Gaps Trend [ChartPrime]The Gaps Trend - ChartPrime indicator is designed to detect Fair Value Gaps (FVGs) in the market and apply a trailing stop mechanism based on those gaps. It identifies both bullish and bearish gaps and provides traders with a way to manage trades dynamically as gaps appear. The indicator visually highlights gaps and uses the detected momentum to assess trend direction, helping traders identify price imbalances caused by strong buy or sell pressure.
⯁ KEY FEATURES & HOW TO USE
⯌ Fair Value Gap (FVG) Detection :
The indicator automatically detects both bullish and bearish FVGs, identifying gaps between candle highs and lows. Bullish gaps are shown in green, and bearish gaps in purple. These gaps indicate price imbalances driven by strong momentum, such as when there is significant buying or selling pressure.
Use : Traders can use FVG detection to identify periods of high price momentum, offering insight into potential continuation or exhaustion of trends.
⯌ Trailing Stop Feature Based on FVGs :
A core feature of this indicator is the trailing stop mechanism, which adjusts dynamically based on the identified FVGs. When a bullish gap is detected, the trailing stop is placed below the price to capture upward momentum, while bearish gaps result in a trailing stop placed above the price. This feature helps traders stay in trends while protecting profits as the price moves.
Use : The trailing stop follows the momentum of the price, ensuring that traders can stay in profitable trades during strong trends and exit when the momentum shifts.
bullish set up
bearish set up
⯌ Trend Direction Indication :
The indicator colors the chart according to the current trend direction based on the position of the price relative to the trailing stop. Green indicates an uptrend (bullish gap), while purple shows a downtrend (bearish gap). This provides traders with a quick visual assessment of trend direction based on the presence of gaps.
Use : Traders can monitor the chart's color to stay aligned with the market’s trend, staying long during green phases and short during purple ones.
⯌ Gap Size Filtering :
Each detected gap is assigned a numerical ranking based on its size, with larger gaps having higher rankings. The gap size filter allows traders to only display gaps that meet a minimum size threshold, focusing on the most impactful gaps in terms of price movement.
Use : Traders can use the filter to focus on gaps of a certain size, filtering out smaller, less significant gaps. The numerical ranking helps identify the largest and most influential gaps for decision-making.
⯌ FVG Level Visualization :
The indicator can display dashed lines marking the levels of previously filled FVGs. These levels represent areas where price once experienced a gap and later filled it. Monitoring these levels can provide traders with key reference points for potential reactions in price.
Use : Traders can use these gap levels to track where price has filled gaps and potentially use these levels as zones for entry, exit, or assessing market behavior.
⯁ USER INPUTS
Filter Gaps : Adjust the size threshold to filter gaps by their size ranking.
Show Gap Levels : Toggle the display of dashed lines at filled FVG levels.
Enable Trailing Stop : Activate or deactivate the trailing stop feature based on FVGs.
Trailing Stop Length : Set the number of bars used to calculate the trailing stop.
Bullish/Bearish Colors : Customize the colors representing bullish and bearish gaps.
⯁ CONCLUSION
The Gaps Trend indicator combines Fair Value Gap detection with a dynamic trailing stop feature to help traders manage trades during periods of high price momentum. By detecting gaps caused by strong buy or sell pressure and applying adaptive stops, the indicator provides a powerful tool for riding trends and managing risk. The additional ability to filter gaps by size and visualize previously filled gaps enhances its utility for both trend-following and risk management strategies.
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Double Ribbon [ChartPrime]The Double Ribbon - ChartPrime indicator is a powerful tool that combines two sets of Simple Moving Averages (SMAs) into a visually intuitive ribbon, which helps traders assess market trends and momentum. This indicator features two distinct ribbons: one with a fixed length but changing offset (displayed in gray) and another with varying lengths (displayed in colors). The relationship between these ribbons forms the basis of a trend score, which is visualized as an oscillator. This comprehensive approach provides traders with a clear view of market direction and strength.
◆ KEY FEATURES
Dual Ribbon Visualization : Displays two sets of 11 SMAs—one in a neutral gray color with a fixed length but varying offset, and another in vibrant colors with lengths that increase incrementally.
Trend Score Calculation : The trend score is derived from comparing each SMA in the colored ribbon with its corresponding SMA in the gray ribbon. If a colored SMA is above its gray counterpart, a positive score is added; if below, a negative score is assigned.
// Loop to calculate SMAs and update the score based on their relationships
for i = 0 to length
// Calculate SMA with increasing lengths
sma = ta.sma(src, len + 1 + i)
// Update score based on comparison of primary SMA with current SMA
if sma1 < sma
score += 1
else
score -= 1
// Store calculated SMAs in the arrays
sma_array.push(sma)
sma_array1.push(sma1 )
Dynamic Trend Analysis : The score oscillator provides a dynamic analysis of the trend, allowing traders to quickly gauge market conditions and potential reversals.
Customizable Ribbon Display : Users can toggle the display of the ribbon for a cleaner chart view, focusing solely on the trend score if desired.
◆ USAGE
Trend Confirmation : Use the position and color of the ribbon to confirm the current market trend. When the colored ribbon consistently stays above the gray ribbon, it indicates a strong uptrend, and vice versa for a downtrend.
Momentum Assessment : The score oscillator provides insight into the strength of the current trend. Higher scores suggest stronger trends, while lower scores may indicate weakening momentum or a potential reversal.
Strategic Entry/Exit Points : Consider using crossovers between the ribbons and changes in the score oscillator to identify potential entry or exit points in trades.
⯁ USER INPUTS
Length : Sets the base length for the primary SMAs in the ribbons.
Source : Determines the price data used for calculating the SMAs (e.g., close, open).
Ribbon Display Toggle : Allows users to show or hide the ribbon on the chart, focusing on either the ribbon, the trend score, or both.
⯁ CONCLUSION
The Double Ribbon indicator offers traders a comprehensive tool for analyzing market trends and momentum. By combining two ribbons with varying SMA lengths and offsets, it provides a clear visual representation of market conditions. The trend score oscillator enhances this analysis by quantifying trend strength, making it easier for traders to identify potential trading opportunities and manage risk effectively.
Radius Trend [ChartPrime]RADIUS TREND
⯁ OVERVIEW
The Radius Trend [ ChartPrime ] indicator is an innovative technical analysis tool designed to visualize market trends using a dynamic, radius-based approach. By incorporating adaptive bands that adjust based on price action and volatility, this indicator provides traders with a unique perspective on trend direction, strength, and potential reversal points.
The Radius Trend concept involves creating a dynamic trend line that adjusts its angle and position based on market movements, similar to a radius sweeping across a chart. This approach allows for a more fluid and adaptive trend analysis compared to traditional linear trend lines.
◆ KEY FEATURES
Dynamic Trend Band: Calculates and plots a main trend band that adapts to market conditions.
Radius-Based Adjustment: Uses a step-based radius approach to adjust the trend band angle.
// Apply step angle to trend lines
if bar_index % n == 0 and trend
multi1 := 0
multi2 += step
band += distance1 * multi2
if bar_index % n == 0 and not trend
multi1 += step
multi2 := 0
band -= distance1 * multi1
Volatility-Adjusted Calculations: Incorporates price range volatility for more accurate band placement.
Trend Direction Visualization: Provides clear color-coding to distinguish between uptrends and downtrends.
Flexible Parameters: Allows users to adjust the radius step and initial distance for customized analysis.
◆ USAGE
Trend Identification: Use the color and direction of the main band to determine the current market trend.
Trend Strength Analysis: Observe the angle and consistency of the band for insights into trend strength.
Reversal Detection: Watch for price crossing the main band or crossing a dashed band as a potential trend reversal signal.
Volatility Assessment: The distance between price and bands can provide insights into market volatility.
⯁ USER INPUTS
Radius Step: Controls the rate of angle adjustment for the trend band (default: 0.15, step: 0.001).
Start Points Distance: Sets the initial distance multiplier for band calculations (default: 2, step: 0.1).
The Radius Trend indicator offers traders a unique and dynamic approach to trend analysis. By combining radius-based trend adjustments with volatility-sensitive calculations, it provides a fluid representation of market trends. This indicator is particularly useful for traders looking to identify trend persistence, potential reversal points, and adaptive support/resistance levels across various market conditions and timeframes.
Polynomial Regression Keltner Channel [ChartPrime]Polynomial Regression Keltner Channel
⯁ OVERVIEW
The Polynomial Regression Keltner Channel [ ChartPrime ] indicator is an advanced technical analysis tool that combines polynomial regression with dynamic Keltner Channels. This indicator provides traders with a sophisticated method for trend analysis, volatility assessment, and identifying potential overbought and oversold conditions.
◆ KEY FEATURES
Polynomial Regression: Uses polynomial regression for trend analysis and channel basis calculation.
Dynamic Keltner Channels: Implements Keltner Channels with adaptive volatility-based bands.
Overbought/Oversold Detection: Provides visual cues for potential overbought and oversold market conditions.
Trend Identification: Offers clear trend direction signals and change indicators.
Multiple Band Levels: Displays four levels of upper and lower bands for detailed market structure analysis.
Customizable Visualization: Allows toggling of additional indicator lines and signals for enhanced chart analysis.
◆ FUNCTIONALITY DETAILS
⬥ Polynomial Regression Calculation:
Implements a custom polynomial regression function for trend analysis.
Serves as the basis for the Keltner Channel, providing a smoothed centerline.
//@function Calculates polynomial regression
//@param src (series float) Source price series
//@param length (int) Lookback period
//@returns (float) Polynomial regression value for the current bar
polynomial_regression(src, length) =>
sumX = 0.0
sumY = 0.0
sumXY = 0.0
sumX2 = 0.0
sumX3 = 0.0
sumX4 = 0.0
sumX2Y = 0.0
n = float(length)
for i = 0 to n - 1
x = float(i)
y = src
sumX += x
sumY += y
sumXY += x * y
sumX2 += x * x
sumX3 += x * x * x
sumX4 += x * x * x * x
sumX2Y += x * x * y
slope = (n * sumXY - sumX * sumY) / (n * sumX2 - sumX * sumX)
intercept = (sumY - slope * sumX) / n
n - 1 * slope + intercept
⬥ Dynamic Keltner Channel Bands:
Calculates ATR-based volatility for dynamic band width adjustment.
Uses a base multiplier and adaptive volatility factor for flexible band calculation.
Generates four levels of upper and lower bands for detailed market structure analysis.
atr = ta.atr(length)
atr_sma = ta.sma(atr, 10)
// Calculate Keltner Channel Bands
dynamicMultiplier = (1 + (atr / atr_sma)) * baseATRMultiplier
volatility_basis = (1 + (atr / atr_sma)) * dynamicMultiplier * atr
⬥ Overbought/Oversold Indicator line and Trend Line:
Calculates an OB/OS value based on the price position relative to the innermost bands.
Provides visual representation through color gradients and optional signal markers.
Determines trend direction based on the polynomial regression line movement.
Generates signals for trend changes, overbought/oversold conditions, and band crossovers.
◆ USAGE
Trend Analysis: Use the color and direction of the basis line to identify overall trend direction.
Volatility Assessment: The width and expansion/contraction of the bands indicate market volatility.
Support/Resistance Levels: Multiple band levels can serve as potential support and resistance areas.
Overbought/Oversold Trading: Utilize OB/OS signals for potential reversal or pullback trades.
Breakout Detection: Monitor price crossovers of the outermost bands for potential breakout trades.
⯁ USER INPUTS
Length: Sets the lookback period for calculations (default: 100).
Source: Defines the price data used for calculations (default: HLC3).
Base ATR Multiplier: Adjusts the base width of the Keltner Channels (default: 0.1).
Indicator Lines: Toggle to show additional indicator lines and signals (default: false).
⯁ TECHNICAL NOTES
Implements a custom polynomial regression function for efficient trend calculation.
Uses dynamic ATR-based volatility adjustment for adaptive channel width.
Employs color gradients and opacity levels for intuitive visual representation of market conditions.
Utilizes Pine Script's plotchar function for efficient rendering of signals and heatmaps.
The Polynomial Regression Keltner Channel indicator offers traders a sophisticated tool for trend analysis, volatility assessment, and trade signal generation. By combining polynomial regression with dynamic Keltner Channels, it provides a comprehensive view of market structure and potential trading opportunities. The indicator's adaptability to different market conditions and its customizable nature make it suitable for various trading styles and timeframes.
LOWESS (Locally Weighted Scatterplot Smoothing) [ChartPrime]LOWESS (Locally Weighted Scatterplot Smoothing)
⯁ OVERVIEW
The LOWESS (Locally Weighted Scatterplot Smoothing) [ ChartPrime ] indicator is an advanced technical analysis tool that combines LOWESS smoothing with a Modified Adaptive Gaussian Moving Average. This indicator provides traders with a sophisticated method for trend analysis, pivot point identification, and breakout detection.
◆ KEY FEATURES
LOWESS Smoothing: Implements Locally Weighted Scatterplot Smoothing for trend analysis.
Modified Adaptive Gaussian Moving Average: Incorporates a volatility-adapted Gaussian MA for enhanced trend detection.
Pivot Point Identification: Detects and visualizes significant pivot highs and lows.
Breakout Detection: Tracks and optionally displays the count of consecutive breakouts.
Gaussian Scatterplot: Offers a unique visualization of price movements using randomly colored points.
Customizable Parameters: Allows users to adjust calculation length, pivot detection, and visualization options.
◆ FUNCTIONALITY DETAILS
⬥ LOWESS Calculation:
Utilizes a weighted local regression to smooth price data.
Adapts to local trends, reducing noise while preserving important price movements.
⬥ Modified Adaptive Gaussian Moving Average:
Combines Gaussian weighting with volatility adaptation using ATR and standard deviation.
Smooths the Gaussian MA using LOWESS for enhanced trend visualization.
⬥ Pivot Point Detection and Visualization:
Identifies pivot highs and lows using customizable left and right bar counts.
Draws lines and labels to mark broke pivot points on the chart.
⬥ Breakout Tracking:
Monitors price crossovers of pivot lines to detect breakouts.
Optionally displays and updates the count of consecutive breakouts.
◆ USAGE
Trend Analysis: Use the color and direction of the smoothed Gaussian MA line to identify overall trend direction.
Breakout Trading: Monitor breakouts from pivot levels and their persistence using the breakout count feature.
Volatility Assessment: The spread of the Gaussian scatterplot can provide insights into market volatility.
⯁ USER INPUTS
Length: Sets the lookback period for LOWESS and Gaussian MA calculations (default: 30).
Pivot Length: Determines the number of bars to the left for pivot calculation (default: 5).
Count Breaks: Toggle to show the count of consecutive breakouts (default: false).
Gaussian Scatterplot: Toggle to display the Gaussian MA as a scatterplot (default: true).
⯁ TECHNICAL NOTES
Implements a custom LOWESS function for efficient local regression smoothing.
Uses a modified Gaussian MA calculation that adapts to market volatility.
Employs Pine Script's line and label drawing capabilities for clear pivot point visualization.
Utilizes random color generation for the Gaussian scatterplot to enhance visual distinction between different time periods.
The LOWESS (Locally Weighted Scatterplot Smoothing) indicator offers traders a sophisticated tool for trend analysis and breakout detection. By combining advanced smoothing techniques with pivot point analysis, it provides a comprehensive view of market dynamics. The indicator's adaptability to different market conditions and its customizable nature make it suitable for various trading styles and timeframes.
Spiral Levels [ChartPrime]SPIRAL LEVELS
⯁ OVERVIEW
The Spiral Levels [ ChartPrime ] indicator, designed for use on TradingView and developed with Pine Script™ , leveraging a combination of traditional pivot points and spiral geometry to visualize support and resistance levels on the chart. By plotting spirals from pivot points, the indicator provides a distinctive perspective on potential price movements.
It's an experiment inspired from spirals in the Pine documentation and the concept of using spirals to add padding/offsets to SR zones in a market (an idea we plan to expand on in the future).
◆ USAGE
● Identifying Pivot Points: The indicator identifies significant pivot highs and lows based on user-defined criteria.
● Filtered Pivot Points: Pivot points for spirals are filtered using volume and high/low thresholds to ensure they are significant.
● Spiral Visualization: Spirals are plotted from these pivots, indicating potential future support and resistance levels or as liquidity zones.
Additionally, the plotted levels can serve as liquidity zones where the price might attempt to grab liquidity, providing a deeper understanding of market behavior at significant volume levels.
● Volume-Based Coloring: Spirals are colored based on volume data, providing additional context about the strength of the price movement.
● Labeling and Line Extensions: Labels display volume information, and lines extend from the end of the spirals to the current bar for clarity.
● Spiral Rotation: By adjusting the "Number of spiral rotations" input, you can control the number of rotations each spiral makes around a pivot point, offering more detailed insights. This also allows you to control the distance of levels from a pivot. More rotations will extend the spiral further from the pivot point, potentially identifying support and resistance levels or liquidity zones at greater distances.
This modification emphasizes that the number of rotations not only provides more detailed insights but also affects the spatial distribution of the identified levels relative to the pivot point.
⯁ USER INPUTS
● Pivots
Left Bars: Determines the number of bars to the left of the pivot.
Right Bars: Determines the number of bars to the right of the pivot.
● Filter
Volume Filter: Sets the threshold for volume filtering.
High & Low Filter: Sets the threshold for filtering pivot highs and lows.
● Spiral
Spirals Shown: Specifies the number of spirals to be displayed on the chart.
Number of spiral rotations: Sets the number of rotations for each spiral.
X Scale: Adjusts the horizontal scale of the spirals.
Y Scale: Adjusts the vertical scale of the spirals, relative to the ATR(200).
Reverse Spirals: Option to reverse the direction of the spirals.
⯁ TECHNICAL NOTES
The indicator uses Pine Script's polyline feature for smooth spiral rendering.
It implements a custom cross detection function to manage line and label visibility.
The script is optimized to limit calculations to the last 1000 bars for performance.
It automatically manages the number of displayed elements to prevent clutter and ensure smooth performance.
The Spiral Levels ChartPrime indicator offers a unique and visually engaging method to identify potential support and resistance levels. By integrating volume data and pivot points with spiral geometry, traders can gain valuable insights into market dynamics and make more informed trading decisions.
Volume Positive & Negative Levels [ChartPrime]Volume Positive & Negative Levels
Overview:
The Volume Positive & Negative Levels indicator by ChartPrime is designed to provide traders with a clear visualization of volume activity across different price levels. By plotting volume levels as histograms, this tool helps identify significant areas of buying (positive volume) and selling (negative volume) pressure, enhancing the ability to spot potential support and resistance zones.
Key Features:
⯁ Lookback Period:
- The `lookbackPeriod` parameter, set to 500 bars, determines the range over which the volume analysis is conducted, ensuring a comprehensive view of the market’s volume activity. The maximum lookback period is 500 bars or the bars currently visible on the chart, whichever is smaller.
⯁ Dynamic Volume Calculation:
- Volume is calculated dynamically based on the price action, with positive volume indicating buying pressure (close > open) and negative volume indicating selling pressure (close < open).
⯁ Color Coding for Clarity:
- Positive Volume: Represented with a distinct color (`#ad9a2c`), making it easy to identify areas of buying interest.
- Negative Volume: Highlighted with another color (`#ad2cad`), simplifying the detection of selling pressure.
Volume Threshold and Bins:
- The indicator allows users to set a volume threshold (`volume_level`) to highlight significant volume levels, with the default set at 70.
- The number of bins (`numBins`) defines the granularity of the volume profile, with a higher number providing more detail.
⯁ Volume Profile Visualization:
- The volume profile is plotted as a histogram, with the height of each bar proportional to the volume at that price level. This visualization helps in quickly assessing the strength of volume at various price points.
⯁ Interactive Labels and Threshold Indicators:
- Labels: The indicator uses labels to mark significant volume levels, providing quick reference points for traders.
- Threshold Lines: Lines are drawn at specified volume thresholds, with colors and widths dynamically adjusted based on the volume levels.
⯁ User Inputs:
- Volume Threshold (`volume_level`): Sets the minimum volume required to highlight significant levels.
- Number of Bins (`numBins`): Determines the resolution of the volume profile.
- Line Width (`line_withd`): Specifies the width of the lines used in the visualization.
The Volume Positive & Negative Levels indicator is a powerful tool for traders looking to gain deeper insights into market dynamics. By providing a clear visual representation of volume activity across different price levels, it helps traders identify key support and resistance zones, spot trends, and make more informed trading decisions. Whether you are a day trader or a swing trader, this indicator enhances your ability to analyze volume data effectively, improving your overall trading strategy.
Bayesian Trend Indicator [ChartPrime]Bayesian Trend Indicator
Overview:
In probability theory and statistics, Bayes' theorem (alternatively Bayes' law or Bayes' rule), named after Thomas Bayes, describes the probability of an event, based on prior knowledge of conditions that might be related to the event.
The "Bayesian Trend Indicator" is a sophisticated technical analysis tool designed to assess the direction of price trends in financial markets. It combines the principles of Bayesian probability theory with moving average analysis to provide traders with a comprehensive understanding of market sentiment and potential trend reversals.
At its core, the indicator utilizes multiple moving averages, including the Exponential Moving Average (EMA), Simple Moving Average (SMA), Double Exponential Moving Average (DEMA), and Volume Weighted Moving Average (VWMA) . These moving averages are calculated based on user-defined parameters such as length and gap length, allowing traders to customize the indicator to suit their trading strategies and preferences.
The indicator begins by calculating the trend for both fast and slow moving averages using a Smoothed Gradient Signal Function. This function assigns a numerical value to each data point based on its relationship with historical data, indicating the strength and direction of the trend.
// Smoothed Gradient Signal Function
sig(float src, gap)=>
ta.ema(source >= src ? 1 :
source >= src ? 0.9 :
source >= src ? 0.8 :
source >= src ? 0.7 :
source >= src ? 0.6 :
source >= src ? 0.5 :
source >= src ? 0.4 :
source >= src ? 0.3 :
source >= src ? 0.2 :
source >= src ? 0.1 :
0, 4)
Next, the indicator calculates prior probabilities using the trend information from the slow moving averages and likelihood probabilities using the trend information from the fast moving averages . These probabilities represent the likelihood of an uptrend or downtrend based on historical data.
// Define prior probabilities using moving averages
prior_up = (ema_trend + sma_trend + dema_trend + vwma_trend) / 4
prior_down = 1 - prior_up
// Define likelihoods using faster moving averages
likelihood_up = (ema_trend_fast + sma_trend_fast + dema_trend_fast + vwma_trend_fast) / 4
likelihood_down = 1 - likelihood_up
Using Bayes' theorem , the indicator then combines the prior and likelihood probabilities to calculate posterior probabilities, which reflect the updated probability of an uptrend or downtrend given the current market conditions. These posterior probabilities serve as a key signal for traders, informing them about the prevailing market sentiment and potential trend reversals.
// Calculate posterior probabilities using Bayes' theorem
posterior_up = prior_up * likelihood_up
/
(prior_up * likelihood_up + prior_down * likelihood_down)
Key Features:
◆ The trend direction:
To visually represent the trend direction , the indicator colors the bars on the chart based on the posterior probabilities. Bars are colored green to indicate an uptrend when the posterior probability is greater than 0.5 (>50%), while bars are colored red to indicate a downtrend when the posterior probability is less than 0.5 (<50%).
◆ Dashboard on the chart
Additionally, the indicator displays a dashboard on the chart , providing traders with detailed information about the probability of an uptrend , as well as the trends for each type of moving average. This dashboard serves as a valuable reference for traders to monitor trend strength and make informed trading decisions.
◆ Probability labels and signals:
Furthermore, the indicator includes probability labels and signals , which are displayed near the corresponding bars on the chart. These labels indicate the posterior probability of a trend, while small diamonds above or below bars indicate crossover or crossunder events when the posterior probability crosses the 0.5 threshold (50%).
The posterior probability of a trend
Crossover or Crossunder events
◆ User Inputs
Source:
Description: Defines the price source for the indicator's calculations. Users can select between different price values like close, open, high, low, etc.
MA's Length:
Description: Sets the length for the moving averages used in the trend calculations. A larger length will smooth out the moving averages, making the indicator less sensitive to short-term fluctuations.
Gap Length Between Fast and Slow MA's:
Description: Determines the difference in lengths between the slow and fast moving averages. A higher gap length will increase the difference, potentially identifying stronger trend signals.
Gap Signals:
Description: Defines the gap used for the smoothed gradient signal function. This parameter affects the sensitivity of the trend signals by setting the number of bars used in the signal calculations.
In summary, the "Bayesian Trend Indicator" is a powerful tool that leverages Bayesian probability theory and moving average analysis to help traders identify trend direction, assess market sentiment, and make informed trading decisions in various financial markets.
Volume Storm Trend [ChartPrime]The Volume Storm Trend (VST) indicator is a robust tool for traders looking to analyze volume momentum and trend strength in the market. By incorporating key volume-based calculations and dynamic visualizations, VST provides clear insights into market conditions.
Components:
Calculating the median of the source data.
Volume Power Calculation: The indicator calculates the "heat power" and "cold power" by applying an Exponential Moving Average (EMA) to the median of volume data arrays.
// ---------------------------------------------------------------------------------------------------------------------}
// 𝙄𝙉𝘿𝙄𝘾𝘼𝙏𝙊𝙍 𝘾𝘼𝙇𝘾𝙐𝙇𝘼𝙏𝙄𝙊𝙉𝙎
// ---------------------------------------------------------------------------------------------------------------------{
max_val = 1000
src = close
source = ta.median(src, len)
heat.push(src > source ? (volume > max_val ? max_val : volume) : 0)
heat.remove(0)
cold.push(src < source ? (volume > max_val ? max_val : volume) : 0)
cold.remove(0)
heat_power = ta.ema(heat.median(), 10)
cold_power = ta.ema(cold.median(), 10)
Visualization:
Gradient Colors: The indicator uses gradient colors to visualize bullish volume and bearish volume powers, providing a clear contrast between rising and falling trends.
Bars Fill Color: The color fill between high and low prices changes based on whether the heat power is greater than the cold power.
Bottom Line: A zero line with changing colors based on the dominance of heat or cold power.
Weather Symbols: Visual indicators ("☀" for hot weather and "❄" for cold weather) appear on the chart when the heat and cold powers crossover, helping traders quickly identify trend changes.
Inputs:
Source: The input data source, typically the closing price.
Median Length: The period length for calculating the median of the source. Default is 40.
Volume Length: The period length for calculating the average volume. Default is 3.
Show Weather: A toggle to display weather symbols on the chart. Default is false.
Temperature Type: Allows users to choose between Celsius (°C) and Fahrenheit (°F) for temperature display.
Show Weather Function:
The `Show Weather?` function enhances the VST indicator by displaying weather symbols ("☀" for hot and "❄" for cold) when there are significant crossovers between heat power and cold power. This feature adds a visual cue for potential market tops and bottoms. When the market heats to a high temperature, it often indicates a potential top, signaling traders to consider exiting long positions or preparing for a reversal.
Additional Features:
Dynamic Table Display: A table displays the current "temperature" on the chart, indicating market heat based on the calculated heat and cold powers.
The Volume Storm Trend indicator is a powerful tool for traders
looking to enhance their market analysis with volume and momentum insights, providing a clear and visually appealing representation of key market dynamics.
Liquidations [ChartPrime]Liquidations Indicator:
The Liquidations indicator is a powerful tool designed to help traders identify significant liquidation levels in financial markets. By analyzing volume data over a specified lookback period, the indicator highlights potential areas where market participants with high leverage positions may face liquidation, providing valuable insights into market dynamics.
Usage:
Traders can use the Liquidations indicator to:
◈ Identify liquidity grab opportunities: Liquidation levels often attract price action as market participants with leveraged positions face the risk of forced liquidation. Traders can anticipate price movements as the market aims to trigger these stops, potentially leading to rapid price movements or reversals.
◈ Confirm trend strength: A cluster of liquidation levels in the same direction as the prevailing trend may confirm the strength of the trend, while divergences between liquidation levels and price movements may signal potential trend reversals.
Settings:
◈ Previous Value Bars Back: Specifies the number of previous bars used in calculating the liquidation levels.
◈ Show Leverage: Allows users to selectively display liquidation levels for different leverage multiples, including 5x, 10x, 25x, 50x, and 100x.
◈ Liquidation Levels Width: Sets the width of the lines representing liquidation levels on the chart.
◈ Short Liquidations Color: Specifies the color of the lines representing short liquidation levels.
◈ Long Liquidations Color: Specifies the color of the lines representing long liquidation levels.
◈ Bar Color: Sets the color of the background bar when the indicator is active.
Visual Representation:
◈ Liquidation levels are plotted as horizontal lines on the chart, with different colors representing short and long liquidation levels.
◈ Each liquidation level is labeled with the corresponding leverage multiple (e.g., 5x, 10x, etc.).
A dashboard displays the active liquidation levels for each leverage multiple, allowing traders to quickly assess the current market conditions.
◈ Time Window allows users to cut off unnecessary part of the chart and concentrate on a current active part of the chart to make better trading decisions:
Interpretation:
Market participants tend to place stop-loss orders near liquidation levels , creating clusters of pending orders. As price approaches these levels, it may trigger a cascade of stop-loss orders, providing liquidity for market orders and potentially leading to rapid price movements in the opposite direction.
Traders can anticipate price reversals or accelerations as price interacts with liquidation levels, using them as reference points for identifying potential entry or exit opportunities.
Note:
While the Liquidations indicator provides valuable insights into market dynamics, traders should use it in conjunction with other technical analysis tools and risk management strategies to make informed trading decisions.
Relative Average Extrapolation [ChartPrime]Relative Average Extrapolation (ChartPrime) is a new take on session averages, like the famous vwap . This indicator leverages patterns in the market by leveraging average-at-time to get a footprint of the average market conditions for the current time. This allows for a great estimate of market conditions throughout the day allowing for predictive forecasting. If we know what the market conditions are at a given time of day we can use this information to make assumptions about future market conditions. This is what allows us to estimate an entire session with fair accuracy. This indicator works on any intra-day time frame and will not work on time frames less than a minute, or time frames that are a day or greater in length. A unique aspect of this indicator is that it allows for analysis of pre and post market sessions independently from regular hours. This results in a cleaner and more usable vwap for each individual session. One drawback of this is that the indicator utilizes an average for the length of a session. Because of this, some after hour sessions will only have a partial estimation. The average and deviation bands will work past the point where it has been extrapolated to in this instance however. On low time frames due to the limited number of data points, the indicator can appear noisy.
Generally crypto doesn't have a consistent footprint making this indicator less suitable in crypto markets. Because of this we have implemented other weighting schemes to allow for more flexibility in the number of use cases for this indicator. Besides volume weighting we have also included time, volatility, and linear (none) weighting. Using any one of these weighting schemes will transform the vwap into a wma, volatility adjusted ma, or a simple moving average. All of the style are still session period and will become longer as the session progresses.
Relative Average Extrapolation (ChartPrime) works by storing data for each time step throughout the day by utilizing a custom indexing system. It takes the a key , ie hour/minute, and transforms it into an array index to stor the current data point in its unique array. From there we can take the current time of day and advance it by one step to retrieve the data point for the next bar index. This allows us to utilize the footprint the extrapolate into the future. We use the relative rate of change for the average, the relative deviation, and relative price position to extrapolate from the current point to the end of the session. This process is fast and effective and possibly easier to use than the built in map feature.
If you have used vwap before you should be familiar with the general settings for this indicator. We have made a point to make it as intuitive for anyone who is already used to using the standard vwap. You can pick the source for the average and adjust/enable the deviation bands multipliers in the settings group. The average period is what determines the number of days to use for the average-at-time. When it is set to 0 it will use all available data. Under "Extrapolation" you will find the settings for the estimation. "Direction Sensitivity" adjusts how sensitive the indicator is to the direction of the vwap. A higher number will allow it to change directions faster, where a lower number will make it more stable throughout the session. Under the "Style" section you will find all of the color and style adjustments to customize the appearance of this indicator.
Relative Average Extrapolation (ChartPrime) is an advanced and customizable session average indicator with the ability to estimate the direction and volatility of intra-day sessions. We hope you will find this script fascinating and useful in your trading and decision making. With its unique take on session weighting and forecasting, we believe it will be a secret weapon for traders for years to come.
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Fibonacci Archer Box [ChartPrime]Fibonacci Archer Box (ChartPrime) is a full featured Fibonacci box indicator that automatically plots based on pivot points. This indicator plots retracement levels, time lines, fan lines, and angles. Each one of these features are fully customizable with the ability to disable individual features. A unique aspect to this implementation is the ability to set targets based on retracement levels and time zones. This is set to 0.618 by default but you can pick any Fibonacci zone you like. Also included are markings that show you when Fibonacci levels are met or exceeded. These moments are plotted on the chart as colored dots that can be enabled or disabled. Along with these markings are crosses that can be shown when targets are hit. Both of these markings are colored with the related Fibonacci level colors.
When there is a zig-zag, this indicator will test to see if the zig-zag meets the criteria set up by the user before plotting a new Fibonacci box. You can pick from either higher highs or lower highs for bearish patterns, and higher lows or lower lows for bullish patterns. Both patterns can be set to use both when finding new boxes if you want to make it more sensitive. You also have the option to filter based on minimum and maximum size. If the box isn't within the selected size range, it will simply be ignored. The pivot levels can be configured to use either candle wicks or candle bodies. By default this is configured to use candle wick with a lookforward of 5 and lookback of 10.
We have included alerts for Fibonacci level crosses, Fibonacci time crosses, and target hits. All alerts are found in the add alert section built into tradingview to make alert creation as easy as possible. Each alert is labeled with their correct names to make navigation simple.
W.D. Gann, a renowned figure in the world of trading and market analysis, is often questioned for his use of Fibonacci levels in his strategies. However, evidence points to the fact that Gann did not directly employ Fibonacci price levels in his work. Instead, Gann had his unique approach, dividing price ranges into thirds, eighths, and other fractions, which, although somewhat aligning with Fibonacci levels, are not exact matches. It is clear that Gann was familiar with Fibonacci and the golden ratio, as references to them appear in his recommended reading list and some of his writings. Despite this awareness, Gann chose not to incorporate Fibonacci levels explicitly in his methodologies, preferring instead to use his divisions of price and time. Notably, Gann's emphasis on the 50% level—a marker not associated with Fibonacci numbers—further illustrates his departure from Fibonacci usage. This level, despite its popularity among some Fibonacci enthusiasts, does not stem from Fibonacci's sequence. This is why we opted to call this indicator Fibonacci Archer Box instead of a Gann Box as we didn't feel like it was appropriate.
In summary, the Fibonacci Archer Box (ChartPrime) is a tool that incorporates Fibonacci retracements and projections with an automated pivot point-based plotting system. It allows for customization across various features including retracement levels, timelines, fan lines, and angles, and integrates visual cues for level crosses and target hits. While it acknowledges the methodologies of W.D. Gann, it distinctively utilizes Fibonacci techniques, providing a straightforward tool for market analysis. We hope you enjoy using this indicator as much as we enjoyed making it!
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Composite Trend Oscillator [ChartPrime]CODE DUELLO:
Have you ever stopped to wonder what the underlying filters contained within complex algorithms are actually providing for you? Wouldn't it be nice to actually visually inspect for that? Those would require some kind of wild west styled quick draw duel or some comparison method as a proper 'code duello'. Then it can be determined which filter can 'draw' the quickest from it's computational holster with the least amount of lag and smoothness.
In Pine we can do so, discovering how beneficial that would be. This can be accomplished by quickly switching from one filter to another by input() back and forth, requiring visual memory. A better way could be done by placing two indicators added to the chart and then eventually placed into one indicator pane on top of each other.
By adding a filter() helper function that calls other moving average functions chosen for comparison, it can put to the test which moving average is the best drawing filter suited to our expected needs. PhiSmoother was formerly debuted and now it is utilized in a more complex environment in a multitude of ways along side other commonly utilized filters. Now, you the reader, get to judge for yourself...
FILTER VERSATILITY:
Having the capability to adjust between various smoothing methods such as PhiSmoother, TEMA, DEMA, WMA, EMA, and SMA on historical market data within the code provides an advantage. Each of these filter methods offers distinct advantages and hinderances. PhiSmoother stands out often by having superb noise rejection, while also being able to manipulate the fine-tuning of the phase or lag of the indicator, enhancing responsiveness to price movements.
The following are more well-known classic filters. TEMA (Triple Exponential Moving Average) and DEMA (Double Exponential Moving Average) offer reduced transient response times to price changes fluctuations. WMA (Weighted Moving Average) assigns more weight to recent data points, making it particularly useful for reduced lag. EMA (Exponential Moving Average) strikes a balance between responsiveness and computational efficiency, making it a popular choice. SMA (Simple Moving Average) provides a straightforward calculation based on the arithmetic mean of the data. VWMA and RMA have both been excluded for varying reasons, both being unworthy of having explanation here.
By allowing for adjustment refinements between these filter methods, traders may garner the flexibility to adapt their analysis to different market dynamics, optimizing their algorithms for improved decision-making and performance on demand.
INDICATOR INTRODUCTION:
ChartPrime's Composite Trend Oscillator operates as an oscillator based on the concept of a moving average ribbon. It utilizes up to 32 filters with progressively longer periods to assess trend direction and strength. Embedded within this indicator is an alternative view that utilizes the separation of the ribbon filaments to assess volatility. Both versions are excellent candidates for trend and momentum, both offering visualization of polarity, directional coloring, and filter crossings. Anyone who has former experience using RSI or stochastics may have ease of understanding applying this to their chart.
COMPOSITE CLUSTER MODES EXPLAINED:
In Trend Strength mode, the oscillator behavior signifies market direction and movement strength. When the oscillator is rising and above zero, the market is within a bullish phase, and visa versa. If the signal filter crosses the composite trend, this indicates a potential dynamic shift signaling a possible reversal. When the oscillator is teetering on its extremities, the market is more inclined to reverse later.
With Volatility mode, the oscillator undergoes a transformation, displaying an unbounded oscillator driven by market volatility. While it still employs the same scoring mechanism, it is now scaled according to the strength of the market move. This can aid with identification of ranging scenarios. However, one side effect is that the oscillator no longer has minimum or maximum boundaries. This can still be advantageous when considering divergences.
NOTEWORTHY SETTINGS FEATURES:
The following input settings described offer comprehensive control over the indicator's behavior and visualization.
Common Controls:
Price Source Selection - The indicator offers flexibility in choosing the price source for analysis. Traders can select from multiple options.
Composite Cluster Mode - Choose between "Trend Strength" and "Volatility" modes, providing insights into trend directionality or volatility weighting.
Cluster Filter and Length - Selects a filter for the cluster composition. This includes a length parameter adjustment.
Cluster Options:
Cluster Dispersion - Users can adjust the separation between moving averages in the cluster, influencing the sensitivity of the analysis.
Cluster Trimming - By modifying upper and lower trim parameters, traders can adjust the sensitivity of the moving averages within the cluster, enhancing its adaptability.
PostSmooth Filter and Length - Choose a filter to refine the composite cluster's post-smoothing with a length parameter adjustment.
Signal Filter and Length - Users can select a filter for the lagging signal plot, also having a length parameter adjustment.
Transition Easing - Sensitivity adjustment to influence the transition between bullish and bearish colors.
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Deep Volume [ChartPrime]Deep Volume is an indicator designed to give you high fidelity volume information. It does this by utilizing real time data provided by Tradingview to generate a wide range of metrics. We have included a convenient column chart to visualize the polarity of the volume, and a table to see the real time data. This works by utilizing pine script's varip feature to get information within candles. This is convenient as it allows users to get lower time frame information without the use of ltf functions. The result is seconds level data with out the need to be on a lower time frame chart. As a result, as you increase the time frame of the chart the updates will become slower. This is because Tradingview doesn't update the chart information as frequently on higher time frames as there isn't as much of a need.
This indicator works on real time data so to compensate for this we generate a simulated history based on candle structure. This helps in estimating the state of the moving average before the real time data starts. As a result the estimated history isn't as accurate and should be treated as such. That being said it is nice to have an estimation when the indicator is first loaded onto the chart.
Finally we have included a cumulative volume comparison that shows you how much volume there is compared to the average cumulative volume for the day. This metric utilizes a gradient to help you interpret the information at a glance. Low daily volume is represented with grays by default, while normal volume and greater is represented with a green color by default.
The table is partitioned into two sections; tick data, and average data. On the left you will see color coded information based on the direction of the move. On the left, the information is color coded based on the average movement direction. You can control how much information is displayed in the table within the indicators settings. This is defaulted to 20 but it can be as long or short as you like. Every new candle open the far left of the table you will see a 🗘 symbol and at the start of a new session you will see a 🗓 symbol.
The included metrics are as follows:
Time: This displays the time of the real time data update.
Time Delta: This displays the elapsed time between updates.
Order Size: This is the volume times the price change between updates.
Volume: This is the volume change for the update.
Price Change: This is the change in price since the last update.
Price: This is the price of the asset at the time of the update.
Speed of Tape: This is the average time delta. Use this to see how quickly the market is moving.
Average Order Size: This is the average order size.
Average Volume: This is the average volume
Volume Ratio: This the the ratio of bullish to bearish volume as expressed by a percent. 100% is all bullish within the window and -100% is all bearish within the window.
Average Price Change: This is the average price change within the window.
Sensitivity: This is a volatility metric designed to show you the price change per 1 volume unit.
Relative Sensitivity: This is a volatility metric designed to show you the average price change per average volume.
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Monte Carlo Future Moves [ChartPrime]ORIGINS AND HISTORICAL BACKGROUND:
Prior to the the advent of the Monte Carlo method, examining well-understood deterministic problems via simulation generally utilized statistical sampling to gauge uncertainty estimations. The Monte Carlo (MC) approach inverts this paradigm by modeling with probabilistic metaheuristics to address deterministic problems. Addressing Buffon's needle problem, an early form of the Monte Carlo method estimated π (3.14159) by dropping needles on a floor. Later, the modern MC inception primarily began when Stanislaw Ulam was playing solitaire games while experiencing illness and recovery.
Ulam further developed, applied, and ascribed "Monte Carlo" as a classified code name to maintain a level of secrecy for the modern method applications during collaborative investigations on neutron diffusion and collision intricacies with John von Neumann. Despite having relevant data, physicist's conventional deterministic mathematical methods were unable to solve mysterious "neutronion problems". Monte Carlo filled in the gaps necessary to resolve this perplexing neutron problem with innovative statistics, and the resilient MC continues onward to have diverse application in many fields of science. MC also extends into the realm of relevance within finance.
APPLICATION IN FINANCE:
Building on its historical roots, the Monte Carlo method's transition into finance opened new avenues for risk assessment and predictive analysis. In financial markets, characterized by uncertainty and complex variables, this method offers a powerful tool for simulating a wide range of scenarios and assessing probabilities of different outcomes. By employing probabilistic models to predict price movements, the Monte Carlo method helps in creating more resilient and informed trading strategies. This approach is particularly valuable in options pricing, portfolio management, and risk assessment, where understanding the range of potential outcomes is crucial for making sound investment decisions. Our indicator utilizes this methodology, blending traditional financial analysis with advanced statistical techniques.
THE INDICATOR:
The Monte Carlo Future Moves (ChartPrime) indicator is designed to predict future price movements. It simulates various possible price paths, showing the likelihood of different outcomes. We have designed it to be simple to use and understand by displaying lines indicating the most likely bullish and bearish outcomes. The arrows point to these areas making it intuitive to understand. Also included is extreme price levels shown in blue and yellow. This is the most likely extreme range that the price will move to. The outcome distribution is there to show you the range of outcomes along with a visual representation of the possible future outcomes. To make things more user friendly we have also included a representation of this distribution as a background heatmap. The brighter the price level, the more likely the price will end at that level. Finally, we have also included a market bias indication on the side that shows you the general bullish/bearish probabilities.
HOW TO USE:
To use this indicator you want to first assess the market bias. From there you want to target the most likely polar outcome. You can use the range of outcomes to assess your risk and set a stop within a reasonable range of the desired target. By default the indicator projects 10 steps into the future, however this can be easily adjusted in the settings. Generally this indicator excels at mid-term estimations and may yield inconclusive results if the prediction period is too short or too long. You can change the granularity of the outcomes to give you a more or less detailed view of the future. That being said, a lower resolution can make the predictions less useful while a higher resolution can give you a less useful picture. If you decide to use a higher resolution we have included an option to smooth the final result. This is intended to reduce the uncertainty and noise in the predicted outcomes. It is advised to use the minimum level of smoothing possible as a high level of smoothing will greatly reduce the accuracy.
INPUT SECTION:
Derivative Source changes how the indicator sees the price movements. When you set this to Candle it will use the difference between the open and close of each candle. If set to Move, it will use the difference between closing prices. If you are in a market with gaps, you might want to use Candle as this will prevent the indicator from seeing gaps.
Number of Simulations is a crucial setting as it is the core of this indicator. This determines the number of simulations the indicator will use to get its final result. By default it is set to 1000 as we feel like that is around the minimum number of simulations required to get a reasonable output while maintaining stability. In tests the maximum number of simulations we have been able to consistently achieve is 2000.
Lookback is the number of historical candles to account for. A lookback that is too short will not have enough data to accurately assess the likelihood of a price movement, while a period that is too large can make the data less relevant. By default this is set to 1000 as we feel like this is a reasonable tradeoff between volume of data and relevance.
Steps Into Future is the prediction period. By default we have picked a period of 10 steps as this has a good balance between accuracy and usability. The more steps into the future you go, the more uncertain the future outcome will be.
Outcome Granularity controls the precision of the simulated outcomes. By default this is set to 40 as its a good balance between resolution and accuracy.
Outcome Smoothing allows you to smooth the outcome distribution. By default this is set to 0 as it is generally not needed for lower resolutions. Smoothing levels beyond 2 are not recommended as it will negatively impact the output.
Returns Granularity controls the level of definition in the collected price movements. This directly impacts indicator performance and is set to 50 by default because its a good balance between fidelity and usability. When this number is too small, the simulations will be less accurate while numbers too large will negatively impact the probabilities of the movements.
Drift is the trend component in the simulation. This adds the directionality of the simulations by biasing the movements in the current direction of the market. We have included both the standard formula for drift and linear regression. Both methods are well suited for simulating future price movements and have their own advantages. The drift period is set to 100 by default as its a good balance between current and historical directionality. You may want to increase or decrease this number depending on the current market conditions but it is advised to use a period that isn't too small. If your period is too small it can skew the outcomes too much resulting in poor performance. When this is set to 0 it will use the same period as your lookback.
Volatility Adjust , adjusts the simulation to include current volatility. This makes sure that the price movements in the simulation reflects the current market conditions better by making sure that each price move is at least a minimum size.
Returns Style allows you to pick between using percent moves and log returns. We have opted to make percent move the default as it is more intuitive for beginners however both settings yield similar results. Log returns can be less cpu intensive so it might be desirable for longer term predictions.
Precision adjusts the rounding of used when collecting the frequency of price movement sizes. By default this is set to 4 as its is fairly accurate without impacting performance too much. A larger number will make the indicator more precise but at the cost of cpu time. Precision levels that are too small can greatly reduce the accuracy of the simulation and even break the indicator all together.
Update Every Bar allows you to recalculate the prediction every bar and is there for you if you want to strictly use the market bias. It is not recommended to enable this feature but it is there for flexibility.
Side of Chart allows you to pick what side of the price action you want the visuals to be on. When its set to the right everything will be to the right of the starting point and when its set to Left it will position everything to the left of the starting point.
Move Visualization is there to give you an arrow to the most likely bullish and bearish moves. It is meant as a visual aid and visualization tool. The color of these arrows use the same colors as the distribution.
Most Likely Move is a horizontal line that indicates the most likely move. It is positioned in the same location as the Move Visualization.
Standard Deviation is horizontal lines at the extremities of the simulated price action. These represent the most likely range of the future outcomes. You can adjust the multiplier of the standard deviation but by default it is set to 2.
Most Likely Direction is a vertical bar that shows you the sum of the up and down probabilities. It is there to show you the bias of the outcomes and guide you in decision making.
Max Probability Zone is a horizontal line that highlights the location of the highest probability move. You can think of it almost like the POC in a volume distribution but in this case it is the "most likely" single outcome.
Outcome Distribution allows you to toggle the distribution on or off. This is the distribution of all of the simulated outcomes. You can toggle the scale width of the distribution to fit your visual style.
Distribution Text toggles the probability text inside of the distribution bars. When you have a large number for the outcome granularity this text may not be visible and you may want to disable this feature.
Background is a heatmap of the outcome distribution. This allows you to visualize the underlying distribution without the need for the distribution histogram. The brighter the color, the more likely the outcome is for that level. It can be useful for visualizing the range of possible outcomes.
Starting Line is simply a horizontal line indicating the starting point of the simulation. It just the opening price for the starting position.
Extend Lines allows you to extend the lines and background past the prediction period.
CONCLUSION:
With its intuitive visuals and flexible settings, the Monte Carlo Future Moves (ChartPrime) indicator is practice and easy to use. It brings clarity to price movement predictions, helping you to build confidence in your strategies. This indicator not only reflects the evolution of technical analysis but also touches on data-driven insights.
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Dynamic Support/Resistance Zones [ChartPrime]Dynamic Support/Resistance Zones is a new way to visualize key support and resistance levels by analyzing pivot points. It aggregates these points into bins and uses different scoring methods to determine the strength of the zone. The Linear method treats every pivot the same, Time gives more importance to recent pivots, and Volume scores pivots based on trading activity.
It visually represents the strength of price zones using either a visual distribution or an overlay of colors. Areas with many aggregated pivots are marked using the High Color, indicating strong support or resistance. Fewer pivots are shown in Low Color, suggesting weaker levels. Users can also see the score using the distribution mode to more accurately determine the strength of these areas.
The indicator also includes a special moving average line, calculated from pivot prices and their weights. This gives a central pivot level, allowing you to see the average pivot position. We have also provided some smoothing for this line to make it easer to use.
We have included various options to tailor your analysis. These include selecting the scoring method for pivots and adjusting the number of pivots to consider, along with many visual aids. Traders can also set the level of filtering for the distribution of pivots. By default the filter isn't enabled but when it is enabled it allows for a less noisy experience at the expense of precision.
We have included four pivot periods that you can modify and toggle. The idea is that longer period pivots will enhance the strength of the shorter period ones providing a natural way to weight pivot levels. You can also specify whether you want to use pivot high, pivot low, or both in your analysis.
Here are some details on the key inputs:
Weighting Style: Choose how to score pivot points. Options include: Linear: Treats each pivot equally. Time: Gives more importance to recent pivots. Volume: Scores pivots based on trading volume.
Number of Pivots: Set the number of pivots to consider in the calculation. Both pivot highs and lows are treated separately.
Filtering: Adjust the level of filtering applied to the distribution of pivots. A higher value smooths the distribution, providing a cleaner visual representation at the cost of some precision. This setting is crucial for managing the trade-off between clarity and detail in the visualization of support and resistance zones.
Distribution Scale: Determines the scale of the distribution on the screen. It influences both the visual aspect and the precision of the calculations, allowing for a balance between visibility and analytical accuracy.
Manual Precision: Manually set the number of divisions within the range. This setting offers control over the granularity.
Auto Precision: When enabled, it automatically adjusts the precision based on the average range of a candle, ensuring a minimum level of detail in the visualization.
Show Distribution: Toggle the visibility of the distribution of pivot points. When activated, it provides a detailed visual representation of where pivots are concentrated.
Show Score in Distribution: Opt to display the actual score within the distribution. This feature adds a quantitative element to the visual representation, offering a clearer understanding of the pivot point concentration.
Distribution Overlay: Activate a heat map overlay to visualize the distribution of pivots. You can also adjusting the transparency of this overlay, providing a balanced view that does not obstruct the underlying price chart.
Show Support/Resistance: Enable lines that indicate identified support and resistance levels based on the aggregated pivots. This feature provides a clear, actionable insight directly on the chart.
S/R Zone Visibility: Choose to display the support/resistance zones and set their transparency. It offers an extended visual cue about the potential breadth of support or resistance areas.
Pivot Level Average: Introduce a moving average line that's calculated based on the weighted pivot levels. You can also adjust the smoothness of this line.
Dynamic Support/Resistance Zones is an intuitive and versatile trading indicator that offers a novel approach to identifying support and resistance levels by analyzing pivot points. It blends a variety of scoring methods, customizable visual representations, and a unique moving average line. With its customizable settings for pivot analysis, visual clarity, and precision, it's an nifty tool for traders looking to enhance their decision making with detailed and actionable insights.
Channels With Patterns [ChartPrime]The Channels With Patterns indicator is an attempt at minimizing the delay in forming a trend channel. This indicator uses a single pivot in conjunction with a smooth version of the price to estimate the direction of an emerging trend. Using ATR, this indicator estimates the volatility of the new trend by adjusting the channel size by a multiple of the current ATR.
One of the biggest complains for any trend indicator is that it takes too long to create a channel or trend line. This indicator estimates the trend channel by checking if the price is moving in the correct direction and then it projects the channel from a single pivot. To allow for some margin of error, this script uses an offset to help center the channel.
This offset is generated from the ATR at the time of formation. In conjunction with forming estimated trend channels, this indicator features select candle stick patterns. These candle stick patterns are filtered by location in the formed trend channel. If the price is within an extremity of the trend channel it will appear. Filtering classical vanilla candle stick patterns using this methodology can result in some interesting results and possible confluence points for traders. For example; a bearish hammer appearing when filtered in an upper zone might add an extra level of realtime unique confluence traders.
Traders can use this script as a general trend line indicator that is a bit more forward looking than others, or it can be used it as its full blown trend channel estimator. Due to the fact that this is an estimate using the minimum possible information to make the channel, its accuracy will not always be perfect and can suffer compared to alternative methods.
When configuring the indicator it is important to understand the role of each input. Here is a description of all of the settings provided:
Presets (`preset`): This input allows users to quickly configure the indicator based on the market they are trading in. Selecting "Stocks," "Forex," or "Crypto" automatically adjusts various parameters to settings deemed optimal for these markets. The "User" option lets traders manually configure settings for a more personalized approach.
Style (`style`): This setting determines how pivot points are calculated. "Wick" uses the high and low of candlesticks (including wicks), which can be more sensitive to market extremes. "Body" uses only the open and close prices (the body of the candlesticks), potentially offering a more stable pivot point calculation.
Break Style (`break_style`): This option defines what price is used to determine if a channel has been broken. "Close" uses the closing price of a candlestick, while "High/Low" uses the highest and lowest prices. This affects how channel breaks are identified and can influence trading signals.
Instant Mode (`instant`): When enabled, this feature allows the indicator to form channels more quickly by initiating them as soon as potential formations are detected. This can provide earlier signals but may increase the risk of false positives.
ATR Length (`atr_length`): This input sets the period for the Average True Range (ATR), a common volatility indicator. A longer ATR period may smooth out the channel but could delay responsiveness to market changes. A shorter period might make the channel more responsive but potentially more erratic.
Offset Center (`offset`): Adjusts the vertical positioning of the channel. This can help in aligning the channel more accurately with the price action, depending on market conditions and personal trading strategies.
Size (`atr_multiplier`): Alters the channel's size relative to the ATR. A higher multiplier makes a wider channel, which might be useful in more volatile markets. A lower multiplier tightens the channel, which could be better for less volatile conditions.
Padding % (`padding`): This setting adjusts the padding within the top and bottom quarters of the channel. It essentially fine-tunes the channel's sensitivity to price movements near its boundaries.
Pivot Length (`pivot_length`): Determines the number of bars used to calculate pivot points. A longer length may provide more significant pivot points but can reduce the number of channels formed.
Pivot Look Forward (`look_forward`): Sets the number of bars to look forward in the pivot calculation, affecting how quickly the channel adapts to new pivots.
Average H/L Length (`avg_length`): Controls the smoothing of the high and low prices used in the channel calculation. A longer average length can lead to smoother, more gradual channel slopes.
Enable Hammer (`enable_hammer`): When enabled, the indicator will highlight Hammer candlestick patterns, which are often considered bullish reversal indicators.
Enable Inverted Hammer (`enable_ihammer`): This toggles the display of Inverted Hammer patterns, typically viewed as potential bullish reversal signals.
Enable Bullish Engulfing (`enable_bullish_engulfing`): Enables the identification of Bullish Engulfing patterns, another type of bullish reversal indicator.
Enable Bearish Engulfing (`enable_bearish_engulfing`): When activated, this highlights Bearish Engulfing patterns, which are often interpreted as bearish reversal signals.
Extend Channel (`extend`): This option, when enabled, extends the drawn channels forward until they are either broken or a new channel is formed.
Show Break Label (`show_break_label`): Toggles the display of labels indicating where the channel has been broken, providing visual cues for potential trade entries or exits.
Channel History Length (`history_length`): Determines how many historical channels are displayed on the chart. This can be useful for analyzing past performance and patterns.
Channel Colors (`top_color`, `bottom_color`, `center_color`): These settings allow customization of the channel's appearance by setting the colors of the top, bottom, and center lines.
Line Transparency (`line_trans`): Adjusts the transparency of the channel lines, helping to balance visibility with chart readability.
Center Line Transparency (`center_trans`): Specifically sets the transparency level of the center line of the channel.
Channel Fill Transparency (`fill_trans`): Modifies the transparency of the filled areas between the channel lines, which can enhance chart clarity and focus on the price action.
Break Colors (`break_up_color`, `break_down_color`): Sets the colors for labels that appear when the channel is broken, either upwards or downwards.
Break Label Text Color (`text_color`): Determines the color of the text in the break labels, enhancing readability based on the chart's background and color scheme.
Candle Pattern Colors (`h_color`, `ih_color`, `bullish_engulfing_color`, `bearish_engulfing_color`): These inputs allow for the customization of the colors used to highlight various candle patterns on the chart.
Candle Pattern Text Color (`candle_text_color`): Sets the color of the text for labels associated with candle pattern indicators.
Alerts (`new_channel_alert`, `break_alert`, `hammer_alert`, `ihammer_alert`, `bullish_engulfing_alert`, `bearish_engulfing_alert`): These toggles enable or disable alerts for different events, such as the formation of new channels, channel breaks, or the appearance of specific candle patterns. This feature is crucial for traders who rely on timely notifications for potential trading opportunities.
We have provided a few presets to allow you to get a feeling for how the indicator works with different settings easily. Here is a description of the settings used in each preset:
Stocks Preset:
Style: "Wick"
Break Style: False (High/Low)
Instant Mode: True
ATR Length: 10
Size (ATR Multiplier): 4
Pivot Length: 10
Pivot Look Forward: 15
Average H/L Length: 18
Forex Preset:
Style: "Wick"
Break Style: False (High/Low)
Instant Mode: True
ATR Length: 100
Size (ATR Multiplier): 5
Pivot Length: 10
Pivot Look Forward: 15
Average H/L Length: 18
Crypto Preset:
Style: "Wick"
Break Style: False (High/Low)
Instant Mode: True
ATR Length: 10
Size (ATR Multiplier): 4
Pivot Length: 10
Pivot Look Forward: 15
Average H/L Length: 18
This script first starts by defining and collecting the relevant data for the main body of the code with data(). This generates the pivot data, the levels, the ranges, the averages, the deltas, and finally the candle sticks. Once there is a higher low, or lower high detected via the pivots and the current price it triggers the formation of the new channel. It takes the delta between the last pivot and the current average price and projects the trend channel using this delta. If the price exceeds the extremities of the channel it will classify this as a break from the estimated structure and begin looking for a new channel. The idea is that when trending, the price will oscillate between extremities as defined by a range and direction. If the price is inside of one of these extremities the script will look for candle stick patterns. This is how the script operates.
On a more technical level, this script is meant to showcase Pine Script's custom types and methods. We have made use of a properties pattern allows functions to use a minimal number of arguments. This allows you to add new inputs without modifying a string of functions. The use of methods and data structures allows the main body of the code to be easy to understand and for the script as a whole to be easily modified. We have made sure that the script is modular so that users can incorporate this into their own custom scripts. It should be easy to expand on this script as the main logic is fairly compact and open for easy modification. All features are packed into their own function for easy use elsewhere. This is particularly evident in the candle stick section. I have simplified the process of creating candle stick patterns by creating a type. All users have to do is make methods for this type.
candle()=>
polarity = open < close
body_top = math.max(open, close)
body_bottom = math.min(open, close)
body_range = body_top - body_bottom
top_wick = high - body_top
bottom_wick = body_bottom - low
average_body = ta.ema(body_range, 14)
average_top_wick = ta.ema(top_wick, 14)
average_bottom_wick = ta.ema(bottom_wick, 14)
has_body = body_range != 0
has_top_wick = top_wick != 0
has_bottom_wick = bottom_wick != 0
above_average_body = body_range > average_body
above_average_top_wick = top_wick > average_top_wick
above_average_bottom_wick = bottom_wick > average_bottom_wick
candle_data.new(
polarity
, body_top
, body_bottom
, body_range
, top_wick
, bottom_wick
, average_body
, average_top_wick
, average_bottom_wick
, has_body
, has_top_wick
, has_bottom_wick
, above_average_body
, above_average_top_wick
, above_average_bottom_wick
)
In conclusion, this script offers a blend of rapid trend channel formation and candlestick pattern recognition, making it a unique tool for traders looking for a more proactive approach to trend analysis.
Liquidity Hunter [ChartPrime]The Liquidity Hunter helps traders identify areas in the market where reversals may occur by analyzing candle formations and structures.
█ Wick-to-Body Analysis:
The Liquidity Hunter analyses each candlestick to identify those with distinctive wick-to-body ratios. By focusing on candles with significant wick imbalances, it can reveal potential liquidity absorption zones that may influence market behavior. Users can fine-tune this ratio to their preferences through customizable body% and wick% inputs, allowing for tailored analysis.
█ Body Size Significance:
To ensure the relevance and impact of its findings, this indicator evaluates the size of the candle body.
Only candles with bodies meeting a certain size threshold are considered, eliminating noise and highlighting candles of significance.
█ Dynamic Target Setting:
The Liquidity Hunter employs the Average True Range (ATR) as a foundation for target calculation. Users can adjust their trading targets by specifying a multiplier, offering flexibility in capturing potential profit or managing risk. Customizable target inputs ensure adaptability to your trading strategy.
█ Stop Loss Protection:
In addition to setting your profit targets, the Liquidity Hunter incorporates stop loss levels, safeguarding your investments from excessive risk. By implementing a well-balanced risk-reward ratio, users may be better at navigating market fluctuations.
█ Market Character Labels:
The Liquidity Hunter Indicator goes beyond basic analysis by detecting changes in market character. It identifies shifts in sentiment providing traders with invaluable insights into evolving market conditions.
█ Candle Color Highlighting:
To enhance user-friendliness and visualization, the indicator employs distinctive candle colors between trades. These color cues help you easily spot and interpret trading opportunities, drawing your attention to potential entry and exit points.
Overall this indicator is designed to help simplify liquidity analysis and give visual targets in a market.
Volume HeatMap With Profile [ChartPrime]The Volume Heatmap with Profile indicator is a tool designed to provide traders with a comprehensive view of market activity through customizable visualizations. This indicator goes beyond traditional volume analysis by offering a range of adjustable parameters and features that enhance analysis of volume and give a cleaner experience when analyzing it.
To get started click the start and end time for the profile.
Key Features:
Extended Calculation: This indicator extends its calculation to the last bar, ensuring that the user has insights into current market dynamics.
Point of Control (POC): Easily identify the price level at which the highest trading activity has occurred, helping the user pinpoint potential reversal points and significant support/resistance zones.
VWAP Point of Control: Display the Volume Weighted Average Price (VWAP) Point of Control, giving the user a clear reference for determining the average price traders are paying and potential price reversals.
Adjustable Colors for Heatmap: Change the heatmap colors to the users preference, allowing the user to match the indicator's appearance to their chart style and personal visual preferences.
Forecasted Zone: This feature allows traders to forecast areas of high activity by providing the option to adjust colors within this zone. This feature assists in identifying potential breakouts or areas where increased trading volume is anticipated.
Volume Profile: Customize the colors of the volume profile to make it distinct and easily distinguishable on the chart.
Adjustable Volume Levels: Specify the number volume levels that are most relevant to your trading strategy.
Adjustable Placement for Volume Profile: Position the volume profile on the chart. Whether the user prefers it on the left, right, or at the center of the chart, this indicator offers placement flexibility.
The ratio of bull vs bear volume is plotted on the outside of the range indicating how bullish or bearish price action is in a given range.
Bollinger Bands Liquidity Cloud [ChartPrime]This indicator overlays a heatmap on the price chart, providing a detailed representation of Bollinger bands' profile. It offers insights into the price's behavior relative to these bands. There are two visualization styles to choose from: the Volume Profile and the Z-Score method.
Features
Volume Profile: This method illustrates how the price interacts with the Bollinger bands based on the traded volume.
Z-Score: In this mode, the indicator samples the real distribution of Z-Scores within a specified window and rescales this distribution to the desired sample size. It then maps the distribution as a heatmap by calculating the corresponding price for each Z-Score sample and representing its weight via color and transparency.
Parameters
Length: The period for the simple moving average that forms the base for the Bollinger bands.
Multiplier: The number of standard deviations from the moving average to plot the upper and lower Bollinger bands.
Main:
Style: Choose between "Volume" and "Z-Score" visual styles.
Sample Size: The size of the bin. Affects the granularity of the heatmap.
Window Size: The lookback window for calculating the heatmap. When set to Z-Score, a value of `0` implies using all available data. It's advisable to either use `0` or the highest practical value when using the Z-Score method.
Lookback: The amount of historical data you want the heatmap to represent on the chart.
Smoothing: Implements sinc smoothing to the distribution. It smoothens out the heatmap to provide a clearer visual representation.
Heat Map Alpha: Controls the transparency of the heatmap. A higher value makes it more opaque, while a lower value makes it more transparent.
Weight Score Overlay: A toggle that, when enabled, displays a letter score (`S`, `A`, `B`, `C`, `D`) inside the heatmap boxes, based on the weight of each data point. The scoring system categorizes each weight into one of these letters using the provided percentile ranks and the median.
Color
Color: Color for high values.
Standard Deviation Color: Color to represent the standard deviation on the Bollinger bands.
Text Color: Determines the color of the letter score inside the heatmap boxes. Adjusting this parameter ensures that the score is visible against the heatmap color.
Usage
Once this indicator is applied to your chart, the heatmap will be overlaid on the price chart, providing a visual representation of the price's behavior in relation to the Bollinger bands. The intensity of the heatmap is directly tied to the price action's intensity, defined by your chosen parameters.
When employing the Volume Profile style, a brighter and more intense area on the heatmap indicates a higher trading volume within that specific price range. On the other hand, if you opt for the Z-Score method, the intensity of the heatmap reflects the Z-Score distribution. Here, a stronger intensity is synonymous with a more frequent occurrence of a specific Z-Score.
For those seeking an added layer of granularity, there's the "Weight Score Overlay" feature. When activated, each box in your heatmap will sport a letter score, ranging from `S` to `D`. This score categorizes the weight of each data point, offering a concise breakdown:
- `S`: Data points with a weight of 1.
- `A`: Weights below 1 but greater than or equal to the 75th percentile rank.
- `B`: Weights under the 75th percentile but at or above the median.
- `C`: Weights beneath the median but surpassing the 25th percentile rank.
- `D`: All that fall below the 25th percentile rank.
This scoring feature augments the heatmap's visual data, facilitating a quicker interpretation of the weight distribution across the dataset.
Further Explanations
Volume Profile
A volume profile is a tool used by traders to visualize the amount of trading volume occurring at specific price levels. This kind of profile provides a deep insight into the market's structure and helps traders identify key areas of support and resistance, based on where the most trading activity took place. The concept behind the volume profile is that the amount of volume at each price level can indicate the potential importance of that price.
In this indicator:
- The volume profile mode creates a visual representation by sampling trading volumes across price levels.
- The representation displays the balance between bullish and bearish volumes at each level, which is further differentiated using a color gradient from `low_color` to `high_color`.
- The volume profile becomes more refined with sinc smoothing, helping to produce a smoother distribution of volumes.
Z-Score and Distribution Resampling
Z-Score, in the context of trading, represents the number of standard deviations a data point (e.g., closing price) is from the mean (average). It’s a measure of how unusual or typical a particular data point is in relation to all the data. In simpler terms, a high Z-Score indicates that the data point is far away from the mean, while a low Z-Score suggests it's close to the mean.
The unique feature of this indicator is that it samples the real distribution of z-scores within a window and then resamples this distribution to fit the desired sample size. This process is termed as "resampling in the context of distribution sampling" . Resampling provides a way to reconstruct and potentially simplify the original distribution of z-scores, making it easier for traders to interpret.
In this indicator:
- Each Z-Score corresponds to a price value on the chart.
- The resampled distribution is then used to display the heatmap, with each Z-Score related price level getting a heatmap box. The weight (or importance) of each box is represented as a combination of color and transparency.
How to Interpret the Z-Score Distribution Visualization:
When interpreting the Z-Score distribution through color and alpha in the visualization, it's vital to understand that you're seeing a representation of how unusual or typical certain data points are without directly viewing the numerical Z-Score values. Here's how you can interpret it:
Intensity of Color: This often corresponds to the distance a particular data point is from the mean.
Lighter shades (closer to `low_color`) typically indicate data points that are more extreme, suggesting overbought or oversold conditions. These could signify potential reversals or significant deviations from the norm.
Darker shades (closer to `high_color`) represent data points closer to the mean, suggesting that the price is relatively typical compared to the historical data within the given window.
Alpha (Transparency): The degree of transparency can indicate the significance or confidence of the observed deviation. More opaque boxes might suggest a stronger or more reliable deviation from the mean, implying that the observed behavior is less likely to be a random occurrence.
More transparent boxes could denote less certainty or a weaker deviation, meaning that the observed price behavior might not be as noteworthy.
- Combining Color and Alpha: By observing both the intensity of color and the level of transparency, you get a richer understanding. For example:
- A light, opaque box could suggest a strong, significant deviation from the mean, potentially signaling an overbought or oversold scenario.
- A dark, transparent box might indicate a weak, insignificant deviation, suggesting the price is behaving typically and is close to its average.
Retest Support Resistance Signals [ChartPrime]The Retest Support Resistance Signals Indicator is a powerful tool designed to assist traders in identifying key support and resistance levels within the market. Most importantly and uniquely it identifies retests of these structures and displays them on the trader's chart. By utilizing a combination of pivot points and price action analysis, this indicator offers valuable insights for both signal-based and support/resistance trading strategies.
Key Features & settings:
Retest Confirmation: The indicator waits for a break above a support or resistance level and observes subsequent price action. If price retraces and forms a wick below the level, followed by a bounce, the indicator identifies it as a retest and labels it as "R" to indicate potential support or resistance confirmation.
This indicator combines the benefits of signal-based trading and support/resistance analysis, providing users with a versatile trading tool suitable for various strategies.
Retest Weaker Toggle: Users have the option to enable or disable the retest weaker feature. When enabled, the indicator considers a support or resistance level weaker if it experiences a test. When disabled, the indicator assumes that a bounce may occur from the level.
Pivot Detection Customization: Users can adjust the pivot detection method based on either wicks or bodies. This flexibility allows traders to adapt the indicator to different market conditions and preferences. The trader can also customize the number of bars used for pivot detection on both the left and right sides. This feature enables traders to fine-tune the indicator's sensitivity and responsiveness.
Users also have control over how support or resistance levels are managed on the chart. They can choose to either stop updating the levels (freeze) or completely remove them (delete) from the chart.
Breakout Threshold Setting: Traders can adjust the breakout threshold until deletion setting. This setting determines the number of successful breakouts through a support or resistance level required to remove it from the chart. This feature helps filter out weaker levels and focus on more significant ones.
Shown above we see the retest labels in action denoted with an R label
This indicator can be a useful addition to an SR trader's toolkit. Identifying when a level in the market is retested can reveal interesting information about the underlying strength of a trend. This indicator has been designed with the two major schools of thought; a level gets weaker the more it's tested vs stronger the more it's tested. We have designed this therefore to be versatile and adapt to both thought procceses. The R labels should be taken and considered as a larger part of an analysis process and not followed blindly.
Parabolic Scalp Take Profit[ChartPrime]Indicators can be a great way to signal when the optimal time is for taking profits. However, many indicators are lagging in nature and will get market participants out of their trades at less than optimal price points. This take profit indicator uses the concept of slope and exponential gain to calculate when the optimal time is to take profits on your trades, thus making this a leading indicator.
Usage:
In essence the indicator will draw a parabolic line that starts from the market participants entry point and exponentially grows the slope of the line eventually intersecting with the price action. When price intersects with the parabolic line a take profit signal will appear in the form of an x. We have found that this take profit indicator is especially useful for scalp trades on lower timeframes.
How To Use:
Add the indicator to the chart. Click on the candle which the trade is on. Click on either the price which the trade will be at, or at the bottom of the candle in a long, or the top of a candle in a short. Select long or short. Open the settings of the indicator and adjust the aggressiveness to the desired value.
Settings:
- Start Time -- This is the bar in which your entry will be at, or occured at and the script will ask you to click on the bar with your mouse upon first adding the script.
- Start Price -- This is the price in which the entry will be at, or was at and the script will ask you to click on the price with your mouse upon first adding the script.
- Long/Short -- This is a setting which lets the script know if it is a long or a short trade, and the script will ask you to confirm this upon first adding it to the chart.
- Aggressiveness -- This directly affects how aggressive the exponential curve is. A value of 101 is the lowest possible setting, indicating a very non-aggressive exponential buildup. A value of 200 is the highest and most aggressive setting, indicating a doubling effect per bar on the slope.
MACD + SMA 200 Strategy (by ChartArt)Here is a combination of the classic MACD (moving average convergence divergence indicator) with the classic slow moving average SMA with period 200 together as a strategy.
This strategy goes long if the MACD histogram and the MACD momentum are both above zero and the fast MACD moving average is above the slow MACD moving average. As additional long filter the recent price has to be above the SMA 200. If the inverse logic is true, the strategy goes short. For the worst case there is a max intraday equity loss of 50% filter.
Save another $999 bucks with my free strategy.
This strategy works in the backtest on the daily chart of Bitcoin, as well as on the S&P 500 and the Dow Jones Industrial Average daily charts. Current performance as of November 30, 2015 on the SPX500 CFD daily is percent profitable: 68% since the year 1970 with a profit factor of 6.4. Current performance as of November 30, 2015 on the DOWI index daily is percent profitable: 51% since the year 1915 with a profit factor of 10.8.
All trading involves high risk; past performance is not necessarily indicative of future results. Hypothetical or simulated performance results have certain inherent limitations. Unlike an actual performance record, simulated results do not represent actual trading. Also, since the trades have not actually been executed, the results may have under- or over-compensated for the impact, if any, of certain market factors, such as lack of liquidity. Simulated trading programs in general are also subject to the fact that they are designed with the benefit of hindsight. No representation is being made that any account will or is likely to achieve profits or losses similar to those shown.
