Ensure there is sufficient volume to support the crossover signals, indicating stronger momentum behind the move.
When NOT to Use Buy and Sell Alerts:
Low Volume: Avoid using buy and sell alerts during periods of low trading volume, as the signals may be less reliable.
Market Noise: Be cautious in highly volatile markets where frequent crossovers might generate false signals.
Sideways Market: In a sideways or range-bound market, crossover signals can result in multiple whipsaws, leading to potential losses.
Why Use This Script? This script provides a comprehensive tool for traders to monitor multiple moving averages and VWAP crossovers efficiently. It allows you to customize alerts based on your trading strategy and helps you make informed decisions by visualizing key technical indicators on your chart.
Legal Disclaimer: The information provided by this script is for educational and informational purposes only and should not be considered financial advice. The developer of this script is not responsible for any financial losses incurred from using this script.
Ichimoku Wave Oscillator with Custom MAIchimoku Wave Oscillator with Custom MA - Pine Script Description
This script uses various types of moving averages (MA) to implement the concept of Ichimoku wave theory for wave analysis. The user can select from SMA, EMA, WMA, TEMA, SMMA to visualize the difference between short-term, medium-term, and long-term waves, while identifying potential buy and sell signals at crossover points.
Key Features:
MA Type Selection:
The user can select from SMA (Simple Moving Average), EMA (Exponential Moving Average), WMA (Weighted Moving Average), TEMA (Triple Exponential Moving Average), and SMMA (Smoothed Moving Average) to calculate the waves. This script is unique in that it combines TEMA and SMMA, distinguishing it from other simple moving average-based indicators.
TEMA (Triple Exponential Moving Average): Best suited for capturing short-term trends with quick responsiveness.
SMMA (Smoothed Moving Average): Useful for identifying long-term trends with minimal noise, providing more stable signals.
Wave Calculations:
The script calculates three waves: Wave 9-17, Wave 17-26, and Wave 9-26, each of which analyzes different time horizons.
Wave 9-17 (blue): Primarily used for analyzing short-term trends, ideal for detecting quick changes.
Wave 17-26 (red): Used to analyze medium-term trends, providing a more stable market direction.
Wave 9-26 (green): Represents long-term trends, suitable for understanding broader trend shifts.
Baseline (0 Line):
Each wave is visualized around the 0 line, where waves above the line indicate an uptrend and waves below the line indicate a downtrend. This allows for easy identification of trend reversals.
Crossover Signals:
CrossUp: When Wave 9-17 (short-term wave) crosses Wave 17-26 (medium-term wave) upward, it is considered a buy signal, indicating a potential upward trend shift.
CrossDown: When Wave 9-17 (short-term wave) crosses Wave 17-26 downward, it is considered a sell signal, indicating a potential downward trend shift.
Background Color for Signal:
The script visually highlights the signals with background colors. When a buy signal occurs, the background turns green, and when a sell signal occurs, the background turns red. This makes it easier to spot reversal points.
Calculation Method:
The script calculates the difference between moving averages to display the wave oscillation. Wave 9-17, Wave 17-26, and Wave 9-26 represent the difference between the moving averages for different time periods, allowing for analysis of short-term, medium-term, and long-term trends.
Wave 9-17 = MA(9) - MA(17): Represents the difference between the short-term moving averages.
Wave 17-26 = MA(17) - MA(26): Represents the difference between medium-term moving averages.
Wave 9-26 = MA(9) - MA(26): Provides insight into the long-term trend.
This calculation method effectively visualizes the oscillation of waves and helps identify trend reversals at crossover points.
Uniqueness of the Script:
Unlike other moving average-based indicators, this script combines TEMA (Triple Exponential Moving Average) and SMMA (Smoothed Moving Average) to capture both short-term sensitivity and long-term stability in trends. This duality makes the script more versatile for different market conditions.
TEMA is ideal for short-term traders who need quick signals, while SMMA is useful for long-term investors seeking stability and noise reduction. By combining these two, this script provides a more refined analysis of trend changes across various timeframes.
How to Use:
This script is effective for trend analysis and reversal detection. By visualizing the crossover points between the waves, users can spot potential buy and sell signals to make more informed trading decisions.
Scalping strategies can rely on Wave 9-17 to detect quick trend changes, while those looking for medium-term trends can analyze signals from Wave 17-26.
For a broader market overview, Wave 9-26 helps users understand the long-term market trend.
This script is built on the concept of wave theory to anticipate trend changes, making it suitable for various timeframes and strategies. The user can tailor the characteristics of the waves by selecting different MA types, allowing for flexible application across different trading strategies.
Ichimoku Wave Oscillator with Custom MA - Pine Script 설명
이 스크립트는 다양한 이동 평균(MA) 유형을 활용하여 일목 파동론의 개념을 기반으로 파동 분석을 시도하는 지표입니다. 사용자는 SMA, EMA, WMA, TEMA, SMMA 중 원하는 이동 평균을 선택할 수 있으며, 이를 통해 단기, 중기, 장기 파동 간의 차이를 시각화하고, 교차점에서 상승 및 하락 신호를 포착할 수 있습니다.
주요 기능:
이동 평균(MA) 유형 선택:
사용자는 SMA(단순 이동 평균), EMA(지수 이동 평균), WMA(가중 이동 평균), TEMA(삼중 지수 이동 평균), SMMA(평활 이동 평균) 중 하나를 선택하여 파동을 계산할 수 있습니다. 이 스크립트는 TEMA와 SMMA의 독창적인 조합을 통해 기존의 단순한 이동 평균 지표와 차별화됩니다.
TEMA(삼중 지수 이동 평균): 빠른 반응으로 단기 트렌드를 포착하는 데 적합합니다.
SMMA(평활 이동 평균): 장기적인 추세를 파악하는 데 유용하며, 노이즈를 최소화하여 안정적인 신호를 제공합니다.
파동(Wave) 계산:
이 스크립트는 Wave 9-17, Wave 17-26, Wave 9-26의 세 가지 파동을 계산하여 각각 단기, 중기, 장기 추세를 분석합니다.
Wave 9-17 (파란색): 주로 단기 추세를 분석하는 데 사용되며, 빠른 추세 변화를 포착하는 데 유용합니다.
Wave 17-26 (빨간색): 중기 추세를 분석하는 데 사용되며, 좀 더 안정적인 시장 흐름을 보여줍니다.
Wave 9-26 (녹색): 장기 추세를 나타내며, 큰 흐름의 방향성을 파악하는 데 적합합니다.
기준선(0 라인):
각 파동은 0 라인을 기준으로 변동성을 시각화합니다. 0 위에 있는 파동은 상승세, 0 아래에 있는 파동은 하락세를 나타내며, 이를 통해 추세의 전환을 쉽게 확인할 수 있습니다.
파동 교차 신호:
CrossUp: Wave 9-17(단기 파동)이 Wave 17-26(중기 파동)을 상향 교차할 때, 상승 신호로 간주됩니다. 이는 단기적인 추세 변화가 발생할 수 있음을 의미합니다.
CrossDown: Wave 9-17(단기 파동)이 Wave 17-26(중기 파동)을 하향 교차할 때, 하락 신호로 해석됩니다. 이는 시장이 약세로 돌아설 가능성을 나타냅니다.
배경 색상 표시:
교차 신호가 발생할 때, 상승 신호는 녹색 배경, 하락 신호는 빨간색 배경으로 시각적으로 강조되어 사용자가 신호를 쉽게 인식할 수 있습니다.
계산 방식:
이 스크립트는 이동 평균 간의 차이를 계산하여 각 파동의 변동성을 나타냅니다. Wave 9-17, Wave 17-26, Wave 9-26은 각각 설정된 주기의 이동 평균(MA)의 차이를 통해, 시장의 단기, 중기, 장기 추세 변화를 시각적으로 표현합니다.
Wave 9-17 = MA(9) - MA(17): 단기 추세의 차이를 나타냅니다.
Wave 17-26 = MA(17) - MA(26): 중기 추세의 차이를 나타냅니다.
Wave 9-26 = MA(9) - MA(26): 장기적인 추세 방향을 파악할 수 있습니다.
이러한 계산 방식은 파동의 변동성을 파악하는 데 유용하며, 추세의 교차점을 통해 상승/하락 신호를 잡아냅니다.
스크립트의 독창성:
이 스크립트는 기존의 이동 평균 기반 지표들과 달리, TEMA(삼중 지수 이동 평균)와 SMMA(평활 이동 평균)을 함께 사용하여 짧은 주기와 긴 주기의 트렌드를 동시에 파악할 수 있도록 설계되었습니다. 이를 통해 단기 트렌드의 민감한 변화와 장기 트렌드의 안정성을 모두 반영합니다.
TEMA는 단기 트레이더에게 빠르고 민첩한 신호를 제공하며, SMMA는 장기 투자자에게 보다 안정적이고 긴 호흡의 트렌드를 파악하는 데 유리합니다. 두 지표의 결합으로, 다양한 시장 환경에서 추세의 변화를 더 정교하게 분석할 수 있습니다.
사용 방법:
이 스크립트는 추세 분석과 변곡점 포착에 효과적입니다. 각 파동 간의 교차점을 시각적으로 확인하고, 상승 또는 하락 신호를 포착하여 매매 시점 결정을 도울 수 있습니다.
스캘핑 전략에서는 Wave 9-17을 주로 참고하여 빠르게 추세 변화를 잡아내고, 중기 추세를 참고하고 싶은 경우 Wave 17-26을 사용해 신호를 분석할 수 있습니다.
장기적인 시장 흐름을 파악하고자 할 때는 Wave 9-26을 통해 큰 트렌드를 확인할 수 있습니다.
이 스크립트는 파동 이론의 개념을 기반으로 시장의 추세 변화를 예측하는 데 유용하며, 다양한 시간대와 전략에 맞추어 사용할 수 있습니다. 특히, 사용자가 선택한 MA 유형에 따라 파동의 특성을 변화시킬 수 있어, 여러 매매 전략에 유연하게 대응할 수 있습니다.
Combined IndicatorSummary
This custom Pine Script combines three main indicators into one, each with its own functionalities and visual cues. It provides a comprehensive approach to trend analysis by integrating short-term, medium-term, and long-term indicators. Each part of the indicator can be toggled on or off independently to suit the trader’s needs.
Part 1: EMA 14 and EMA 200
Purpose: This part of the indicator is designed to identify short-term and long-term trends using Exponential Moving Averages (EMA). It helps traders spot potential entry and exit points based on the relationship between short-term and long-term moving averages.
Visuals:
• EMA 14: Plotted in blue (#2962ff)
• EMA 200: Plotted in red (#f23645)
Signals:
• Long Signal: Generated when EMA 14 crosses above EMA 200, indicating a potential upward trend.
• Short Signal: Generated when EMA 14 crosses below EMA 200, indicating a potential downward trend.
Usage: Toggle this part on or off using the checkbox input to focus on short-term vs. long-term trends.
Part 2: EMA 9 and SMA 20
Purpose: This part combines Exponential and Simple Moving Averages to provide a medium-term trend analysis. It helps smooth out price data and identify potential trend reversals and continuation patterns.
Visuals:
• EMA 9: Plotted in green
• SMA 20: Plotted in dark red
Usage: Toggle this part on or off using the checkbox input to focus on medium-term trends and price smoothing.
Part 3: Golden Cross and Death Cross
Purpose: This part identifies long-term bullish and bearish market conditions using the 50-day and 200-day Simple Moving Averages (SMA). It highlights major trend changes that can inform long-term investment decisions.
Visuals:
• 50-day SMA: Plotted in gold (#ffe600)
• 200-day SMA: Plotted in black
Signals:
• Golden Cross: Generated when the 50-day SMA crosses above the 200-day SMA, indicating a potential long-term upward trend.
• Death Cross: Generated when the 50-day SMA crosses below the 200-day SMA, indicating a potential long-term downward trend.
Usage: Toggle this part on or off using the checkbox input to focus on long-term trend changes.
How to Use
1. Enable/Disable Indicators: Use the checkboxes provided in the input settings to enable or disable each part of the indicator according to your analysis needs.
2. Interpret Signals: Look for crossover events to determine potential entry and exit points based on the relationship between the moving averages.
3. Visual Confirmation: Use the color-coded lines and shape markers on the chart to visually confirm signals and trends.
4. Customize Settings: Adjust the lengths of the EMAs and SMAs in the input settings to suit your trading strategy and the specific asset you are analyzing.
Practical Application
• Short-Term Trading: Use the EMA 14 and EMA 200 signals to identify quick trend changes.
• Medium-Term Trading: Use the EMA 9 and SMA 20 to capture medium-term trends and reversals.
• Long-Term Investing: Monitor the Golden Cross and Death Cross signals to make decisions based on long-term trend changes.
Example of Unique Features
• Integrated Toggle System: Allows users to enable or disable specific parts of the indicator to customize their analysis.
• Multi-Tier Trend Analysis: Combines short-term, medium-term, and long-term indicators to provide a comprehensive view of the market.
Multi-Timeframe MA Levels█ OVERVIEW
This Pine Script is an indicator for displaying multiple moving average (MA) levels from several timeframes on your TradingView charts. At the Realtime Bar (the right-most bar on your chart), it draws a line where the various moving averages currently are.
For example, it will show you where the 8 EMA on the 5 minute timeframe is on your 1-minute timeframe chart.
It derives its look and function from "Lepelle's Key Levels" and focuses on visualizing various moving averages to complement this indicator.
█ FEATURES
1 — Multi-Timeframe Analysis:
• The script allows traders to view moving averages from different timeframes on a single chart.
This multi-timeframe approach helps identify significant levels and trends that might not be apparent when looking at a single timeframe.
2 — Customization and Flexibility:
• Extensive input options for customizing the appearance of the lines (width, style, color) and labels (size, position, distance from price).
This ensures that the indicator can be tailored to individual preferences and charting styles.
3 — Multiple Moving Averages:
• Support for various types of moving averages (8 EMA, 21 EMA, 50 SMA, 100 SMA, 200 SMA).
Each moving average can be individually enabled or disabled for specific timeframes,
providing a flexible tool for technical analysis.
█ SETTINGS
Inputs for Styling:
• Controls the appearance of the lines and labels.
• Includes options for line width, line style, text size, distance from the candlesticks, label position,
and whether to hide prices or use shorthand notation.
Moving Averages Settings:
• Inputs to select different moving averages (8 EMA, 21 EMA, 50 SMA, 100 SMA, 200 SMA) and their corresponding colors.
• Boolean inputs to enable or disable these moving averages on various timeframes (2 min, 5 min, hourly, daily).
█ SUMMARY
In essence, this script provides a comprehensive tool for technical analysis by combining multi-timeframe moving averages into a single, customizable, and user-friendly indicator. It enhances traders' ability to make informed decisions by providing clear visual representations of key moving average levels across different timeframes.
═════════════════════════════════════════════════════════════
█ LIMITATIONS
This script is best used with a short timeframe such as 1-minute or lower because of the limitations of Multi-Timeframe scripts. Basically, the alternate timeframes in use should always be higher than the chart timeframe.
═════════════════════════════════════════════════════════════
█ NOTES
This indicator is intended to complement and be used with "Lepelle's Key Levels" indicator.
In that indictor settings, I recommend turning off the 5 Daily timeframe moving average levels in that script, if using this one.
═════════════════════════════════════════════════════════════
Jemmy Trade Whales Multiple Signal Options - Nine in One $$$This script is a combination of several indicators and trading strategies.
Let's break down each part:
1. MACD Indicator (My MACD Indicator – Nabil's Version): This calculates the Moving Average Convergence Divergence (MACD) using Heikin Ashi candles. It uses Exponential Moving Averages (EMA) to compute the fast and slow lengths and then calculates the MACD line, signal line, and histogram based on the difference between these EMAs.
2. Smoothed Moving Average (SMMA): This calculates a smoothed moving average using a user-defined length.
3. Least Squares Moving Average (LSMA): This calculates a least squares moving average using a user-defined length.
4. High Low SAR - Nabil's Version: This section calculates various levels based on SAR (Stop and Reverse) indicator. It also plots lines based on certain conditions and includes SAR lines with specific properties.
5. Volume-Weighted Hull Moving Average (VHMA) - Nabil's Version: This calculates a volume-weighted Hull moving average.
6. SAR (Stop and Reverse): This calculates the SAR indicator with user-defined parameters.
7. Mean Reversion Strategy: This part calculates upper and lower bands based on a multiplier of Standard Deviation from a mean. It also generates buy and sell signals based on crossing these bands.
8. SSL Hybrid - Nabil's Version: This calculates various indicators like SSL (Stochastic Scaled Levels), ATR (Average True Range) bands, and Keltner Channels. It also plots buy and sell signals based on certain conditions.
9. Buy Signal Options: This section defines several conditions for generating buy signals based on different combinations of indicators and plots corresponding buy signals.
Each section seems to be relatively independent and focused on calculating specific indicators or trading strategies. The script combines these components to provide a comprehensive trading setup with various buy signal options based on user preferences.
BUY SIGNALS EXPLAINATION:
1. MAIN - Price: This signal triggers when the current candle's close price crosses above the lookback average line (lookbackavg). It indicates a bullish momentum when the price moves above the average line.
2. MAIN - Price - SMMA - LSMA / Crossing: This signal combines multiple conditions:
• The current candle's close price crosses above the lookback average line.
• The smoothed moving average (SMMA) crosses above the lookback average line.
• The least squares moving average (LSMA) crosses above the lookback average line. This signal confirms a bullish trend when all three moving averages cross above the average line simultaneously.
3. MAIN - Price - (SMMA > LSMA) / No Crossing: This signal triggers when the following conditions are met:
• The current candle's close price crosses above the lookback average line.
• The SMMA is above the LSMA. This signal confirms a bullish trend when the SMMA remains consistently above the LSMA without crossing.
4. MAIN - Price - SMMA - LSMA - SAR - SSL / Crossing: This signal combines multiple conditions:
• The current candle's close price, SMMA, and LSMA cross above the lookback average line.
• The SAR (Stop and Reverse) indicator is above the SSL (Stochastic Scaled Levels). This signal indicates a strong bullish momentum when all conditions align.
5. MAIN - Price - (SMMA > LSMA) - SAR - SSL / No Crossing: This signal triggers when the following conditions are met:
• The current candle's close price crosses above the lookback average line.
• The SMMA is consistently above the LSMA.
• The SAR is above the SSL. This signal confirms a bullish trend without any crossing of moving averages.
6. MAIN - Price - SMMA - LSMA - SAR - SSL / Crossing - Coloring: Similar to signal 4, this signal additionally checks for specific colors of SAR and SSL lines to confirm a bullish momentum.
7. MAIN - Price - (SMMA > LSMA) - SAR - SSL / No Crossing - Coloring: Similar to signal 5, this signal also checks for specific colors of SAR and SSL lines to confirm a bullish trend without any crossing of moving averages.
8. MAIN Support line - 2 Candles: This signal triggers when the price pulls back from below the support line within the last two candles. It indicates a potential reversal from a support level.
9. MAIN Support line - lookBack Candles: This signal is similar to signal 8 but considers a specified lookback range for checking the pullback from below the support line.
These buy signals aim to identify various bullish scenarios based on combinations of price action, moving averages, SAR, and SSL indicators. Each signal offers different levels of confirmation for potential buying opportunities in the market.
USE IT WITH YOUR RISK MANAGEMENT STRATEGIES.
Future Updates "Coming Soon"
Targets - Under processing.
Stop loss - Under Processing.
Trailing - Under Processing.
Historical Data Table - Under processing.
Strength Table - Under Processing.
Whales Catcher - Under Processing.
Order Book Analyzer - Under Processing.
NABIL ELMAHDY $$
Fear and Greed Index (Crypto & Stock)The Fear and Greed Index utilizes various metrics to gauge the overall sentiment of the stock and crypto market.
It's divided into two categories:
Extreme Fear (0-25) -> Red background
Extreme Greed (75-100) -> Green background
When the index is in the Extreme Fear zone, the indicator background changes to red, while in the Extreme Greed zone, it changes to green.
The blue line represents the Fear and Greed Index for the overall stock or crypto market. The index automatically switches between the crypto and stock depending on the active chart, providing insights into both markets.
The histogram represents Price Momentum for the current active symbol on the chart.
How is the Crypto Fear and Greed Index calculated?
The index is calculated using three factors including momentum of stable coin (safe haven), momentum of major coins, and the balance of unique addresses holding the major coins. The index tracks how much these individual indicators deviate from their averages compared to how much they normally diverge. The index gives each factor equal weighting in calculating a score from 0 to 100, with 100 representing maximum greediness and 0 signaling maximum fear.
The main factors used in the calculation are:
1. Momentum of Stable Coins
The index calculates the momentum of three major stable coins, including USDT, USDC and DAI. The index looks at the stable coins’ levels compared to where they’ve been over the past two months. When the stable coin is below its moving average of the prior 60 trading days, that’s a sign of positive momentum. But if the index is above this average, it shows investors are getting skittish. The Fear & Greed Index uses the growing momentum of stable coin as a signal for Fear and a slowing momentum for Greed.
During a market sell-off, investors may anticipate a decline in the value of their cryptocurrency investments and may transition into stable coins as a safe haven. This is because stable coins are designed to maintain a stable value, often pegged to a fiat currency like the US Dollar.
By analyzing the overall trend of stable coins' movement, the index can help determine whether the market sentiment leans towards greed or fear. If stable coins are experiencing a significant increase in momentum, it may suggest that investors are moving away from riskier assets (like cryptocurrencies) and into safer assets (like stable coins), indicating a fear-driven market sentiment. Conversely, if stable coins are experiencing a decrease in momentum, it may suggest that investors are more confident in the market and are less concerned about potential declines in the value of their cryptocurrency investments, indicating a greed-driven market sentiment.
2. Momentum of major coins
The index calculates the momentum of 16 major cryptocurrencies, including Bitcoin, Ethereum, and BNB. This index assesses the overall trend of these cryptocurrencies' movement, which can provide insights into market sentiment. The index checks how many coins are doing well versus those that are struggling. This shows the number of coins on the market at 2-months highs compared to those at 2-months lows. When there are many more highs than lows, that’s a bullish sign and signals Greed.
By analyzing the momentum of these 16 major cryptocurrencies, the index can help determine whether there's more bullish or bearish sentiment prevailing in the market over the given period. If the overall momentum is positive, it may suggest that investors are more optimistic about the market, leading to increased buying activity and higher prices. Conversely, if the overall momentum is negative, it may suggest that investors are more pessimistic about the market, leading to increased selling activity and lower prices.
3. Balance of unique addresses holding major coins
The index is tracking the number of unique addresses holding Bitcoin and Ethereum. This measure looks at the amount of investors holding Bitcoin or Ethereum and compares the amount to its 2-month moving average.
The logic behind this assessment is that when there are more unique addresses holding Bitcoin and Ethereum, it suggests that more individuals are interested in holding these cryptocurrencies, which may indicate bullish sentiment. Conversely, when there are fewer unique addresses holding Bitcoin and Ethereum, it suggests that fewer individuals are interested in holding these cryptocurrencies, which may indicate bearish sentiment.
How is the Stock Fear and Greed Index calculated?
The Stock Fear & Greed Index is a compilation of two indicators that measure some aspect of stock market behavior. They are market momentum and stock price strength. The Stock Fear & Greed Index calculates how much these individual indicators deviate from their averages and compares this divergence to their typical variations. Both indicators receive equal weighting in calculating a score ranging from 0 to 100.
A score of 100 indicates maximum greediness, suggesting that market momentum and stock prices are significantly above their historical averages.
Conversely, a score of 0 signals maximum fear, indicating that market momentum and stock prices are significantly below their historical averages.
1. Market Momentum
The Stock Fear & Greed index looks at stock market levels compared to where they’ve been over the past few months. When the S&P 500, DJI and NASDAQ is above its moving average of the prior 180 trading days, that’s a sign of positive momentum. But if the index is below this average, it shows investors are getting skittish. The Fear & Greed Index uses slowing momentum as a signal for Fear and a growing momentum for Greed.
2. Momentum of major stocks
The index calculates momentum by analyzing the price levels of major stocks relative to their moving averages over the past six months. When a stock's price is above its moving average of the prior 180 trading days, it indicates positive momentum. Conversely, if the stock's price is below this moving average, it suggests that investors are becoming skittish, or there is a loss of momentum.
How to use the Fear and Greed Index?
The Fear & Greed Index ranges from 0 to 100, a reading of 0-25 indicates extreme fear, while a reading of 75-100 indicates extreme greed. The index can help investors and traders identify market trends and potential turning points. By understanding the sentiment of the market, investors can avoid making decisions based on emotions and biases.
When the Fear and Greed Index is at an extreme level of fear (0-25), it can indicate that investors are overly worried and selling their assets out of fear. This could present a buying opportunity for investors who believe in the long-term potential of the market.
Conversely, when the Fear and Greed Index is at an extreme level of greed (75-100), it can indicate that investors are overly optimistic and buying assets out of greed. This could be a sign that the market is due for a correction.
How is the Price Momentum (Histogram) calculated?
Momentum focuses on the rate of change in stock prices over a specific period. It assesses how quickly prices are moving in a particular direction, whether upward or downward. A momentum value above 50 indicates that prices are fueled by strength to move upward. This suggests that buying pressure is dominant in the market, driving prices higher. Conversely, a momentum value below 50 indicates that prices are fueled by strength moving downward. This suggests that selling pressure is dominant, pushing prices lower.
Our momentum indicator can help investors identify trends and potential turning points in the market. Rising momentum values may indicate an upward trend, while declining momentum values may suggest a weakening trend or a potential reversal.
Extreme momentum values may indicate overbought or oversold conditions in the market. Overbought conditions occur when momentum values are excessively high, suggesting that prices may be due for a correction. Conversely, oversold conditions occur when momentum values are excessively low, indicating potential buying opportunities.
How to use our Fear & Greed Indicator
Using price momentum and the Fear and Greed Index together can provide valuable confirmation signals for investors in the stock or crypto market. Here's how you can use them together:
Identify Trends: Start by identifying the overall trend in the market using price momentum. Rising momentum values often indicate an uptrend, while declining momentum values suggest a downtrend.
Monitor Fear and Greed Index: Simultaneously, monitor the Fear and Greed Index to gauge market sentiment. In an uptrend, high readings on the Fear and Greed Index (75-100) may indicate excessive greed among investors, potentially signaling that the uptrend is becoming overextended and due for a correction. Conversely, in a downtrend, low readings on the Fear and Greed Index (0-25) may indicate extreme fear, potentially signaling capitulation and a possible reversal.
Look for Confirmation Signals: Look for confirmation signals between price momentum and the Fear and Greed Index. For example:
In an uptrend, if momentum is declining while the Fear and Greed Index is at a high level, it may suggest weakening buying pressure and potential exhaustion in the uptrend.
In a downtrend, if momentum is reducing while the Fear and Greed Index is at a low level, it may indicate that selling pressure is subsiding, potentially signaling a reversal in the downtrend.
Goertzel Adaptive JMA T3Hello Fellas,
The Goertzel Adaptive JMA T3 is a powerful indicator that combines my own created Goertzel adaptive length with Jurik and T3 Moving Averages. The primary intention of the indicator is to demonstrate the new adaptive length algorithm by applying it on bleeding-edge MAs.
It is useable like any moving average, and the new Goertzel adaptive length algorithm can be used to make own indicators Goertzel adaptive.
Used Adaptive Length Algorithms
Normalized Goertzel Power: This uses the normalized power of the Goertzel algorithm to compute an adaptive length without the special operations, like detrending, Ehlers uses for his DFT adaptive length.
Ehlers Mod: This uses the Goertzel algorithm instead of the DFT, originally used by Ehlers, to compute a modified version of his original approach, which sticks as close as possible to the original approach.
Scoring System
The scoring system determines if bars are red or green and collects them.
Then, it goes through all collected red and green bars and checks how big they are and if they are above or below the selected MA. It is positive when green bars are under MA or when red bars are above MA.
Then, it accumulates the size for all positive green bars and for all positive red bars. The same happens for negative green and red bars.
Finally, it calculates the score by ((positiveGreenBars + positiveRedBars) / (negativeGreenBars + negativeRedBars)) * 100 with the scale 0–100.
Signals
Is the price above MA? -> bullish market
Is the price below MA? -> bearish market
Usage
Adjust the settings to reach the highest score, and enjoy an outstanding adaptive MA.
It should be useable on all timeframes. It is recommended to use the indicator on the timeframe where you can get the highest score.
Now, follows a bunch of knowledge for people who don't know about the concepts used here.
T3
The T3 moving average, short for "Tim Tillson's Triple Exponential Moving Average," is a technical indicator used in financial markets and technical analysis to smooth out price data over a specific period. It was developed by Tim Tillson, a software project manager at Hewlett-Packard, with expertise in Mathematics and Computer Science.
The T3 moving average is an enhancement of the traditional Exponential Moving Average (EMA) and aims to overcome some of its limitations. The primary goal of the T3 moving average is to provide a smoother representation of price trends while minimizing lag compared to other moving averages like Simple Moving Average (SMA), Weighted Moving Average (WMA), or EMA.
To compute the T3 moving average, it involves a triple smoothing process using exponential moving averages. Here's how it works:
Calculate the first exponential moving average (EMA1) of the price data over a specific period 'n.'
Calculate the second exponential moving average (EMA2) of EMA1 using the same period 'n.'
Calculate the third exponential moving average (EMA3) of EMA2 using the same period 'n.'
The formula for the T3 moving average is as follows:
T3 = 3 * (EMA1) - 3 * (EMA2) + (EMA3)
By applying this triple smoothing process, the T3 moving average is intended to offer reduced noise and improved responsiveness to price trends. It achieves this by incorporating multiple time frames of the exponential moving averages, resulting in a more accurate representation of the underlying price action.
JMA
The Jurik Moving Average (JMA) is a technical indicator used in trading to predict price direction. Developed by Mark Jurik, it’s a type of weighted moving average that gives more weight to recent market data rather than past historical data.
JMA is known for its superior noise elimination. It’s a causal, nonlinear, and adaptive filter, meaning it responds to changes in price action without introducing unnecessary lag. This makes JMA a world-class moving average that tracks and smooths price charts or any market-related time series with surprising agility.
In comparison to other moving averages, such as the Exponential Moving Average (EMA), JMA is known to track fast price movement more accurately. This allows traders to apply their strategies to a more accurate picture of price action.
Goertzel Algorithm
The Goertzel algorithm is a technique in digital signal processing (DSP) for efficient evaluation of individual terms of the Discrete Fourier Transform (DFT). It's particularly useful when you need to compute a small number of selected frequency components. Unlike direct DFT calculations, the Goertzel algorithm applies a single real-valued coefficient at each iteration, using real-valued arithmetic for real-valued input sequences. This makes it more numerically efficient when computing a small number of selected frequency components¹.
Discrete Fourier Transform
The Discrete Fourier Transform (DFT) is a mathematical technique used in signal processing to convert a finite sequence of equally-spaced samples of a function into a same-length sequence of equally-spaced samples of the discrete-time Fourier transform (DTFT), which is a complex-valued function of frequency . The DFT provides a frequency domain representation of the original input sequence .
Usage of DFT/Goertzel In Adaptive Length Algorithms
Adaptive length algorithms are automated trading systems that can dynamically adjust their parameters in response to real-time market data. This adaptability enables them to optimize their trading strategies as market conditions fluctuate. Both the Goertzel algorithm and DFT can be used in these algorithms to analyze market data and detect cycles or patterns, which can then be used to adjust the parameters of the trading strategy.
The Goertzel algorithm is more efficient than the DFT when you need to compute a small number of selected frequency components. However, for covering a full spectrum, the Goertzel algorithm has a higher order of complexity than fast Fourier transform (FFT) algorithms.
I hope this can help you somehow.
Thanks for reading, and keep it up.
Best regards,
simwai
---
Credits to:
@ClassicScott
@yatrader2
@cheatcountry
@loxx
YinYang VolumeOverview:
YinYang Volume is an Advanced Volume Indicator. Regular Volume can be deceiving. It can be hard to tell how much of the Volume bar is Buy vs Sell volume, especially since the bar is green or red simply based on if it closes at a greater price than it opened. With YinYang Volume you'll be able to see how much Buy AND Sell Volume there is on each bar. Being able to see both is very useful, but the cherry on top is the Buy and Sell Moving Average Lines. These lines (White is Buy and Orange is Sell) can show who is currently winning the fight, Bulls or Bears. When the lines cross it's a shift in momentum and when combined with other technical analysis you can better understand the direction the market is moving and make an informed and educated trading decision. YinYang Volume also has Information tables, these tables display the Buy vs Sell volume on different Timeframes. This way even if you're trading on a Low Timeframe (like 15 minutes) you can see how the Buy vs Sell volume is fairing on other Timeframes.
Tutorial:
Unlike most volume indicators, including standard volume, we can see both Buy AND Sell volume for each bar. You may be wondering, well what’s the importance of this? The answer is EVERYTHING! Volume is one of the most important indicators when it comes to trading. Nothing moves without volume. However, with standard volume, the bar is either red or green simply based on if it closes greater than it opens. Now, that is pretty silly if you ask us. Let’s get into depth as to why seeing both Buy and Sell volume is important, and examples for how you can make trades with it:
In this example above, we have 2 green bars and they both have high levels of volume. This bar on the right however, has more volume than the one on the left. The issue here is, the bar on the right has MORE Sell volume than it even does have Buy volume; meanwhile the bar on the left has way more buy volume than the bar on the right with little sell volume. Without separating them and by simply looking at the price bar and regular volume bar, we would never be able to deduce this. It is crucial to understand and see how much of each volume there is as it plays a huge role in the price movements.
The white line represents the Buy Volume Moving Average and the orange line represents the Sell Volume Moving Average. These moving averages are very useful as when they cross they represent strong Buy and Sell Signals.
We’ve enabled signals which plot circles onto the MA’s to display when they’ve crossed. The white circle represents a Buy Signal and the Orange circle represents a Sell Signal. These signals are very strong, but there is a catch that comes with it. The bar right after the signal has the highest chance of a reversal so it isn’t always advised to make the trade until confirmed that the reversal didn’t happen on the following bar. If you have enough data based on other technical analysis to know the first signal is true, then use it as a way to solidify the fact that it is a good entry/exit location.
You can change the length of which the MA’s are smoothed out over. For instance, in the previous examples and by default the length is 14. However, if we are to change it to 50 for instance, it makes them a longer lasting MA that has much fewer crosses. This can be useful based on your trading style and if you prefer to stay in trades for quite awhile. As you can see, all signals with the 50 length are quite accurate and would have produced profitable trades, likely more so than at 14, but since it moves slower there's fewer signals to trade on.
Our Information Tables are there to show you the amount of Buy vs Sell %’s on 6 different Time Frames at the same time. It can be very useful to know how people are feeling on different Time Frames without you having to change your own. This way you can stay on say the 15 minute Time Frame locked in your trade and can see if the momentum of your long trade is cooling down based on higher Time Frames Buy vs Sell volume %’s.
For example, let's say you got an alert from YinYang Volume for Buy Signal on the 1 Day. You then entered a trade which you deemed a good location on the 15 minutes (after doing your own technical analysis on the 15 minute too). The Buy vs Sell Volume %’s on the 1 Day was 55% Buy and 45% Sell when you entered the trade. You are still waiting for exit confirmation on the 15 minute but you notice the Buy vs Sell Volume % on the 1 Day goes down to 52% Buy and 48% Sell. You can see the momentum changing. Even though you haven’t received confirmation for exit on the 15 minute, it may still be a good time to get out as momentum is clearly changing on the 1 Day.
We will conclude this Tutorial here. We hope you’ll get some good use out of our Volume Indicator and its ability to display unique Volume Data. If you have any Questions, Comments, Suggestions or Concerns, please don’t hesitate to contact us.
Settings:
1. Show Signals:
Toggling this setting shows when the Buy and Sell Volume MA’s cross each other. It produces a white circle when the Buy Volume Crosses over the Sell Volume (BULLISH) and an orange circle when the Sell Volume Crosses over the Buy Volume (BEARISH).
2. Length:
How far back should we average the Buy and Sell Volume Moving Averages? 14 is default has been tested and proven to work well, however you can change it if there is a different value that suits your trading style better.
3. Type:
How is the Moving Averages calculated? VWMA (Volume Weighted Moving Average) is the default as it has been tested and worked best; afterall, we are calculating volume and therefore should use a volume weighted MA calculation. However, you can change it as your options are:
VWMA, EMA and SMA
4. Information Tables:
4.1. Show Information Tables:
Our Information tables display 6 different resolutions so you can see how much Buy vs Sell volume there is as a % in multiple different Time Frames without having to change your Time Frame.
4.2. Strength:
The Buy / Sell Volume %’s displayed within your Information Tables are based on Moving Averages. The length this moving average uses is based on the Strength you select. The strengths aren’t as simple as just a length amount but are a calculation involving multiple different lengths and averages. However, the stronger the strength, generally the farther the lookback length is as an average. Your options for strength are:
Unbreakable
Very Strong
Strong
Average
Weak
Very Weak
Glass
We recommend ‘Average’ Strength, however if you find you want to see the %’s change more or less frequently you can adjust to your trading style
4.3. Res1 / Res2/ Res3 / Res4 / Res5 / Res6:
These represent the different resolutions (Time Frames) being used in your information tables and can be modified to display whatever resolution works best for your trading style. By default they are:
Res1: Current Timeframe
Res2: 15 Minute
Res3: 1 Hour
Res4: 4 Hour
Res5: 1 Day
Res6: 1 Week
Backup Res (not changeable): 5 Minute (this is only used if your Current Timeframe in Res1 is a duplicate of one of the other resolutions)
HAPPY TRADING!
High/Low of week: Stats & Day of Week tendencies// Purpose:
-To show High of Week (HoW) day and Low of week (LoW) day frequencies/percentages for an asset.
-To further analyze Day of Week (DoW) tendencies based on averaged data from all various custom weeks. Giving a more reliable measure of DoW tendencies ('Meta Averages').
-To backtest day-of-week tendencies: across all asset history or across custom user input periods (i.e. consolidation vs trending periods).
-Education: to see how how data from a 'hard-defined-week' may be misleading when seeking statistical evidence of DoW tendencies.
// Notes & Tips:
-Only designed for use on DAILY timeframe.
-Verification table is to make sure HoW / LoW DAY (referencing previous finished week) is printing correctly and therefore the stats table is populating correctly.
-Generally, leaving Timezone input set to "America/New_York" is best, regardless of your asset or your chart timezone. But if misaligned by 1 day =>> tweak this timezone input to correct
-If you want to use manual backtesting period (e.g. for testing consolidation periods vs trending periods): toggle these settings on, then click the indicator display line three dots >> 'Reset Points' to quickly set start & end dates.
// On custom week start days:
-For assets like BTC which trade 7 days a week, this is quite simple. Pick custom start day, use verification table to check all is well. See the start week day & time in said verification table.
-For traditional assets like S&P which trade only 5 days a week and suffer from occasional Holidays, this is a bit more complicated. If the custom start day input is a bank holiday, its custom 'week' will be discounted from the data set. E.g.1: if you choose 'use custom start day' and set it to Monday, then bank holiday Monday weeks will be discounted from the data set. E.g.2: If you choose 'use custom start day' and set it to Thursday, then the Holiday Thursday custom week (e.g Thanksgiving Thursday >> following Weds) would be discounted from the data set.
// On 'Meta Averages':
-The idea is to try and mitigate out the 'continuation bias' that comes from having a fixed week start/end time: i.e. sometimes a market is trending through the week start/end time, so the start/end day stats are over-weighted if one is trying to tease out typical weekly profile tendencies or typical DoW tendencies. You'll notice this if you compare the stats with various custom start days ('bookend' start/end days are always more heavily weighted). I wanted to try to mitigate out this 'bias' by cycling through all the possible new week start/end days and taking an average of the results. i.e. on BTC/USD the 'meta average' for Tuesday would be the average of the Tuesday HoW frequencies from the set of all 7 possible custom weeks(Mon-Sun, Tues-Mon, Weds-Tues, etc etc).
// User Inputs:
~Week Start:
-use custom week start day (default toggled OFF); Choose custom week start day
-show Meta Averages (default toggled ON)
~Verification Table:
-show table, show new week lines, number of new week lines to show
-table formatting options (position, color, size)
-timezone (only for tweaking if printed DoW is misaligned by 1 day)
~Statistics Table:
-show table, table formatting options (position, color, size)
~Manual Backtesting:
-Use start date (default toggled OFF), choose start date, choose vline color
-Use end date (defautl toggled OFF), choose end date, choose vline color
// Demo charts:
NQ1! (Nasdaq), Full History, Traditional week (Mon>>Friday) stats. And Meta Averages. Annotations in purple:
NQ1! (Nasdaq), Full History, Custom week (custom start day = Wednesday). And Meta Averages. Annotations in purple:
Machine Learning : Cosine Similarity & Euclidean DistanceIntroduction:
This script implements a comprehensive trading strategy that adheres to the established rules and guidelines of housing trading. It leverages advanced machine learning techniques and incorporates customised moving averages, including the Conceptive Price Moving Average (CPMA), to provide accurate signals for informed trading decisions in the housing market. Additionally, signal processing techniques such as Lorentzian, Euclidean distance, Cosine similarity, Know sure thing, Rational Quadratic, and sigmoid transformation are utilised to enhance the signal quality and improve trading accuracy.
Features:
Market Analysis: The script utilizes advanced machine learning methods such as Lorentzian, Euclidean distance, and Cosine similarity to analyse market conditions. These techniques measure the similarity and distance between data points, enabling more precise signal identification and enhancing trading decisions.
Cosine similarity:
Cosine similarity is a measure used to determine the similarity between two vectors, typically in a high-dimensional space. It calculates the cosine of the angle between the vectors, indicating the degree of similarity or dissimilarity.
In the context of trading or signal processing, cosine similarity can be employed to compare the similarity between different data points or signals. The vectors in this case represent the numerical representations of the data points or signals.
Cosine similarity ranges from -1 to 1, with 1 indicating perfect similarity, 0 indicating no similarity, and -1 indicating perfect dissimilarity. A higher cosine similarity value suggests a closer match between the vectors, implying that the signals or data points share similar characteristics.
Lorentzian Classification:
Lorentzian classification is a machine learning algorithm used for classification tasks. It is based on the Lorentzian distance metric, which measures the similarity or dissimilarity between two data points. The Lorentzian distance takes into account the shape of the data distribution and can handle outliers better than other distance metrics.
Euclidean Distance:
Euclidean distance is a distance metric widely used in mathematics and machine learning. It calculates the straight-line distance between two points in Euclidean space. In two-dimensional space, the Euclidean distance between two points (x1, y1) and (x2, y2) is calculated using the formula sqrt((x2 - x1)^2 + (y2 - y1)^2).
Dynamic Time Windows: The script incorporates a dynamic time window function that allows users to define specific time ranges for trading. It checks if the current time falls within the specified window to execute the relevant trading signals.
Custom Moving Averages: The script includes the CPMA, a powerful moving average calculation. Unlike traditional moving averages, the CPMA provides improved support and resistance levels by considering multiple price types and employing a combination of Exponential Moving Averages (EMAs) and Simple Moving Averages (SMAs). Its adaptive nature ensures responsiveness to changes in price trends.
Signal Processing Techniques: The script applies signal processing techniques such as Know sure thing, Rational Quadratic, and sigmoid transformation to enhance the quality of the generated signals. These techniques improve the accuracy and reliability of the trading signals, aiding in making well-informed trading decisions.
Trade Statistics and Metrics: The script provides comprehensive trade statistics and metrics, including total wins, losses, win rate, win-loss ratio, and early signal flips. These metrics offer valuable insights into the performance and effectiveness of the trading strategy.
Usage:
Configuring Time Windows: Users can customize the time windows by specifying the start and finish time ranges according to their trading preferences and local market conditions.
Signal Interpretation: The script generates long and short signals based on the analysis, custom moving averages, and signal processing techniques. Users should pay attention to these signals and take appropriate action, such as entering or exiting trades, depending on their trading strategies.
Trade Statistics: The script continuously tracks and updates trade statistics, providing users with a clear overview of their trading performance. These statistics help users assess the effectiveness of the strategy and make informed decisions.
Conclusion:
With its adherence to housing trading rules, advanced machine learning methods, customized moving averages like the CPMA, and signal processing techniques such as Lorentzian, Euclidean distance, Cosine similarity, Know sure thing, Rational Quadratic, and sigmoid transformation, this script offers users a powerful tool for housing market analysis and trading. By leveraging the provided signals, time windows, and trade statistics, users can enhance their trading strategies and improve their overall trading performance.
Disclaimer:
Please note that while this script incorporates established tradingview housing rules, advanced machine learning techniques, customized moving averages, and signal processing techniques, it should be used for informational purposes only. Users are advised to conduct their own analysis and exercise caution when making trading decisions. The script's performance may vary based on market conditions, user settings, and the accuracy of the machine learning methods and signal processing techniques. The trading platform and developers are not responsible for any financial losses incurred while using this script.
By publishing this script on the platform, traders can benefit from its professional presentation, clear instructions, and the utilisation of advanced machine learning techniques, customised moving averages, and signal processing techniques for enhanced trading signals and accuracy.
I extend my gratitude to TradingView, LUX ALGO, and JDEHORTY for their invaluable contributions to the trading community. Their innovative scripts, meticulous coding patterns, and insightful ideas have profoundly enriched traders' strategies, including my own.
Adaptive Candlestick Pattern Recognition System█ INTRODUCTION
Nearly three years in the making, intermittently worked on in the few spare hours of weekends and time off, this is a passion project I undertook to flesh out my skills as a computer programmer. This script currently recognizes 85 different candlestick patterns ranging from one to five candles in length. It also performs statistical analysis on those patterns to determine prior performance and changes the coloration of those patterns based on that performance. In searching TradingView's script library for scripts similar to this one, I had found a handful. However, when I reviewed the ones which were open source, I did not see many that truly captured the power of PineScrypt or leveraged the way it works to create efficient and reliable code; one of the main driving factors for releasing this 5,000+ line behemoth open sourced.
Please take the time to review this description and source code to utilize this script to its fullest potential.
█ CONCEPTS
This script covers the following topics: Candlestick Theory, Trend Direction, Higher Timeframes, Price Analysis, Statistic Analysis, and Code Design.
Candlestick Theory - This script focuses solely on the concept of Candlestick Theory: arrangements of candlesticks may form certain patterns that can potentially influence the future price action of assets which experience those patterns. A full list of patterns (grouped by pattern length) will be in its own section of this description. This script contains two modes of operation for identifying candlestick patterns, 'CLASSIC' and 'BREAKOUT'.
CLASSIC: In this mode, candlestick patterns will be identified whenever they appear. The user has a wide variety of inputs to manipulate that can change how certain patterns are identified and even enable alerts to notify themselves when these patterns appear. Each pattern selected to appear will have their Profit or Loss (P/L) calculated starting from the first candle open succeeding the pattern to a candle close specified some number of candles ahead. These P/L calculations are then collected for each pattern, and split among partitions of prior price action of the asset the script is currently applied to (more on that in Higher Timeframes ).
BREAKOUT: In this mode, P/L calculations are held off until a breakout direction has been confirmed. The user may specify the number of candles ahead of a pattern's appearance (from one to five) that a pattern has to confirm a breakout in either an upward or downward direction. A breakout is constituted when there is a candle following the appearance of the pattern that closes above/at the highest high of the pattern, or below/at its lowest low. Only then will percent return calculations be performed for the pattern that's been identified, and these percent returns are broken up not only by the partition they had appeared in but also by the breakout direction itself. Patterns which do not breakout in either direction will be ignored, along with having their labels deleted.
In both of these modes, patterns may be overridden. Overrides occur when a smaller pattern has been detected and ends up becoming one (or more) of the candles of a larger pattern. A key example of this would be the Bearish Engulfing and the Three Outside Down patterns. A Three Outside Down necessitates a Bearish Engulfing as the first two candles in it, while the third candle closes lower. When a pattern is overridden, the return for that pattern will no longer be tracked. Overrides will not occur if the tail end of a larger pattern occurs at the beginning of a smaller pattern (Ex: a Bullish Engulfing occurs on the third candle of a Three Outside Down and the candle immediately following that pattern, the Three Outside Down pattern will not be overridden).
Important Functionality Note: These patterns are only searched for at the most recently closed candle, not on the currently closing candle, which creates an offset of one for this script's execution. (SEE LIMITATIONS)
Trend Direction - Many of the patterns require a trend direction prior to their appearance. Noting TradingView's own publication of candlestick patterns, I utilize a similar method for determining trend direction. Moving Averages are used to determine which trend is currently taking place for candlestick patterns to be sought out. The user has access to two Moving Averages which they may individually modify the following for each: Moving Average type (list of 9), their length, width, source values, and all variables associated with two special Moving Averages (Least Squares and Arnaud Legoux).
There are 3 settings for these Moving Averages, the first two switch between the two Moving Averages, and the third uses both. When using individual Moving Averages, the user may select a 'price point' to compare against the Moving Average (default is close). This price point is compared to the Moving Average at the candles prior to the appearance of candle patterns. Meaning: The close compared to the Moving Average two candles behind determines the trend direction used for Candlestick Analysis of one candle patterns; three candles behind for two candle patterns and so on. If the selected price point is above the Moving Average, then the current trend is an 'uptrend', 'downtrend' otherwise.
The third setting using both Moving Averages will compare the lengths of each, and trend direction is determined by the shorter Moving Average compared to the longer one. If the shorter Moving Average is above the longer, then the current trend is an 'uptrend', 'downtrend' otherwise. If the lengths of the Moving Averages are the same, or both Moving Averages are Symmetrical, then MA1 will be used by default. (SEE LIMITATIONS)
Higher Timeframes - This script employs the use of Higher Timeframes with a few request.security calls. The purpose of these calls is strictly for the partitioning of an asset's chart, splitting the returns of patterns into three separate groups. The four inputs in control of this partitioning split the chart based on: A given resolution to grab values from, the length of time in that resolution, and 'Upper' and 'Lower Limits' which split the trading range provided by that length of time in that resolution that forms three separate groups. The default values for these four inputs will partition the current chart by the yearly high-low range where: the 'Upper' partition is the top 20% of that trading range, the 'Middle' partition is 80% to 33% of the trading range, and the 'Lower' partition covers the trading range within 33% of the yearly low.
Patterns which are identified by this script will have their returns grouped together based on which partition they had appeared in. For example, a Bullish Engulfing which occurs within a third of the yearly low will have its return placed separately from a Bullish Engulfing that occurred within 20% of the yearly high. The idea is that certain patterns may perform better or worse depending on when they had occurred during an asset's trading range.
Price Analysis - Price Analysis is a major part of this script's functionality as it can fundamentally change how patterns are shown to the user. The settings related to Price Analysis include setting the number of candles ahead of a pattern's appearance to determine the return of that pattern. In 'BREAKOUT' mode, an additional setting allows the user to specify where the P/L calculation will begin for a pattern that had appeared and confirmed. (SEE LIMITATIONS)
The calculation for percent returns of patterns is illustrated with the following pseudo-code (CLASSIC mode, this is a simplified version of the actual code):
type patternObj
int ID
int partition
type returnsArray
float returns
// No pattern found = na returned
patternObj TEST_VAL = f_FindPattern()
priorTestVal = TEST_VAL
if not na( priorTestVal )
pnlMatrixRow = priorTestVal.ID
pnlMatrixCol = priorTestVal.partition
matrixReturn = matrix.get(PERCENT_RETURNS, pnlMatrixRow, pnlMatrixCol)
percentReturn = ( (close - open ) / open ) * 100%
array.push(matrixReturn.returns, percentReturn)
Statistic Analysis - This script uses Pine's built-in array functions to conduct the Statistic Analysis for patterns. When a pattern is found and its P/L calculation is complete, its return is added to a 'Return Array' User-Defined-Type that contains numerous fields which retain information on a pattern's prior performance. The actual UDT is as follows:
type returnArray
float returns = na
int size = 0
float avg = 0
float median = 0
float stdDev = 0
int polarities = na
All values within this UDT will be updated when a return is added to it (some based on user input). The array.avg , array.median and array.stdev will be ran and saved into their respective fields after a return is placed in the 'returns' array. The 'polarities' integer array is what will be changed based on user input. The user specifies two different percentages that declare 'Positive' and 'Negative' returns for patterns. When a pattern returns above, below, or in between these two values, different indices of this array will be incremented to reflect the kind of return that pattern had just experienced.
These values (plus the full name, partition the pattern occurred in, and a 95% confidence interval of expected returns) will be displayed to the user on the tooltip of the labels that identify patterns. Simply scroll over the pattern label to view each of these values.
Code Design - Overall this script is as much of an art piece as it is functional. Its design features numerous depictions of ASCII Art that illustrate what is being attempted by the functions that identify patterns, and an incalculable amount of time was spent rewriting portions of code to improve its efficiency. Admittedly, this final version is nearly 1,000 lines shorter than a previous version (one which took nearly 30 seconds after compilation to run, and didn't do nearly half of what this version does). The use of UDTs, especially the 'patternObj' one crafted and redesigned from the Hikkake Hunter 2.0 I published last month, played a significant role in making this script run efficiently. There is a slight rigidity in some of this code mainly around pattern IDs which are responsible for displaying the abbreviation for patterns (as well as the full names under the tooltips, and the matrix row position for holding returns), as each is hard-coded to correspond to that pattern.
However, one thing I would like to mention is the extensive use of global variables for pattern detection. Many scripts I had looked over for ideas on how to identify candlestick patterns had the same idea; break the pattern into a set of logical 'true/false' statements derived from historically referencing candle OHLC values. Some scripts which identified upwards of 20 to 30 patterns would reference Pine's built-in OHLC values for each pattern individually, potentially requesting information from TradingView's servers numerous times that could easily be saved into a variable for re-use and only requested once per candle (what this script does).
█ FEATURES
This script features a massive amount of switches, options, floating point values, detection settings, and methods for identifying/tailoring pattern appearances. All modifiable inputs for patterns are grouped together based on the number of candles they contain. Other inputs (like those for statistics settings and coloration) are grouped separately and presented in a way I believe makes the most sense.
Not mentioned above is the coloration settings. One of the aims of this script was to make patterns visually signify their behavior to the user when they are identified. Each pattern has its own collection of returns which are analyzed and compared to the inputs of the user. The user may choose the colors for bullish, neutral, and bearish patterns. They may also choose the minimum number of patterns needed to occur before assigning a color to that pattern based on its behavior; a color for patterns that have not met this minimum number of occurrences yet, and a color for patterns that are still processing in BREAKOUT mode.
There are also an additional three settings which alter the color scheme for patterns: Statistic Point-of-Reference, Adaptive coloring, and Hard Limiting. The Statistic Point-of-Reference decides which value (average or median) will be compared against the 'Negative' and 'Positive Return Tolerance'(s) to guide the coloration of the patterns (or for Adaptive Coloring, the generation of a color gradient).
Adaptive Coloring will have this script produce a gradient that patterns will be colored along. The more bullish or bearish a pattern is, the further along the gradient those patterns will be colored starting from the 'Neutral' color (hard lined at the value of 0%: values above this will be colored bullish, bearish otherwise). When Adaptive Coloring is enabled, this script will request the highest and lowest values (these being the Statistic Point-of-Reference) from the matrix containing all returns and rewrite global variables tied to the negative and positive return tolerances. This means that all patterns identified will be compared with each other to determine bullish/bearishness in Adaptive Coloring.
Hard Limiting will prevent these global variables from being rewritten, so patterns whose Statistic Point-of-Reference exceed the return tolerances will be fully colored the bullish or bearish colors instead of a generated gradient color. (SEE LIMITATIONS)
Apart from the Candle Detection Modes (CLASSIC and BREAKOUT), there's an additional two inputs which modify how this script behaves grouped under a "MASTER DETECTION SETTINGS" tab. These two "Pattern Detection Settings" are 'SWITCHBOARD' and 'TARGET MODE'.
SWITCHBOARD: Every single pattern has a switch that is associated with its detection. When a switch is enabled, the code which searches for that pattern will be run. With the Pattern Detection Setting set to this, all patterns that have their switches enabled will be sought out and shown.
TARGET MODE: There is an additional setting which operates on top of 'SWITCHBOARD' that singles out an individual pattern the user specifies through a drop down list. The names of every pattern recognized by this script will be present along with an identifier that shows the number of candles in that pattern (Ex: " (# candles)"). All patterns enabled in the switchboard will still have their returns measured, but only the pattern selected from the "Target Pattern" list will be shown. (SEE LIMITATIONS)
The vast majority of other features are held in the one, two, and three candle pattern sections.
For one-candle patterns, there are:
3 — Settings related to defining 'Tall' candles:
The number of candles to sample for previous candle-size averages.
The type of comparison done for 'Tall' Candles: Settings are 'RANGE' and 'BODY'.
The 'Tolerance' for tall candles, specifying what percent of the 'average' size candles must exceed to be considered 'Tall'.
When 'Tall Candle Setting' is set to RANGE, the high-low ranges are what the current candle range will be compared against to determine if a candle is 'Tall'. Otherwise the candle bodies (absolute value of the close - open) will be compared instead. (SEE LIMITATIONS)
Hammer Tolerance - How large a 'discarded wick' may be before it disqualifies a candle from being a 'Hammer'.
Discarded wicks are compared to the size of the Hammer's candle body and are dependent upon the body's center position. Hammer bodies closer to the high of the candle will have the upper wick used as its 'discarded wick', otherwise the lower wick is used.
9 — Doji Settings, some pulled from an old Doji Hunter I made a while back:
Doji Tolerance - How large the body of a candle may be compared to the range to be considered a 'Doji'.
Ignore N/S Dojis - Turns off Trend Direction for non-special Dojis.
GS/DF Doji Settings - 2 Inputs that enable and specify how large wicks that typically disqualify Dojis from being 'Gravestone' or 'Dragonfly' Dojis may be.
4 Settings related to 'Long Wick Doji' candles detailed below.
A Tolerance for 'Rickshaw Man' Dojis specifying how close the center of the body must be to the range to be valid.
The 4 settings the user may modify for 'Long Legged' Dojis are: A Sample Base for determining the previous average of wicks, a Sample Length specifying how far back to look for these averages, a Behavior Setting to define how 'Long Legged' Dojis are recognized, and a tolerance to specify how large in comparison to the prior wicks a Doji's wicks must be to be considered 'Long Legged'.
The 'Sample Base' list has two settings:
RANGE: The wicks of prior candles are compared to their candle ranges and the 'wick averages' will be what the average percent of ranges were in the sample.
WICKS: The size of the wicks themselves are averaged and returned for comparing against the current wicks of a Doji.
The 'Behavior' list has three settings:
ONE: Only one wick length needs to exceed the average by the tolerance for a Doji to be considered 'Long Legged'.
BOTH: Both wick lengths need to exceed the average of the tolerance of their respective wicks (upper wicks are compared to upper wicks, lower wicks compared to lower) to be considered 'Long Legged'.
AVG: Both wicks and the averages of the previous wicks are added together, divided by two, and compared. If the 'average' of the current wicks exceeds this combined average of prior wicks by the tolerance, then this would constitute a valid 'Long Legged' Doji. (For Dojis in general - SEE LIMITATIONS)
The final input is one related to candle patterns which require a Marubozu candle in them. The two settings for this input are 'INCLUSIVE' and 'EXCLUSIVE'. If INCLUSIVE is selected, any opening/closing variant of Marubozu candles will be allowed in the patterns that require them.
For two-candle patterns, there are:
2 — Settings which define 'Engulfing' parameters:
Engulfing Setting - Two options, RANGE or BODY which sets up how one candle may 'engulf' the previous.
Inclusive Engulfing - Boolean which enables if 'engulfing' candles can be equal to the values needed to 'engulf' the prior candle.
For the 'Engulfing Setting':
RANGE: If the second candle's high-low range completely covers the high-low range of the prior candle, this is recognized as 'engulfing'.
BODY: If the second candle's open-close completely covers the open-close of the previous candle, this is recognized as 'engulfing'. (SEE LIMITATIONS)
4 — Booleans specifying different settings for a few patterns:
One which allows for 'opens within body' patterns to let the second candle's open/close values match the prior candles' open/close.
One which forces 'Kicking' patterns to have a gap if the Marubozu setting is set to 'INCLUSIVE'.
And Two which dictate if the individual candles in 'Stomach' patterns need to be 'Tall'.
8 — Floating point values which affect 11 different patterns:
One which determines the distance the close of the first candle in a 'Hammer Inverted' pattern must be to the low to be considered valid.
One which affects how close the opens/closes need to be for all 'Lines' patterns (Bull/Bear Meeting/Separating Lines).
One that allows some leeway with the 'Matching Low' pattern (gives a small range the second candle close may be within instead of needing to match the previous close).
Three tolerances for On Neck/In Neck patterns (2 and 1 respectively).
A tolerance for the Thrusting pattern which give a range the close the second candle may be between the midpoint and close of the first to be considered 'valid'.
A tolerance for the two Tweezers patterns that specifies how close the highs and lows of the patterns need to be to each other to be 'valid'.
The first On Neck tolerance specifies how large the lower wick of the first candle may be (as a % of that candle's range) before the pattern is invalidated. The second tolerance specifies how far up the lower wick to the close the second candle's close may be for this pattern. The third tolerance for the In Neck pattern determines how far into the body of the first candle the second may close to be 'valid'.
For the remaining patterns (3, 4, and 5 candles), there are:
3 — Settings for the Deliberation pattern:
A boolean which forces the open of the third candle to gap above the close of the second.
A tolerance which changes the proximity of the third candle's open to the second candle's close in this pattern.
A tolerance that sets the maximum size the third candle may be compared to the average of the first two candles.
One boolean value for the Two Crows patterns (standard and Upside Gapping) that forces the first two candles in the patterns to completely gap if disabled (candle 1's close < candle 2's low).
10 — Floating point values for the remaining patterns:
One tolerance for defining how much the size of each candle in the Identical Black Crows pattern may deviate from the average of themselves to be considered valid.
One tolerance for setting how close the opens/closes of certain three candle patterns may be to each other's opens/closes.*
Three floating point values that affect the Three Stars in the South pattern.
One tolerance for the Side-by-Side patterns - looks at the second and third candle closes.
One tolerance for the Stick Sandwich pattern - looks at the first and third candle closes.
A floating value that sizes the Concealing Baby Swallow pattern's 3rd candle wick.
Two values for the Ladder Bottom pattern which define a range that the third candle's wick size may be.
* This affects the Three Black Crows (non-identical) and Three White Soldiers patterns, each require the opens and closes of every candle to be near each other.
The first tolerance of the Three Stars in the South pattern affects the first candle body's center position, and defines where it must be above to be considered valid. The second tolerance specifies how close the second candle must be to this same position, as well as the deviation the ratio the candle body to its range may be in comparison to the first candle. The third restricts how large the second candle range may be in comparison to the first (prevents this pattern from being recognized if the second candle is similar to the first but larger).
The last two floating point values define upper and lower limits to the wick size of a Ladder Bottom's fourth candle to be considered valid.
█ HOW TO USE
While there are many moving parts to this script, I attempted to set the default values with what I believed may help identify the most patterns within reasonable definitions. When this script is applied to a chart, the Candle Detection Mode (along with the BREAKOUT settings) and all candle switches must be confirmed before patterns are displayed. All switches are on by default, so this gives the user an opportunity to pick which patterns to identify first before playing around in the settings.
All of the settings/inputs described above are meant for experimentation. I encourage the user to tweak these values at will to find which set ups work best for whichever charts they decide to apply these patterns to.
Refer to the patterns themselves during experimentation. The statistic information provided on the tooltips of the patterns are meant to help guide input decisions. The breadth of candlestick theory is deep, and this was an attempt at capturing what I could in its sea of information.
█ LIMITATIONS
DISCLAIMER: While it may seem a bit paradoxical that this script aims to use past performance to potentially measure future results, past performance is not indicative of future results . Markets are highly adaptive and often unpredictable. This script is meant as an informational tool to show how patterns may behave. There is no guarantee that confidence intervals (or any other metric measured with this script) are accurate to the performance of patterns; caution must be exercised with all patterns identified regardless of how much information regarding prior performance is available.
Candlestick Theory - In the name, Candlestick Theory is a theory , and all theories come with their own limits. Some patterns identified by this script may be completely useless/unprofitable/unpredictable regardless of whatever combination of settings are used to identify them. However, if I truly believed this theory had no merit, this script would not exist. It is important to understand that this is a tool meant to be utilized with an array of others to procure positive (or negative, looking at you, short sellers ) results when navigating the complex world of finance.
To address the functionality note however, this script has an offset of 1 by default. Patterns will not be identified on the currently closing candle, only on the candle which has most recently closed. Attempting to have this script do both (offset by one or identify on close) lead to more trouble than it was worth. I personally just want users to be aware that patterns will not be identified immediately when they appear.
Trend Direction - Moving Averages - There is a small quirk with how MA settings will be adjusted if the user inputs two moving averages of the same length when the "MA Setting" is set to 'BOTH'. If Moving Averages have the same length, this script will default to only using MA 1 regardless of if the types of Moving Averages are different . I will experiment in the future to alleviate/reduce this restriction.
Price Analysis - BREAKOUT mode - With how identifying patterns with a look-ahead confirmation works, the percent returns for patterns that break out in either direction will be calculated on the same candle regardless of if P/L Offset is set to 'FROM CONFIRMATION' or 'FROM APPEARANCE'. This same issue is present in the Hikkake Hunter script mentioned earlier. This does not mean the P/L calculations are incorrect , the offset for the calculation is set by the number of candles required to confirm the pattern if 'FROM APPEARANCE' is selected. It just means that these two different P/L calculations will complete at the same time independent of the setting that's been selected.
Adaptive Coloring/Hard Limiting - Hard Limiting is only used with Adaptive Coloring and has no effect outside of it. If Hard Limiting is used, it is recommended to increase the 'Positive' and 'Negative' return tolerance values as a pattern's bullish/bearishness may be disproportionately represented with the gradient generated under a hard limit.
TARGET MODE - This mode will break rules regarding patterns that are overridden on purpose. If a pattern selected in TARGET mode would have otherwise been absorbed by a larger pattern, it will have that pattern's percent return calculated; potentially leading to duplicate returns being included in the matrix of all returns recognized by this script.
'Tall' Candle Setting - This is a wide-reaching setting, as approximately 30 different patterns or so rely on defining 'Tall' candles. Changing how 'Tall' candles are defined whether by the tolerance value those candles need to exceed or by the values of the candle used for the baseline comparison (RANGE/BODY) can wildly affect how this script functions under certain conditions. Refer to the tooltip of these settings for more information on which specific patterns are affected by this.
Doji Settings - There are roughly 10 or so two to three candle patterns which have Dojis as a part of them. If all Dojis are disabled, it will prevent some of these larger patterns from being recognized. This is a dependency issue that I may address in the future.
'Engulfing' Setting - Functionally, the two 'Engulfing' settings are quite different. Because of this, the 'RANGE' setting may cause certain patterns that would otherwise be valid under textbook and online references/definitions to not be recognized as such (like the Upside Gap Two Crows or Three Outside down).
█ PATTERN LIST
This script recognizes 85 patterns upon initial release. I am open to adding additional patterns to it in the future and any comments/suggestions are appreciated. It recognizes:
15 — 1 Candle Patterns
4 Hammer type patterns: Regular Hammer, Takuri Line, Shooting Star, and Hanging Man
9 Doji Candles: Regular Dojis, Northern/Southern Dojis, Gravestone/Dragonfly Dojis, Gapping Up/Down Dojis, and Long-Legged/Rickshaw Man Dojis
White/Black Long Days
32 — 2 Candle Patterns
4 Engulfing type patterns: Bullish/Bearish Engulfing and Last Engulfing Top/Bottom
Dark Cloud Cover
Bullish/Bearish Doji Star patterns
Hammer Inverted
Bullish/Bearish Haramis + Cross variants
Homing Pigeon
Bullish/Bearish Kicking
4 Lines type patterns: Bullish/Bearish Meeting/Separating Lines
Matching Low
On/In Neck patterns
Piercing pattern
Shooting Star (2 Lines)
Above/Below Stomach patterns
Thrusting
Tweezers Top/Bottom patterns
Two Black Gapping
Rising/Falling Window patterns
29 — 3 Candle Patterns
Bullish/Bearish Abandoned Baby patterns
Advance Block
Collapsing Doji Star
Deliberation
Upside/Downside Gap Three Methods patterns
Three Inside/Outside Up/Down patterns (4 total)
Bullish/Bearish Side-by-Side patterns
Morning/Evening Star patterns + Doji variants
Stick Sandwich
Downside/Upside Tasuki Gap patterns
Three Black Crows + Identical variation
Three White Soldiers
Three Stars in the South
Bullish/Bearish Tri-Star patterns
Two Crows + Upside Gap variant
Unique Three River Bottom
3 — 4 Candle Patterns
Concealing Baby Swallow
Bullish/Bearish Three Line Strike patterns
6 — 5 Candle Patterns
Bullish/Bearish Breakaway patterns
Ladder Bottom
Mat Hold
Rising/Falling Three Methods patterns
█ WORKS CITED
Because of the amount of time needed to complete this script, I am unable to provide exact dates for when some of these references were used. I will also not provide every single reference, as citing a reference for each individual pattern and the place it was reviewed would lead to a bibliography larger than this script and its description combined. There were five major resources I used when building this script, one book, two websites (for various different reasons including patterns, moving averages, and various other articles of information), various scripts from TradingView's public library (including TradingView's own source code for *all* candle patterns ), and PineScrypt's reference manual.
Bulkowski, Thomas N. Encyclopedia of Candlestick Patterns . Hoboken, New Jersey: John Wiley & Sons Inc., 2008. E-book (google books).
Various. Numerous webpages. CandleScanner . 2023. online. Accessed 2020 - 2023.
Various. Numerous webpages. Investopedia . 2023. online. Accessed 2020 - 2023.
█ AKNOWLEDGEMENTS
I want to take the time here to thank all of my friends and family, both online and in real life, for the support they've given me over the last few years in this endeavor. My pets who tried their hardest to keep me from completing it. And work for the grit to continue pushing through until this script's completion.
This belongs to me just as much as it does anyone else. Whether you are an institutional trader, gold bug hedging against the dollar, retail ape who got in on a squeeze, or just parents trying to grow their retirement/save for the kids. This belongs to everyone.
Private Beta for new features to be tested can be found here .
Vires In Numeris
Quad MAFor a dive into the fine details, see the source code/documentation.
Quad MA is a program designed to allow a wide range of flexibility in overlaying multiple moving averages onto a chart.
This program handles the ability to:
- Overlay Up to 4 moving averages on the chart.
- Change the length of each moving average.
- Adjust optional values for special moving averages
(least squares and Arnaud Legoux)
- Change the color for each moving average.
- Change the type of each moving average individually.
- Change the visibility of each moving average.
- Change the source of the moving averages.
- Set alerts for a cross between any two moving averages.
