8 AM & 9 AM NY Candle HighlighterThis indicator helps me to know when the 9am NY candle has closed above or below the previous candle.
Statistics
DOGE 15MIN**Warm Reminder:** This strategy is intended solely for exploratory research and experimentation to evaluate the effectiveness of various signals. Drawing inspiration from patterns observed on the DOGE cryptocurrency 15-minute chart, it provides a tailored framework to identify potential trading opportunities. For optimal results, it is currently recommended exclusively for DOGE 15min charts. Remember, trading involves inherent risks, and past performance is not indicative of future results. We are dedicated to ongoing optimizations and refinements to enhance its robustness across broader applications—stay tuned for updates!
#### **A. Long Entry Signals**
These conditions trigger a long position entry, provided the strategy has no existing position (position_size == 0) and is not blocked. Signals can be enabled/disabled via input toggles (e.g., enable_vix).
- **VIX Reversal (vix_long)**: VIX signal shifts from high to low volatility (non-high volatility), with RSI between 30-50.
- **RSI Oversold (rsi_long)**: RSI crosses above 30.
- **CVD Bullish (cvd_long)**: CVD is rising.
- **Price RSI Bullish (prsi_long)**: Price RSI crosses above 30 or a long signal is triggered.
- **RangeEMA Bullish (rema_long)**: Candlestick is above POC, with KAMA trend flipping upward.
- **ZVWAP Oversold (zvwap_long)**: ZVWAP enters the oversold zone.
- **KAMA + Volume Bullish (kama_long)**: KAMA trend flips upward, candlestick is above POC, volume is rising, and the candle is bullish (green).
- **Volume Burst Bullish (vol_burst_long)**: Volume RSI crosses below threshold (default 70), open > close (bearish/red candle), triggered within the last two candles. **Special: Ignores all blocks** (bypasses not_long, Pivot, OI, RSI/ADX extreme filters).
#### **B. Short Entry Signals**
Similar to long entries: requires no existing position and no blocks.
- **RSI Overbought (rsi_short)**: RSI crosses below 70.
- **CVD Bearish (cvd_short)**: CVD is declining.
- **Price RSI Bearish (prsi_short)**: Price RSI crosses below 70 or a short signal is triggered.
- **RangeEMA Bearish (rema_short)**: Candlestick is below POC, with KAMA trend flipping downward.
- **ZVWAP Overbought (zvwap_short)**: ZVWAP enters the overbought zone.
- **KAMA + Volume Bearish (kama_short)**: KAMA trend flips downward, candlestick is below POC, volume is declining, and the candle is bearish (red).
- **Chop Bearish (chop_short)**: Chop crosses below 38.2, with RSI > 50.
- **Volume Burst Bearish (vol_burst_short)**: Volume RSI crosses below threshold (default 70), RSI > 70, and close > open (bullish/green candle), triggered within the last two candles. **Special: Ignores all blocks** (bypasses not_short, Pivot, OI, RSI/ADX extreme filters).
#### **C. Long Entry Blocks/Filters**
These conditions block long entries unless the signal ignores blocks (e.g., Volume Burst).
- **Base Prohibition (not_long)**: Volume is declining, or ADX is bearish (di_bear), or VIX is in high volatility (vix_flag), or RSI < 30.
- **Pivot Filter**: Recent Pivot is in a disadvantaged position.
- **OI Filter**: OI is declining.
- **RSI/ADX Extreme Filter**: RSI > 70 or ADX is bullish (di_bull).
- **Other**: Strategy already has a position (position_size != 0), or extreme volatility (is_extreme, though disabled in code).
#### **D. Short Entry Blocks/Filters**
Similar to long blocks.
- **Base Prohibition (not_short)**: Volume is rising, or (Chop < 38.2 and RSI > 50), or ADX is bullish (di_bull), or RSI > 70.
- **Pivot Filter**: Recent Pivot is in a disadvantaged position.
- **OI Filter**: OI is rising.
- **RSI/ADX Extreme Filter**: RSI < 30 or ADX is bearish (di_bear).
- **Other**: Existing position, or extreme volatility.
#### **E. Long Exit Signals**
Triggers closing of long positions, based on states (e.g., super_long, weak_long, only_kama).
- **KAMA Bearish Flip (exist_long)**: KAMA trend flips downward, or KAMA is downward with a short signal.
- **VIX Signal**: VIX shifts from low to high volatility, with RSI < 50.
- **Reversal Signal**: Short signal present and KAMA is downward.
- **Weak Trend Stop-Loss (weak_stop_long)**: In weak_long state, candlestick near POC, and close crosses below POC.
- **Weak KAMA Stop-Loss (weak_kama_long)**: In weak_long state, candlestick far from POC, and KAMA trend reverses.
- **Global Exit (exist_all)**: Volume RSI crosses below threshold (vol_under), or KAMA exit (kama_exit_long), or weak stop-loss, etc.
- **Special**: If in strong_long_hold (only_kama and KAMA remains bullish), ignore certain exit signals to hold the position.
#### **F. Short Exit Signals**
Similar to long exits.
- **KAMA Bullish Flip (exist_short)**: KAMA trend flips upward, or KAMA is upward with a long signal.
- **Reversal Signal**: Long signal present and KAMA is upward.
- **Weak Trend Stop-Loss (weak_stop_short)**: In weak_short state, candlestick near POC, and close crosses above short_state.current_max.
- **Weak KAMA Stop-Loss (weak_kama_short)**: In weak_short state, candlestick far from POC, and KAMA flips upward.
- **Global Exit (exist_all)**: Same as above.
Orthogonal Projections to Latent Structures (O-PLS)Version 0.1
Orthogonal Projections to Latent Structures (O-PLS) Indicator for TradingView
This indicator, named "Orthogonal Projections to Latent Structures (O-PLS)", is designed to help traders understand the relevance or predictive power of various market variables on the future close price of the asset it's applied to. Unlike standard correlation coefficients that show a simple linear relationship, O-PLS aims to separate variables into "predictive" (relevant to Y) and "orthogonal" (irrelevant noise) components. This Pine Script indicator provides a simplified proxy of the relevance score derived from O-PLS principles.
Purpose of the Indicator
The primary purpose of this indicator is to identify which technical factors (such as price, volume, and other indicators) have the strongest relationship with the future price movement of the current trading instrument. By providing a "relevance score" for each input variable, it helps traders focus on the most influential data points, potentially leading to more informed trading decisions.
Inputs
The indicator offers the following user-definable inputs:
* **Lookback Period:** This integer input (default: 100, min: 10, max: 500) determines the number of past bars used to calculate the relevance scores for each variable. A longer lookback period considers more historical data, which can lead to smoother, less reactive scores but might miss recent shifts in variable importance.
* **External Asset Symbol:** This symbol input (default: `BINANCE:BTCUSDT`) allows you to specify an external asset (e.g., `BINANCE:ETHUSDT`, `NASDAQ:TSLA`) whose close price will be included in the analysis as an additional variable. This is useful for cross-market analysis to see how other assets influence the current chart.
* **Plot Visibility Checkboxes (e.g., "Plot: Open Price Relevance", "Plot: Volume Relevance", etc.):** These boolean checkboxes allow you to toggle the visibility of individual relevance score plots on the chart, helping to declutter the display and focus on specific variables.
Outputs
The indicator provides two main types of output:
Relevance Score Plots: These are lines plotted in a separate pane below the main price chart. Each line corresponds to a specific market variable (Open Price, Close Price, High Price, Low Price, Volume, various RSIs, SMAs, MFI, and the External Asset Close). The value of each line represents the calculated "relevance score" for that variable, typically scaled between 0 and 10. A higher score indicates a stronger predictive relationship with the future close price.
Sorted Relevance Table : A table displayed in the top-right corner of the chart provides a clear, sorted list of all analyzed variables and their corresponding relevance scores. The table is sorted in descending order of relevance, making it easy to identify the most influential factors at a glance. Each variable name in the table is colored according to its plot color, and the external asset's name is dynamically displayed without the "BINANCE:" prefix.
How to Use the Indicator
1. **Add to Chart:** Apply the "Orthogonal Projections to Latent Structures (O-PLS)" indicator to your desired trading chart (e.g., ETH/USDT).
2. **Adjust Inputs:**
* **Lookback Period:** Experiment with different lookback periods to see how the relevance scores change. A shorter period might highlight recent correlations, while a longer one might show more fundamental relationships.
* **External Asset Symbol:** If you trade BTC/USDT, you might add ETH/USDT or SPX as an external asset to see its influence.
3. **Analyze Relevance Scores:**
* **Plots:** Observe the individual relevance score plots over time. Are certain variables consistently high? Do scores change before significant price moves?
* **Table:** Refer to the sorted table on the latest confirmed bar to quickly identify the top-ranked variables.
4. **Incorporate into Strategy:** Use the insights from the relevance scores to:
* Prioritize certain indicators or price actions in your trading strategy. For example, if "Volume" has a high relevance score, it suggests volume confirmation is critical for future price moves.
* Understand the influence of inter-market relationships (via the External Asset Close).
How the Indicator Works
The indicator works by performing the following steps on each bar:
1. **Data Fetching:** It gathers historical data for various price components (open, high, low, close), volume, and calculated technical indicators (SMA, RSI, MFI) for the specified `lookback` period. It also fetches the close price of an `External Asset Symbol` .
2. **Standardization (Z-scoring):** All collected raw data series are standardized by converting them into Z-scores. This involves subtracting the mean of each series and dividing by its standard deviation . Standardization is crucial because it brings all variables to a common scale, preventing variables with larger absolute values from disproportionately influencing the correlation calculations.
3. **Correlation Calculation (Proxy for O-PLS Relevance):** The indicator then calculates a simplified form of correlation between each standardized input variable and the standardized future close price (Y variable) . This correlation is a proxy for the relevance that O-PLS would identify. A high absolute correlation indicates a strong linear relationship.
4. **Relevance Scaling:** The calculated correlation values are then scaled to a range of 0 to 10 to provide an easily interpretable "relevance score" .
5. **Output Display:** The relevance scores are presented both as time-series plots (allowing observation of changes over time) and in a real-time sorted table (for quick identification of top factors on the current bar) .
How it Differs from Full O-PLS
This indicator provides a *simplified proxy* of O-PLS principles rather than a full, mathematically rigorous O-PLS model. Here's why and how it differs:
* **Dimensionality Reduction:** A full O-PLS model would involve complex matrix factorization techniques to decompose the independent variables (X) into components that are predictive of Y and components that are orthogonal (unrelated) to Y but still describe X's variance. Pine Script's array capabilities and computational limits make direct implementation of these matrix operations challenging.
* **Orthogonal Components:** A true O-PLS model explicitly identifies and removes orthogonal components (noise) from the X data that are unrelated to Y. This indicator, in its simplified form, primarily focuses on the direct correlation (relevance) between each X variable and Y after standardization, without explicitly modeling and separating these orthogonal variations.
* **Predictive Model:** A full O-PLS model is ultimately a predictive model that can be used for regression (predicting Y). This indicator, however, focuses solely on **identifying the relevance/correlation of inputs to Y**, rather than building a predictive model for Y itself. It's more of an analytical tool for feature importance than a direct prediction engine.
* **Computational Intensity:** Full O-PLS involves Singular Value Decomposition (SVD) or Partial Least Squares (PLS) algorithms, which are computationally intensive. The indicator uses simpler statistical measures (mean, standard deviation, and direct correlation calculation over a lookback window) that are feasible within Pine Script's execution limits.
In essence, this Pine Script indicator serves as a practical tool for gaining insights into variable relevance, inspired by the spirit of O-PLS, but adapted for the constraints and common use cases of a TradingView environment.
Polaris Trend All-in-One📘 Polaris Trend Indicator: Trading Rules & Strategy
Guide
The Polaris Trend Indicator is designed to simplify trading decisions by identifying key entry
and exit signals without the need for excessive technical analysis. This system combines the
Polaris Trend with the Polaris Golden Wave and Market Bias tools to give you confidence
across multiple timeframes.
This guide outlines clear trading rules for two use cases:
● Swing Trading
● Long-Term Investing and Holding
⚡ Swing Trading Strategy
Swing trading can be challenging when the market direction is unclear. The Polaris Trend helps
traders stay on the right side of momentum with straightforward visual signals. This approach is
best used on the Daily or Weekly chart.
✅ Entry Criteria (Bullish Trades)
● A solid green column appears above the zero line.
● A green upward arrow confirms bullish momentum.
● Enter your trade immediately when the green column first appears.
● Hold the trade until a red column appears, signaling a shift in momentum.
🚫 Exit Criteria (Bullish Trades)
● The first appearance of a red column after a green run.
● Multiple green columns followed by a red column.
● Do not enter trades mid-trend; always enter on the first green flip.
***Recommended Swing Strategy
● When a new daily green column appears but the weekly columns are still red, stay
nimble. Enter your position when the Polaris Trend Indicator turns green and displays an
upward-pointing arrow.
● If the price pulls back to a higher low but a red daily column forms, sell 50% of your
position and move your stop loss to your original entry. Then, wait for the next daily
green column and arrow to reappear, this is your signal to reenter the 50% you exited.
● If the price continues to rise and the weekly columns also turn green, shift your focus
to the weekly chart. Ignore daily signals and hold the trade until the weekly column
turns red, which will be your cue to exit. The weekly green column is your confirmation of
a stronger uptrend and a potential longer hold.
🔻 Entry Criteria (Bearish Trades)
● A solid red column appears below the zero line.
● A red downward arrow confirms bearish momentum.
● Enter your short trade immediately when the red column first appears.
● Hold until a green column appears, indicating momentum has shifted.
🔁 Exit Criteria (Bearish Trades)
● The first green column that follows a red sequence.
● Same rule applies: enter only on the initial flip, not mid-trend.
Note: The first color flip is the most reliable entry point. Avoid entering positions
deep into a trend, wait for the clear signal from Polaris.
🧭 Long-Term Investing Strategy
This approach combines the Polaris Golden Wave, Polaris Trend, and Market Bias to help
long-term investors buy at deep value levels and scale into positions over time.
📉 Ideal Entry: Golden Zone + Polaris Trend Signal
● Use the Golden Wave to identify the monthly 0.618–0.826 retracement zone
(significant discount levels).
● When price enters the Golden Zone and the Polaris Trend shows a green column on
the Daily or Weekly, this is your optimal entry point.
● If the trend turns red inside the zone, consider trimming positions and re-entering on the
next bullish signal.
If price drops below the Golden Zone, the stock becomes even more undervalued,
wait for the next green Polaris Trend signal to enter.
💰 Secondary Entry: Market Bias Rebounds
● If you miss the Golden Zone entry or are dollar-cost averaging:
○ Use the Market Bias on a Weekly timeframe.
○ Wait for price to retrace into the Market Bias band after moving higher.
○ Look for a red Polaris Trend column, then wait for price to enter the Market
Bias band and once it enters, wait for Polaris Trend signal to flip back to green
for your entry. If the trend turns red inside the zone, consider trimming positions
and re-entering on the next bullish signal.
Think of the Market Bias like a lake and price like a skipping stone—you want to
buy when the stone comes down and touches the surface.
📊 Indicator Explanations
🔶 Golden Wave (Monthly Fibonacci Retracement Zones)
● Highlights key monthly retracement zones (0.618 to 0.826).
● Helps identify deep-value entries on longer timeframes.
● Visible across all chart timeframes for consistent macro reference.
🔴 Market Bias (Smoothed Heikin-Ashi Trend Filter)
● Measures trend direction and strength using smoothed Heikin-Ashi candles and
oscillation logic.
● Customizable smoothing, oscillator period, and timeframe inputs.
● Option to display trend signals in a separate pane with dynamic coloring.
This combined approach empowers traders to make high-quality decisions with clarity and
discipline. Whether you're entering short-term swings or building long-term positions, the
Polaris Trend system guides you with timely, data-driven signals.
Eliora Gold 1min (Heikin Ashi)Eliora -focused trading strategy designed for anything on the 1-minute timeframe using Heikin Ashi candles. This mode combines advanced market logic with structured risk management to deliver smooth, disciplined trade execution.
Key Features:
✅ Trend Confirmation – Aligns with dominant market direction for higher accuracy.
✅ ATR-Based Volatility Filter – Avoids high-risk conditions and chaotic price action.
✅ Candle Strength Logic – Filters weak setups, focusing on strong momentum.
✅ Balanced Risk/Reward – Calculates stop-loss and take-profit dynamically for consistent results.
✅ Cooldown & Overtrade Protection – Limits frequency to maintain trade quality.
This version of Eliora is built for scalpers and intraday traders seeking high-probability entries with graceful exits.
UniversalPositionCalculatorV5🚀 Universal Position Calculator v5 (with Margin-Check) 🚀
Stop using calculators and complicated Excel sheets! 🤯 With the Universal Position Calculator v5, you have the ultimate tool right on your TradingView chart to manage your position size perfectly. Whether it's Forex, Gold, or Indices – this indicator does all the work for you!
✨ What does this indicator do? ✨
This indicator is your personal risk manager. It calculates the exact lot size for your next trade based on your capital, your desired risk, and your leverage. The best part? It immediately checks if your trade is even possible with your margin and warns you if you're about to over-leverage your account! 🚦
🌟 Key Features at a Glance 🌟
Automatic Lot Calculation: Just enter your risk in percent, and the indicator calculates the perfect lot size.
Margin Check: Instantly detects if your desired position size is limited by your margin and adjusts it. No more margin calls due to oversized positions!
For All Asset Classes: Works perfectly for Forex pairs (e.g., EURUSD) and other assets like commodities (XAUUSD) or indices (GER30). 💹
Currency Conversion: Automatically converts between your account currency and the asset's currency. It doesn't matter if you trade in EUR, USD, CHF, or JPY. 💱
Interactive Lines: Simply drag and drop the Entry and Stop Loss lines directly on the chart to plan your trade. 🎯
Clear Info Panel: All important information (lot size, required margin, risk in €/$/...) is displayed cleanly and clearly on your chart.
🛠️ How to Use: It's This Easy! 🛠️
The setup is a piece of cake and done in two simple steps.
Step 1: Configure Your Setup
Go to the indicator settings and fill out the "1. Setup" section:
Asset Type: Choose Forex for currency pairs or Other for everything else (e.g., Gold, Oil, Indices).
Account Currency: Enter the currency of your trading account (e.g., USD).
Account Capital: Enter your current account capital.
Risk in % per Trade: How much of your capital do you want to risk per trade? (e.g., 1.0 for 1%).
Leverage: Enter your account's leverage (e.g., 30 for 30:1).
Contract Size for 'Other': IMPORTANT! Only for the Other type. For Gold (XAUUSD), this is often 100; for the DAX (GER30), it's often 1 or 25. Check your broker's specifications for this!
Step 2: Plan Your Trade
Now for the fun part in the "2. Trade Control" section:
Entry Line (Blue Line): Click on the blue line and drag it to your desired entry level. You can also enter the value manually in the settings.
Stop Loss Line (Red Line): Click on the red line and drag it to your stop-loss level.
Step 3: Read the Results
As soon as you've set your Entry and Stop Loss, the Info Panel in the top-right corner will instantly show you the results:
Correct Lot Size: This is the lot size you need to enter with your broker for this trade.
⚠️ Heads up: If it says "Lot Size (Margin Limited!)" in orange, it means your desired risk was too high for your leverage. The indicator has automatically reduced the lot size to the maximum possible to avoid a margin call.
Required Margin: This is how much capital will be blocked on your account as a security deposit (margin) for this trade.
Risk in : The exact amount of money you will lose if your stop loss is triggered.
With this tool, you can make disciplined and mathematically sound trading decisions. Good luck and Happy Trading! 📈💰
LiliALHUNTERSystem_v2📚 **Library: LiliALHUNTERSystem_v2**
This library provides a powerful target management system for Pine Script developers.
It includes advanced calculators for EMA, RMA, and Supertrend, and introduces a central `createTargets()` function to dynamically render target lines and labels based on long/short trade logic.
🛠️ **Main Features:**
– Dynamic horizontal & vertical target lines
– Dual target configuration (Target 1 & Target 2)
– Directional logic via `isLong1`, `isLong2`
– Integrated Supertrend validation
– Visual dashboard and label display
– Works seamlessly with custom indicators
🎯 **Purpose:**
The `LiliALHUNTERSystem_v2` Library enables Pine coders to manage and visualize targets consistently across all trading strategies and indicators. It simplifies target logic while maintaining visual clarity and modular usage.
⚠️ **Disclaimer:**
This script is intended for educational and analytical purposes only. It does not constitute financial advice.
Library "LiliALHUNTERSystem_v2"
ema_calc(len, source)
Parameters:
len (simple int)
source (float)
rma_calc(len, source)
Parameters:
len (simple int)
source (float)
supertrend_calc(length, factor)
Parameters:
length (simple int)
factor (float)
createTargets(config, state, source1A, source1B, source2A, source2B)
Parameters:
config (TargetConfig)
state (TargetState)
source1A (float)
source1B (float)
source2A (float)
source2B (float)
showDashboard(state, dashLoc, textSize)
Parameters:
state (TargetState)
dashLoc (string)
textSize (string)
TargetConfig
Fields:
enableTarget1 (series bool)
enableTarget2 (series bool)
isLong1 (series bool)
isLong2 (series bool)
target1Condition (series string)
target2Condition (series string)
target1Color (series color)
target2Color (series color)
target1Style (series string)
target2Style (series string)
distTarget1 (series float)
distTarget2 (series float)
distOptions1 (series string)
distOptions2 (series string)
showLabels (series bool)
showDash (series bool)
TargetState
Fields:
target1LineV (series line)
target1LineH (series line)
target2LineV (series line)
target2LineH (series line)
target1Lbl (series label)
target2Lbl (series label)
target1Active (series bool)
target2Active (series bool)
target1Value (series float)
target2Value (series float)
countTargets1 (series int)
countTgReached1 (series int)
countTargets2 (series int)
countTgReached2 (series int)
order flow buy/sell and profundity OrderBook Buy/Sell Flow & Polarity Indicator
This powerful indicator provides a detailed look into the market's internal dynamics by visualizing Order Flow (Tape/Time & Sales) and Price Polarity directly on your chart, all within a clean, customizable table. Understand real-time buying and selling pressure and gain insights into who's in control of the candle.
Key Features:
Real-time Order Flow (Tape/Time & Sales): Tracks individual "ticks" (price and volume updates) within the current bar, allowing you to see the immediate impact of buy and sell orders.
Dynamic Table Display: All data is presented in an intuitive, customizable table that can be positioned anywhere on your chart.
Aggregated Buy/Sell Volume: Clearly distinguishes between volume driven by buying (price moving up on a tick) and selling (price moving down on a tick).
"Rocket" Order Detection: Highlights unusually large buy or sell orders based on configurable thresholds (in BTC Millions for major cryptos, and Thousands/Millions for others), helping you spot significant institutional or whale activity.
Candle Polarity Section: A dedicated area in the table that shows the percentage of buying vs. selling volume for the entire current candle. The central cell dynamically blends between bullish (green) and bearish (red) colors, visually representing the dominant polarity.
Customizable Aesthetics: Full control over table colors, text colors, font sizes, and individual label colors to match your chart's theme.
Lightweight & Efficient: Designed to run smoothly without significant impact on your chart's performance.
Why Use This Indicator?
Most indicators only show you the result of price action. The "OrderBook Buy/Sell Flow & Polarity" indicator goes deeper, showing you the cause behind the price movement. By understanding the immediate order flow and the underlying buy/sell pressure within each candle, you can:
Identify accumulation or distribution: Spot when smart money might be entering or exiting positions.
Confirm breakouts/breakdowns: See if there's genuine volume behind price moves.
Gauge market sentiment in real-time: Quickly assess who is more aggressive – buyers or sellers.
Improve entry and exit points: Make more informed decisions based on live market activity.
Settings & Customization:
The indicator comes with a comprehensive set of input options, allowing you to fine-tune its appearance and functionality:
Table Position: Choose from various chart locations (Top/Middle/Bottom, Left/Center/Right).
Window Size (Order Flow): Adjust how many recent order flow "ticks" are displayed.
Colors: Personalize all table, text, and label colors.
Rocket Thresholds: Define the volume levels for "rocket" order detection based on asset type.
Polarity Section Toggle: Enable or disable the real-time candle polarity display.
Note: This indicator provides insights based on available real-time tick data from TradingView. While it simulates aspects of order book and tape reading, it is important to remember that direct access to full exchange Level 2 data is not available on TradingView.
Disclaimer: This indicator is for informational purposes only and should not be considered financial advice. Trading involves risk, and past performance is not indicative of future results.
[Teyo69] T1 ATR Standard Deviation Breakout Bands🧭 OVERVIEW
T1 ATR Standard Deviation Breakout Bands is a breakout tool designed to detect volatility-driven price expansion beyond statistically significant zones. It calculates real-time ATR-based standard deviation bands, dynamically tracking breakout conditions with adjustable smoothing. With flexible moving average types and the Kijun-sen as the default baseline, this indicator is built for traders who want to avoid fakeouts and only engage when volatility confirms conviction.
✨ FEATURES
Utilizes ATR standard deviation for real-time volatility band calculations
Supports multiple moving average types (EMA, SMA, WMA, etc.) including Kijun-sen by default
Adjustable ATR multiplier to fine-tune breakout sensitivity
Fully configurable length inputs and MA source types
Identifies long opportunities when price closes above the upper band
Identifies short opportunities when price closes below the lower band
Ideal for trend continuation, momentum breakouts, and volatility-based filtering
🎯 HOW TO USE
Apply the indicator on your preferred timeframe (works best on trending conditions).
Set your baseline MA to match your system (default: Kijun-sen).
Adjust the ATR period and multiplier to balance sensitivity vs. noise.
Go long when the close breaks above the upper standard deviation band.
Go short when the close breaks below the lower standard deviation band.
Use Markers signals to highlight breakout moments.
Can also be used to identify if price is ranging when it is in the gray area of the indicator
⚙️ CONFIGURATION
Length: Period for the moving average and ATR
MA Type: Choose from EMA, SMA, WMA, or Kijun-sen
ATR Multiplier: Controls how wide the breakout bands are
Source: Price type used for calculations (default: close)
⚠️ LIMITATIONS
Standard deviation assumes price is statistically normal — not always true during news spikes
Band expansion does not guarantee follow-through — use in conjunction with volume or trend filters
💡 ADVANCED TIPS
Combine with a trend filter (e.g., 200 EMA) to trade only in the direction of the dominant trend
Use wider ATR multipliers on lower timeframes to reduce noise
Pair with oscillators (e.g., RSI, MACD) for breakout + momentum confluence setups
For scalping, reduce the length but widen the multiplier slightly
📓 NOTES
The standard deviation of ATR is used to capture how volatile volatility itself is. This reveals when the market is entering statistically significant price expansion.
Why this matters: Standard deviation is a core statistical tool for understanding distribution outliers. When price exceeds the upper band, it is outside normal volatility expectations — signaling potential breakout strength.
This indicator applies breakout theory to volatility, not just price action, offering a unique edge over classic Bollinger or Keltner bands.
ZScore Plot with Ranked TableVersion 0.1
ZScore Plot with Ranked Table — Overview
This indicator visualizes the rolling ZScores of up to 10 crypto assets, giving traders a normalized view of log return deviations over time. It's designed for volatility analysis, anomaly detection, and clustering of asset behavior.
🎯 Purpose
• Show how each asset's performance deviates from its historical mean
• Identify potential overbought/oversold conditions across assets
• Provide a ranked leaderboard to compare asset behavior instantly
⚙️ Inputs
• Lookback: Number of bars to calculate mean and standard deviation
• Asset 1–10: Choose up to 10 symbols (e.g. BTCUSDT, ETHUSDT)
📈 Outputs
• ZScore Lines: Each asset plotted on a normalized scale (mean = 0, SD = 1)
• End-of-Line Labels: Asset names displayed at latest bar
• Leaderboard Table: Ranked list (top-right) showing:
◦ Asset name (color-matched)
◦ Final ZScore (rounded to 3 decimals)
🧠 Use Cases
• Quantitative traders seeking cross-asset momentum snapshots
• Signal engineers tracking volatility clusters
• Risk managers monitoring outliers and systemic shifts
Z-Score Multi-Model ClusteringA price/volume clustering framework combining three market behavior models into a single indicator. Designed to help identify emerging trend strength, turning points, and volatility-driven entries or exits.
🔍 How It Works
This indicator classifies market states by comparing normalized price/volume behavior (via Z-Score) to different types of statistical or geometric "cluster centers." You can choose from three clustering approaches:
🧠 Clustering Models
1. Percentile (Z+CVD) – Trend Momentum Bias
Uses volume Z-Score + Cumulative Volume Delta (CVD).
Detects institutional pressure by clustering volume surges with directional delta.
Best for: Breakouts, momentum trades, volume-led reversals.
Cluster Colors:
🔹 Green triangle = Strong bullish confluence
🔻 Red triangle = Bearish divergence (bull trap risk)
⚪ Gray = Neutral/low conviction
2. Euclidean (Z+Slope) – Swing Mean-Reversion
Measures the angle of recent Z-score slope and compares it to directional cluster centers.
Helps detect early directional shifts or exhaustion.
Best for: Swing entries, pullback setups, exit timing
3. Hilbert Phase – Turn Detection via Signal Phase
Applies Hilbert Transform to the Z-Score, measuring the phase difference between trend and oscillator components.
Ideal for anticipating turns or detecting cyclical inflection points.
Useful for: Scalping, top/bottom spotting, volatility fades
✅ Features
Auto-updating cluster logic based on current data
Tooltips and clean user interface
Optional cluster bar coloring (can be toggled off)
Signal-only plotting keeps candlesticks readable
Clear entry/exit logic with triangle markers
Supports trend, swing, and oscillation-based systems
🛠️ Suggested Use Cases
Combine with VWAP, Session High/Low, or Liquidity Zones to confirm entry conditions.
Use Cluster 2 (strong bullish) on pullbacks to trend structure for add-on entries.
Use Cluster 1 in strong trends to watch for potential traps or exits.
Toggle models based on your strategy: e.g., Hilbert for scalping, Percentile for macro trend breaks.
🧪 Best Timeframes
Works across all markets and timeframes
For Percentile (Z+CVD), use intraday TF with 1m–5m CVD source
Hilbert and Euclidean preferred on 5m–1h for accurate slope/phase signals
⚠️ Notes
Clusters do not generate trade signals alone; use them in context with structure, VWAP, or trend filters.
Marker signals are filtered with a magnitude threshold to reduce noise.
Multi-Crypto Principal Component AnalysisVersion 0.2
## 📌 Multi-Crypto Principal Component Analysis (PCA) — Indicator Summary
### 🎯 Purpose
This indicator identifies **cryptocurrency assets that are behaving differently** from the rest of the market, using a simplified approach inspired by Principal Component Analysis (PCA). It’s designed to help traders spot **cross-market divergences**, detect outliers, and improve asset selection and correlation-based strategies.
### ⚙️ How It Works
The indicator analyzes the **log returns** of up to 7 user-defined assets over a configurable lookback period (default: 100 bars). It computes the **z-score** (standardized deviation) for each asset’s return series and compares it against the average behavior of the group.
If an asset’s behavior deviates significantly (beyond a threshold of 1.5 standard deviations), it’s flagged as an **outlier**.
- Each outlier is plotted as a **colored dot horizontally spaced** above the price bar
- Up to **3 dots per bar** are shown for visual clarity
This PCA-style detection works in real time, directly on the chart, and gives you a quick overview of which assets are breaking correlation.
### 🔧 Inputs
- 🕒 **Lookback Period**: Number of bars to analyze (default: 100)
- 🔢 **Assets 1–7**: Choose any 7 crypto symbols from any exchange
- 🎨 **Colors**: Predefined per asset (e.g. BTCUSDT = red, ETHUSDT = yellow)
- 📈 **Threshold**: Internal (1.5 std dev); adjustable in code if needed
### 📊 Outputs
- 🟢 Dots above candles representing assets that are acting as outliers
- 🧠 Real-time clustering insight based on statistical deviation
- 🧭 Spatially spaced dots to avoid visual overlap when multiple outliers appear
### ⚠️ Limitations
- This is a **PCA-inspired approximation**, not true matrix-based PCA
- It does **not compute principal components or eigenvectors**
- Sensitivity may vary with asset volatility or sparse trading data
- Real PCA requires external tools like Python or R for full dimensional analysis
This tool is ideal for traders who want real-time crypto correlation insights without needing external data science platforms. It’s lightweight, fast, and highly visual — and gives you a powerful lens into market dislocations across multiple assets.
M2 Global G13 Liquidity (Custom & Shift, US DXY Adj.)🌎 M2 Global G13 Liquidity index (Custom & Shift, US DXY Adj.)
💡 Indicator Overview
The M2 Global G13 Liquidity indicator combines the M2 liquidity of 13 major countries, allowing users to selectively include or exclude each country to visualize global capital flows and potential investment liquidity at a glance.
Each country's M2 data is converted to USD using real-time exchange rates, and the US M2 is further adjusted using the Dollar Index (DXY) to reflect the impact of dollar strength or weakness on US liquidity.
✅ What is M2?
M2 is a broad measure of money supply that includes cash, demand deposits, savings deposits, and certain financial products.
It represents a country's overall liquidity and capital supply and is often interpreted as "dry powder" ready to be deployed into various assets such as equities, real estate, and bonds.
Therefore, M2 serves as a crucial benchmark for assessing a country's potential investment capacity that can flow into markets at any time.
💰 Exchange Rate & Dollar Index Adjustment
- All country M2 data is converted from local currencies to USD.
- The US M2 is further adjusted using the Dollar Index (DXY) to better reflect its real global power:
- DXY > 100 → Liquidity contraction (strong dollar effect)
- DXY < 100 → Liquidity expansion (weak dollar effect)
🗺️ Country Selection Options
- Default selection: United States
- Major selections: China, Eurozone, Japan, United Kingdom (core G5 economies)
- Additional selections: Switzerland, Canada, India, Russia, Brazil, South Korea, Mexico, South Africa
- Users can freely add or remove countries to customize the indicator to match their analytical needs.
📈 Example Use Cases
- Monitor global capital flows: Track worldwide liquidity trends and detect potential market risk signals.
- Analyze exchange rate and monetary policy trends: Compare dollar strength with major central bank policies.
- Benchmark against equity indices: Evaluate correlations with MSCI World, KOSPI, NASDAQ, etc.
- Valuation analysis: Compare overall liquidity levels to equity index prices or market capitalization to assess relative valuation and identify potential overvaluation or undervaluation.
- Crisis response strategy: Identify liquidity contraction during global credit crises or deleveraging phases.
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🌎 M2 글로벌 G13 유동성 지수 (Custom & Shift, US DXY Adj.)
💡 지표 소개
M2 Global G13 Liquidity 지표는 세계 13개 주요국의 M2 유동성을 선택적으로 결합하여, 글로벌 자금 흐름과 잠재 투자 자금을 한눈에 시각화할 수 있도록 설계된 종합 유동성 지표입니다.
국가별 M2 데이터를 환율과 결합해 달러 기준으로 표준화하며, 특히 미국 M2는 달러지수(DXY)로 보정하여 달러 강약에 따른 파급력을 반영합니다.
✅ M2란?
M2는 광의 통화지표로, 현금 + 요구불 예금 + 저축성 예금 + 일부 금융상품을 포함합니다.
이는 한 국가의 유동성 수준과 자금 공급 상태를 나타내는 핵심 거시경제 지표이며, **주식·부동산·채권 등 다양한 자산에 투자될 준비가 된 '대기자금'**으로도 해석됩니다.
따라서 M2는 투자시장으로 언제든지 흘러들어갈 수 있는 잠재적 투자 역량을 평가할 때 중요한 기준입니다.
💰 환율 및 달러지수 보정
- 모든 국가 M2는 자국 통화에서 **달러(USD)**로 환산됩니다.
- 특히 미국 M2는 달러 가치의 글로벌 실질 파워를 평가하기 위해 DXY 보정을 적용합니다.
- DXY > 100 → 유동성 축소 (강달러 효과)
- DXY < 100 → 유동성 확대 (약달러 효과)
🗺️ 국가별 선택 옵션
- 기본 선택: 미국
- 주요 선택: 중국, 유로존, 일본, 영국 (주요 G5)
- 추가 선택: 스위스, 캐나다, 인도, 러시아, 브라질, 한국, 멕시코, 남아공
- 사용자는 각 국가를 자유롭게 더하거나 빼면서 커스터마이즈할 수 있습니다.
📈 활용 예시
- 글로벌 자금 흐름 모니터링: 전세계 유동성 추세 및 시장 리스크 신호 분석
- 환율/금리 정책 분석: 달러 강약과 주요국 정책 변화 비교
- 주가지수 벤치마크 비교: MSCI World, 코스피, 나스닥 등과 상관관계 확인
- 밸류에이션 분석: 전체 유동성 수준을 주가지수나 시가총액과 비교하여, 시장의 상대적 고평가·저평가 여부를 평가
- 위기 대응 전략: 글로벌 신용위기·자금 긴축 국면 대비
3D Surface Modeling [PhenLabs]📊 3D Surface Modeling
Version: PineScript™ v6
📌 Description
The 3D Surface Modeling indicator revolutionizes technical analysis by generating three-dimensional visualizations of multiple technical indicators across various timeframes. This advanced analytical tool processes and renders complex indicator data through a sophisticated matrix-based calculation system, creating an intuitive 3D surface representation of market dynamics.
The indicator employs array-based computations to simultaneously analyze multiple instances of selected technical indicators, mapping their behavior patterns across different temporal dimensions. This unique approach enables traders to identify complex market patterns and relationships that may be invisible in traditional 2D charts.
🚀 Points of Innovation
Matrix-Based Computation Engine: Processes up to 500 concurrent indicator calculations in real-time
Dynamic 3D Rendering System: Creates depth perception through sophisticated line arrays and color gradients
Multi-Indicator Integration: Seamlessly combines VWAP, Hurst, RSI, Stochastic, CCI, MFI, and Fractal Dimension analyses
Adaptive Scaling Algorithm: Automatically adjusts visualization parameters based on indicator type and market conditions
🔧 Core Components
Indicator Processing Module: Handles real-time calculation of multiple technical indicators using array-based mathematics
3D Visualization Engine: Converts indicator data into three-dimensional surfaces using line arrays and color mapping
Dynamic Scaling System: Implements custom normalization algorithms for different indicator types
Color Gradient Generator: Creates depth perception through programmatic color transitions
🔥 Key Features
Multi-Indicator Support: Comprehensive analysis across seven different technical indicators
Customizable Visualization: User-defined color schemes and line width parameters
Real-time Processing: Continuous calculation and rendering of 3D surfaces
Cross-Timeframe Analysis: Simultaneous visualization of indicator behavior across multiple periods
🎨 Visualization
Surface Plot: Three-dimensional representation using up to 500 lines with dynamic color gradients
Depth Indicators: Color intensity variations showing indicator value magnitude
Pattern Recognition: Visual identification of market structures across multiple timeframes
📖 Usage Guidelines
Indicator Selection
Type: VWAP, Hurst, RSI, Stochastic, CCI, MFI, Fractal Dimension
Default: VWAP
Starting Length: Minimum 5 periods
Default: 10
Step Size: Interval between calculations
Range: 1-10
Visualization Parameters
Color Scheme: Green, Red, Blue options
Line Width: 1-5 pixels
Surface Resolution: Up to 500 lines
✅ Best Use Cases
Multi-timeframe market analysis
Pattern recognition across different technical indicators
Trend strength assessment through 3D visualization
Market behavior study across multiple periods
⚠️ Limitations
High computational resource requirements
Maximum 500 line restriction
Requires substantial historical data
Complex visualization learning curve
🔬 How It Works
1. Data Processing:
Calculates selected indicator values across multiple timeframes
Stores results in multi-dimensional arrays
Applies custom scaling algorithms
2. Visualization Generation:
Creates line arrays for 3D surface representation
Applies color gradients based on value magnitude
Renders real-time updates to surface plot
3. Display Integration:
Synchronizes with chart timeframe
Updates surface plot dynamically
Maintains visual consistency across updates
🌟 Credits:
Inspired by LonesomeTheBlue (modified for multiple indicator types with scaling fixes and additional unique mappings)
💡 Note:
Optimal performance requires sufficient computing resources and historical data. Users should start with default settings and gradually adjust parameters based on their analysis requirements and system capabilities.
Average Daily % Change by Weekday📊 Average Daily % Change by Weekday
This script calculates and displays the average daily percentage change for each weekday (Monday through Sunday) based on historical price data. It helps traders analyze which days tend to be bullish or bearish over a selected backtest date range.
✅ Features:
Customizable date range (From Year/Month/Day to To Year/Month/Day)
Calculates average % change for each weekday (Mon–Sun)
Supports assets that trade 7 days (e.g., crypto)
Color-coded outputs (green = positive, red = negative)
Final results shown as a table in the bottom-right corner
Works only on the 1D timeframe (daily)
🧠 How it works:
For each day within the selected date range:
The script calculates the % change as: (Close - Open) / Open * 100
Then, it groups the data by weekday and averages the values
This gives you insight into how each day of the week behaves historically for the current asset.
⚠️ Notes:
This script only works on daily (1D) timeframes.
For most accurate results, use it on assets with long trading history (e.g., BTCUSD).
Designed for educational and statistical analysis purposes.
NQ Hourly Standard Deviation ZonesNQ Hourly Standard Deviation ZonesDescriptionThe NQ Hourly Standard Deviation Zones indicator is designed for traders analyzing the NASDAQ 100 futures (NQ) on an hourly timeframe. It plots dynamic support and resistance zones based on historical standard deviation (SD) levels calculated from the hourly open price. These zones represent the expected price range for each hour of the trading day, offering insights into potential price targets, reversals, or breakout levels. The indicator is highly customizable, allowing users to adjust the data period, display settings, and visual preferences to suit their trading style.The indicator calculates and displays:
• 0.5 SD Zones: Representing the price levels one-half standard deviation above and below the hourly open.
• 1.0 SD Zones: Representing the price levels one standard deviation above and below the hourly open.
• Hourly Open Line: A reference line marking the hourly open price.
These zones are derived from pre-calculated standard deviation data for the high and low price movements relative to the hourly open, segmented by each hour of the day (0–23). Users can select from multiple historical data periods (3 months to 17+ years) to align the zones with their preferred lookback period, accommodating both short-term and long-term trading strategies.Key Features
• Customizable Data Periods: Choose from 3 months, 6 months, 9 months, 1 year, 2 years, 3 years, 4 years, 5 years, 10 years, 15 years, or 17+ years of historical data to calculate standard deviation zones.
• RTH Filter: Option to display zones only during Regular Trading Hours (RTH, 9:00–15:59, America/New_York timezone) for traders focusing on the main trading session.
• Visual Customization:
• Toggle visibility of 0.5 SD and 1.0 SD labels.
• Customize line styles (Solid, Dotted, Dashed) and colors for 0.5 SD and 1.0 SD lines.
• Enable or disable shaded fills between the 0.5 SD and 1.0 SD zones, with customizable fill color.
• Timezone Support: Aligns with user-specified timezone (default: America/New_York) for accurate hourly calculations.
• Dynamic Updates: Zones are redrawn at the start of each new hourly bar, ensuring real-time relevance.
How It WorksThe indicator uses pre-computed standard deviation values for price movements (high and low) from the hourly open, based on the selected data period. For each hour of the day:
• High Zones: The +0.5 SD and +1.0 SD levels are plotted above the hourly open price.
• Low Zones: The -0.5 SD and -1.0 SD levels are plotted below the hourly open price.
• Hourly Open: A dotted line marks the open price for reference.
• Fills: Optional shaded areas between the 0.5 SD and 1.0 SD zones highlight the expected price range.
• Labels: Optional labels display "+0.5 σ," "-0.5 σ," "+1.0 σ," "-1.0 σ," and "h.o" (hourly open) at the end of each hourly bar for clarity.
The zones are plotted as horizontal lines spanning the duration of the hour, with fills and labels updated dynamically as new hourly bars form. The indicator clears previous lines and labels at the start of each new hour to maintain a clean chart.Usage
• Intraday Trading: Use the 0.5 SD and 1.0 SD zones as dynamic support and resistance levels for identifying potential entry/exit points, reversals, or breakout opportunities.
• Range Trading: The zones help visualize the expected price range for each hour, aiding in range-bound strategies.
• Risk Management: The 1.0 SD zones represent statistically significant levels, useful for setting stop-loss or take-profit levels.
• Session Filtering: Enable the "Show RTH Only" option to focus on high-liquidity hours, ideal for day traders.
• Historical Analysis: Select different data periods to analyze how price behavior varies over short-term (e.g., 3 months) versus long-term (e.g., 17+ years) market conditions.
Settings
• Settings:
• Show RTH Only (9:00–15:59): Toggle to display zones only during Regular Trading Hours (default: true).
• Timezone: Select the timezone for accurate hourly alignment (default: America/New_York).
• Select Data Period: Choose the historical data period for standard deviation calculations (options: 3 Months, 6 Months, 9 Months, 1 Year, 2 Years, 3 Years, 4 Years, 5 Years, 10 Years, 15 Years, 17+ Years; default: 17+ Years).
• Visuals:
• Show Fill: Toggle shaded areas between 0.5 SD and 1.0 SD zones (default: true).
• Fill Color: Customize the color and transparency of the fill (default: light gray, 90% transparency).
• 0.5 SD Line: Set the color (default: gray, 50% transparency) and style (Solid, Dotted, Dashed; default: Dashed) for 0.5 SD lines.
• 1.0 SD Line: Set the color (default: gray, 0% transparency) and style (Solid, Dotted, Dashed; default: Solid) for 1.0 SD lines.
• Show 0.5 SD Labels: Toggle visibility of 0.5 SD labels (default: true) and set their text color (default: gray).
• Show 1.0 SD Labels: Toggle visibility of 1.0 SD labels (default: true) and set their text color (default: gray).
Notes
• The indicator is optimized for the NASDAQ 100 futures (NQ) on an hourly timeframe. Ensure the chart is set to a compatible timeframe (e.g., 1-hour) for accurate results.
• Standard deviation values are pre-calculated and stored for each hour of the day, based on historical data. They are not dynamically recalculated from live data, ensuring consistent performance.
• The indicator uses up to 500 lines and labels to comply with TradingView’s rendering limits, ensuring smooth operation even on extended charts.
• For best results, use on liquid instruments like NQ futures, and consider combining with other technical indicators for confirmation.
Example Use CaseA trader focusing on NQ day trading can enable "Show RTH Only" and select a 3-month data period to plot zones for the 9:00–15:59 session. During the 10:00 AM hour, if the price approaches the +1.0 SD zone, the trader might anticipate resistance and consider a short position, using the -1.0 SD zone as a potential target. Conversely, a break above the +1.0 SD zone could signal a breakout, prompting a long position.Limitations
• The indicator relies on pre-computed standard deviation values, which may not reflect real-time market volatility.
• It is designed specifically for hourly charts and may not function correctly on other timeframes.
• The RTH filter assumes a standard trading session (9:00–15:59); custom session times are not supported.
AuthorThis indicator is designed for traders seeking a statistical approach to intraday price analysis, leveraging historical volatility patterns to inform trading decisions.
Korea M2 Liquidity Index💡 Korea M2 Liquidity Index
- This indicator visualizes Korea's M2 liquidity trends, designed to help both domestic and global investors easily understand the overall money supply situation in the Korean economy.
- In particular, by comparing it with the KOSPI index, investors can assess the equity market level relative to liquidity, allowing for a more precise valuation analysis to determine whether the Korean stock market is overvalued or undervalued.
✅ What is M2?
- M2 is a broad measure of money supply, which includes cash, demand deposits, savings deposits, and certain financial products.
- It serves as a crucial macroeconomic indicator that reflects the overall liquidity and capital supply in the Korean economy.
💰 KRW and USD display options
- KRW basis: Displays the total M2 amount in Korean won (in trillion units).
- USD basis: Converts the total M2 amount into US dollars using the KRW/USD exchange rate(KRW/USD) making it useful for global investors or those analyzing in USD terms.
📊 Display style and interpretation
- Users can freely choose to display Korea’s M2 and liquidity index and turn them on or off as needed.
- The index is simplified and displayed in trillion won units, allowing for an intuitive view of long-term trends and structural changes.
- The Offset (days) feature enables temporal adjustments, making it easier to compare this indicator with other economic or financial data series.
🌏 Example use cases
- Domestic policy analysis: Analyze the correlation between Bank of Korea's monetary policy changes (base rates, liquidity injections, etc.) and M2 growth.
- FX and global capital flow analysis: Understand the relationship between KRW/USD exchange rate fluctuations and changes in domestic liquidity.
- Leading indicator for asset markets: Use it as a forward-looking signal for stock, real estate, and bond markets.
- Comparison with KOSPI index: Identify gaps between liquidity and market levels to support strategic investment decisions and evaluate market capitalization levels more precisely.
copyright @invest_hedgeway
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💡 Korea M2 Liquidity Index
- 이 지표는 대한민국의 M2 유동성 흐름을 시각화하여, 국내 및 글로벌 투자자들이 한국 경제의 자금 공급 상태를 한눈에 파악할 수 있도록 설계되었습니다.
- 특히 코스피 지수와 비교 분석함으로써 유동성 대비 주가지수 수준을 평가하고, 한국 증시의 상대적 고평가·저평가 여부를 판단해 보다 정교한 밸류에이션 분석에 활용할 수 있습니다.
✅ M2란?
- M2는 광의통화 지표로, 현금 + 요구불 예금 + 저축성 예금 + 금융상품(일부) 등을 포함하는 총 유동성을 의미합니다. 이는 한국 경제의 자금 공급 상태를 나타내는 중요한 거시경제 지표로 활용됩니다.
💰 KRW 및 USD 표시 선택
- KRW(원화) 기준: 한국 원화 기준으로 M2 총액(조 단위)을 나타냅니다.
- USD 기준: M2 총액을 환율(KRW/USD) 기준으로 달러화 환산 후 표시하여, 글로벌 투자자나 달러화 기준 평가 시 활용 가능합니다.
📊 표시 방식과 해석
- 사용자는 한국의 M2와 유동성지수를 자유롭게 선택해 원하는 방식으로 켜거나 끌 수 있습니다.
- 지표는 조원(Trillion won) 단위로 단순화해 표시되며, 장기 흐름과 추세 변화를 시각적으로 확인할 수 있습니다.
- Offset (days) 기능을 통해 시리즈를 시차 조정할 수 있어, 다른 경제 지표와의 비교 분석에 유용합니다.
🌏 활용 예시
- 국내 정책 분석: 한국은행의 통화정책 변화(기준금리, 유동성 공급 등)와 M2 증가율 간 상관성 분석.
- 환율 및 글로벌 자금 흐름 분석: 원/달러 환율 변동과 유동성 간 상관관계 파악.
- 주식, 부동산, 채권 등 자산시장 선행 지표로서 활용.
- 코스피 지수와의 비교 분석: 시장 유동성과 지수의 괴리를 파악하여 전략적 투자 판단과 시가총액 수준에 대한 평가에 활용.
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Correlation Coefficient with MA & BB中文版介紹
相關係數、移動平均線與布林帶指標 (Correlation Coefficient with MA & BB)
這個 Pine Script 指標是一款強大的工具，旨在幫助交易者和投資者深入分析兩個市場標的之間的關係強度與方向，並結合移動平均線 (MA) 和布林帶 (BB) 來進一步洞察這種關係的趨勢和波動性。
無論您是想尋找配對交易機會、管理投資組合風險，還是僅僅想更好地理解市場動態，這個指標都能提供有價值的見解。
指標特色與功能：
動態相關係數計算：
您可以選擇任何您想比較的股票、商品或加密貨幣代號（例如，預設為 GOOG）。
指標會自動計算當前圖表（主數據源，預設為收盤價）與您指定標的之間的相關係數。
相關係數值介於 -1 (完美負相關) 至 1 (完美正相關) 之間，0 表示無線性關係。
視覺化呈現相關係數線，並標示 1、0、-1 參考水平線，同時填充完美相關區間，讓您一目了然。
特別之處：程式碼中包含了 ticker.modify，確保比較標的數據考慮了股息調整或延長交易時段，使相關性分析更加精準。
相關係數的移動平均線 (MA)：
為了平滑相關係數的短期波動，指標提供了多種移動平均線類型供您選擇，包括：SMA、EMA、WMA、SMMA。
您可以設定計算 MA 的週期長度（預設 20 週期）。
這條 MA 線有助於識別相關係數的長期趨勢，判斷兩者關係是趨於增強還是減弱。
相關係數的布林帶 (BB)：
將布林帶應用於相關係數，以衡量其波動性和相對高低水平。
中軌與您選擇的移動平均線保持一致。
上軌和下軌則根據相關係數的標準差和您設定的 Z 值（預設 2.0 倍標準差）動態調整。
布林帶可以幫助您識別相關係數何時處於極端水平，可能預示著未來會回歸均值。
如何運用這個指標？
配對交易策略：當兩個通常高度相關的資產，其相關係數短期內顯著偏離平均水平（例如，一個資產價格上漲而另一個原地踏步），您可能可以考慮利用此「失衡」進行配對交易。
投資組合多元化：了解不同資產之間的相關性，有助於構建更穩健的投資組合，避免過度集中於同向變動的資產，有效分散風險。
市場趨勢洞察：透過觀察相關係數的趨勢和波動，您可以更好地理解不同市場板塊或資產類別之間的聯動性，為您的宏觀經濟分析提供數據支持。
請注意，相關性不等於因果性。使用此指標時，請結合您的整體交易策略、宏觀經濟分析以及其他技術指標進行綜合判斷。
English Version Introduction
Correlation Coefficient with Moving Average & Bollinger Bands Indicator (Correlation Coefficient with MA & BB)
This Pine Script indicator is a powerful tool designed to help traders and investors deeply analyze the strength and direction of the relationship between two market instruments. It integrates Moving Averages (MA) and Bollinger Bands (BB) to further insight into the trend and volatility of this relationship.
Whether you're looking for pair trading opportunities, managing portfolio risk, or simply aiming to better understand market dynamics, this indicator can provide valuable insights.
Indicator Features & Functionality:
Dynamic Correlation Coefficient Calculation:
You can select any symbol you wish to compare (e.g., default is GOOG), be it stocks, commodities, or cryptocurrencies.
The indicator automatically calculates the correlation coefficient between the current chart (main data source, default is close price) and your specified symbol.
Correlation values range from -1 (perfect negative correlation) to 1 (perfect positive correlation), with 0 indicating no linear relationship.
It visually plots the correlation line, marks 1, 0, -1 reference levels, and fills the perfect correlation zone for clear visualization.
Special Feature: The code includes ticker.modify, ensuring that the comparative symbol's data accounts for dividend adjustments or extended trading hours, leading to more precise correlation analysis.
Moving Average (MA) for Correlation:
To smooth out short-term fluctuations in the correlation coefficient, the indicator offers multiple MA types for you to choose from: SMA, EMA, WMA, SMMA.
You can set the length of the MA period (default 20 periods).
This MA line helps identify the long-term trend of the correlation coefficient, indicating whether the relationship between the two instruments is strengthening or weakening.
Bollinger Bands (BB) for Correlation:
Bollinger Bands are applied to the correlation coefficient itself to gauge its volatility and relative high/low levels.
The middle band aligns with your chosen Moving Average.
The upper and lower bands dynamically adjust based on the correlation coefficient's standard deviation and your set Z-score (default 2.0 standard deviations).
Bollinger Bands can help you identify when the correlation coefficient is at extreme levels, potentially signaling a future reversion to the mean.
How to Utilize This Indicator:
Pair Trading Strategies: When two typically highly correlated assets show a significant short-term deviation from their average correlation (e.g., one asset's price rises while the other stagnates), you might consider exploiting this "imbalance" for pair trading.
Portfolio Diversification: Understanding the correlation between different assets helps build a more robust investment portfolio, preventing over-concentration in co-moving assets and effectively diversifying risk.
Market Trend Insight: By observing the trend and volatility of the correlation coefficient, you can better understand the联动 (interconnectedness) between different market sectors or asset classes, providing data support for your macroeconomic analysis.
Please note that correlation does not imply causation. When using this indicator, combine it with your overall trading strategy, macroeconomic analysis, and other technical indicators for comprehensive decision-making.
Kase Convergence Divergence [BackQuant]Kase Convergence Divergence
The Kase Convergence Divergence is a sophisticated oscillator designed to measure directional market strength through the lens of volatility-adjusted log return structures. Inspired by Cynthia Kase’s work on statistical momentum and price projection ranges, this unique indicator offers a hybrid framework that merges signal processing, multi-length sweep logic, and adaptive smoothing techniques.
Unlike traditional momentum oscillators like MACD or RSI, which rely on static moving average differences, KCD introduces a dual-process system combining:
Kase-style statistical range projection (via log returns and volatility),
A sweeping loop of lookback lengths for robustness,
First and second derivative modes to capture both velocity and acceleration of price movement.
Core Logic & Computation
The KCD calculation is centered on two volatility-normalized transforms:
KSDI Up: Measures how far the current high has moved relative to a past low, normalized by return volatility.
KSDI Down: Measures how far the current low has moved relative to a past high, also normalized.
For every length in a user-defined sweep range (e.g., 25–35), both KSDI_up and KSDI_dn are computed, and their maximum values across the loop are retained. The difference between these two max values produces the raw signal:
KPO (Kase Projection Oscillator): Measures directional skew.
KCD (Kase Convergence Divergence): Defined as KPO – MA(KPO) — similar in spirit to MACD but structurally different.
Users can choose to visualize either the first derivative (KPO) , or the second derivative (KCD) , depending on market conditions or strategy style.
Key Features
✅ Multi-Length Sweep Logic: Improves signal reliability by aggregating statistical range projections across a set of lookbacks.
✅ Advanced Smoothing Modes: Supports DEMA, HMA, TEMA, LINREG, WMA and more for dynamic adaptation.
✅ Dual Derivative Modes: Choose between speed (first derivative) or smoothness (second derivative) to fit your trading regime.
✅ Color-Encoded Signal Bands: Heatmap-style oscillator coloring enhances visual feedback on trend strength.
✅ Candlestick Painting: Optional bar coloring makes it easy to spot trend shifts on the main chart.
✅ Adaptive Fill Zones: Green and red fills between the oscillator and zero line help distinguish bullish and bearish regimes at a glance.
Practical Applications
📈 Trend Confirmation: Use KCD as a secondary confirmation layer after breakout or pullback entries.
📉 Momentum Shifts: Crossover and crossunder of the zero line highlight potential regime changes.
📊 Strategy Filters: Incorporate into algos to avoid trendless or mean-reverting environments.
🧪 Derivative Switching: Flip between KPO and KCD modes depending on whether you want to measure acceleration or deceleration of price flow.
Alerts & Signals
Two built-in alerts help you catch regime shifts in real time:
Long Signal: Triggered when the selected oscillator crosses above zero.
Short Signal: Triggered when it crosses below zero.
These events can be used to generate entries, exits, or trend validation cues in multi-layer systems.
Conclusion
The Kase Convergence Divergence goes beyond traditional oscillators by offering a volatility-normalized, derivative-aware signal engine with enhanced visual dynamics. Its sweeping architecture and dynamic fill logic make it especially powerful for identifying trending environments, filtering chop, and adding statistical rigor to your trading toolkit.
Whether you’re a discretionary trader seeking precision, or a quant looking to model more robust return structures, KCD offers a creative yet analytically grounded solution.
RISK ROTATION MATRIX ║ BullVision [3.0]🔍 Overview
The Risk Rotation Matrix is a comprehensive market regime detection system that analyzes global market conditions across four critical domains: Liquidity, Macroeconomic, Crypto/Commodities, and Risk/Volatility. Through proprietary algorithms and advanced statistical analysis, it transforms 20+ diverse market metrics into a unified framework for identifying regime transitions and risk rotations.
This institutional-grade system aims to solve a fundamental challenge: how to synthesize complex, multi-domain market data into clear, actionable trading intelligence. By combining proprietary liquidity calculations with sophisticated cross-asset analysis.
The Four-Domain Architecture
1. 💧 LIQUIDITY DOMAIN
Our liquidity analysis combines standard metrics with proprietary calculations:
Proprietary Components:
Custom Global Liquidity Index (GLI): Unique formula aggregating central bank assets, credit spreads, and FX dynamics through our weighted algorithm
Federal Reserve Balance Proxy: Advanced calculation incorporating reverse repos, TGA fluctuations, and QE/QT impacts
China Liquidity Proxy: First-of-its-kind metric combining PBOC operations with FX-adjusted aggregates
Global M2 Composite: Custom multi-currency M2 aggregation with proprietary FX normalization
2. 📈 MACRO DOMAIN
Sophisticated integration of global economic indicators:
S&P 500: Momentum and trend analysis with custom z-score normalization
China Blue Chips: Asian market sentiment with correlation filtering
MBA Purchase Index: Real estate market health indicator
Emerging Markets (EEMS): Risk appetite measurement
Global ETF (URTH): Worldwide equity exposure tracking
Each metric undergoes proprietary transformation to ensure comparability and regime-specific sensitivity.
3. 🪙 CRYPTO/COMMODITIES DOMAIN
Unique cross-asset analysis combining:
Total Crypto Market Cap: Liquidity flow indicator with custom smoothing
Bitcoin SOPR: On-chain profitability analysis with adaptive periods
MVRV Z-Score: Advanced implementation with multiple MA options
BTC/Silver Ratio: Novel commodity-crypto relationship metric
Our algorithms detect when crypto markets lead or lag traditional assets, providing crucial timing signals.
4. ⚡ RISK/VOLATILITY DOMAIN
Advanced volatility regime detection through:
MOVE Index: Bond volatility with inverse correlation analysis
VVIX/VIX Ratio: Volatility-of-volatility for regime extremes
SKEW Index: Tail risk measurement with custom normalization
Credit Stress Composite: Proprietary combination of credit spreads
USDT Dominance: Crypto flight-to-safety indicator
All risk metrics are inverted and normalized to align with the unified scoring system.
🧠 Advanced Integration Methodology
Multi-Stage Processing Pipeline
Data Collection: Real-time aggregation from 20+ sources
Normalization: Custom z-score variants accounting for regime-specific volatility
Domain Scoring: Proprietary weighting within each domain
Cross-Domain Synthesis: Advanced correlation matrix between domains
Regime Detection: State-transition model identifying four market phases
Signal Generation: Composite score with adaptive smoothing
🔁 Composite Smoothing & Signal Generation
The user can apply smoothing (ALMA, EMA, etc.) to highlight trends and reduce noise. Smoothing length, type, and parameters are fully customizable for different trading styles.
🎯 Color Feedback & Market Regimes
Visual dynamics (color gradients, labels, trails, and quadrant placement) offer an at-a-glance interpretation of the market’s evolving risk environment—without forecasting or forward-looking assumptions.
🎯 The Quadrant Visualization System
Our innovative visual framework transforms complex calculations into intuitive intelligence:
Dynamic Ehlers Loop: Shows current position and momentum
Trailing History: Visual path of regime transitions
Real-Time Animation: Immediate feedback on condition changes
Multi-Layer Information: Depth through color, size, and positioning
🚀 Practical Applications
Primary Use Cases
Multi-Asset Portfolio Management: Optimize allocation across asset classes based on regime
Risk Budgeting: Adjust exposure dynamically with regime changes
Tactical Trading: Time entries/exits using regime transitions
Hedging Strategies: Implement protection before risk-off phases
Specific Trading Scenarios
Domain Divergence: When liquidity improves but risk metrics deteriorate
Early Rotation Detection: Crypto/commodity signals often lead broader markets
Volatility Regime Trades: Position for mean reversion or trend following
Cross-Asset Arbitrage: Exploit temporary dislocations between domains
⚙️ How It Works
The Composite Score Engine
The system's intelligence emerges from how it combines domains:
Each domain produces a normalized score (-2 to +2 range)
Proprietary algorithms weight domains based on market conditions
Composite score indicates overall market regime
Smoothing options (ALMA, EMA, etc.) optimize for different timeframes
Regime Classification
🟢 Risk-On (Green): Positive composite + positive momentum
🟠 Weakening (Orange): Positive composite + negative momentum
🔵 Recovery (Blue): Negative composite + positive momentum
🔴 Risk-Off (Red): Negative composite + negative momentum
Signal Interpretation Framework
The indicator provides three levels of analysis:
Composite Score: Overall market regime (-2 to +2)
Domain Scores: Identify which factors drive regime
Individual Metrics: Granular analysis of specific components
🎨 Features & Functionality
Core Components
Risk Rotation Quadrant: Primary visual interface with Ehlers loop
Data Matrix Dashboard: Real-time display of all 20+ metrics
Domain Aggregation: Separate scores for each domain
Composite Calculation: Unified score with multiple smoothing options
Customization Options
Selective Metrics: Enable/disable individual components
Period Adjustment: Optimize lookback for each metric
Smoothing Selection: 10 different MA types including ALMA
Visual Configuration: Quadrant scale, colors, trails, effects
Advanced Settings
Pre-smoothing: Reduce noise before final calculation
Adaptive Periods: Automatic adjustment during volatility
Correlation Filters: Remove redundant signals
Regime Memory: Hysteresis to prevent whipsaws
📋 Implementation Guide
Setup Process
Add to chart (optimized for daily, works on all timeframes)
Review default settings for your market focus
Adjust domain weights based on trading style
Configure visual preferences
Optimization by Trading Style
Position Trading: Longer periods (60-150), heavy smoothing
Swing Trading: Medium periods (20-60), balanced smoothing
Active Trading: Shorter periods (10-40), minimal smoothing
Best Practices
Monitor domain divergences for early signals
Use extreme readings (-1.5/+1.5) for high-conviction trades
Combine with price action for confirmation
Adjust parameters during major events (FOMC, earnings)
💎 What Makes This Unique
Beyond Traditional Indicators
Multi-Domain Integration: Only system combining liquidity, macro, crypto, and volatility
Proprietary Calculations: Custom formulas for GLI, Fed, China, and M2 proxies
Adaptive Architecture: Dynamically adjusts to market regimes
Institutional Depth: 20+ integrated metrics vs typical 3-5
Technical Innovation
Statistical Normalization: Custom z-score variants for cross-asset comparison
Correlation Management: Prevents double-counting related signals
Regime Persistence: Algorithms to identify sustainable vs temporary shifts
Visual Intelligence: Information-dense display without overwhelming
🔢 Performance Characteristics
Strengths
Early regime detection (typically 1-3 weeks ahead)
Robust across different market environments
Clear visual feedback reduces interpretation errors
Comprehensive coverage prevents blind spots
Optimal Conditions
Most effective with 100+ bars of history
Best on daily timeframe (4H minimum recommended)
Requires liquid markets for accurate signals
Performance improves with more enabled components
⚠️ Risk Considerations & Limitations
Important Disclaimers
Probabilistic system, not predictive
Requires understanding of macro relationships
Signals should complement other analysis
Past regime behavior doesn't guarantee future patterns
Known Limitations
Black swan events may cause temporary distortions
Central bank interventions can override signals
Requires active management during regime transitions
Not suitable for pure technical traders
💎 Conclusion
The Risk Rotation Matrix represents a new paradigm in market regime analysis. By combining proprietary liquidity calculations with comprehensive multi-domain monitoring, it provides institutional-grade intelligence previously available only to large funds. The system's strength lies not just in its individual components, but in how it synthesizes diverse market information into clear, actionable trading signals.
⚠️ Access & Intellectual Property Notice
This invite-only indicator contains proprietary algorithms, custom calculations, and years of quantitative research. The mathematical formulations for our liquidity proxies, cross-domain correlation matrices, and regime detection algorithms represent significant intellectual property. Access is restricted to protect these innovations and maintain their effectiveness for serious traders who understand the value of comprehensive market regime analysis.
Premium/Discount with Candle Open stats [Herman]Premium/Discount with Stats
This indicator is designed to help traders identify and analyze premium/discount zones on any timeframe while automatically tracking statistics on price behavior relative to these zones. It is especially valuable for traders looking to structure entries, manage targets, and quantify market reactions to prior session ranges.
What it draws on the chart
✅ Range High and Low Lines
For each selected timeframe period (15min, 30min 1H, 4H, Daily), the indicator plots the high and low of the completed previous period.
These lines are color-coded dynamically based on sweep detection:
If the high was swept (price broke the previous high), the high line is marked as Premium.
If the low was swept, the low line is marked as Discount.
If both were swept or neither, it uses the default color settings.
✅ Midline
An optional midline at the 50% level of the previous period’s high-low range.
Helpful for mean-reversion traders or anyone watching for retests of equilibrium.
✅ Quartile Lines (25%–75%)
Optional additional lines at 25% and 75% of the previous range, helping traders visualize inner range subdivisions.
✅ Open Price Line
Marks the open price of the previous period as a horizontal reference.
✅ Background Fills
The region between low and midline is shaded with the Discount color.
The region between high and midline is shaded with the Premium color.
These optional fills help highlight the premium and discount zones visually.
✅ Current Incomplete Period Lines (optional)
You can choose to display provisional high, low, midline, quartiles, and open for the current forming period.
These update in real-time until the period closes.
Sweep Detection Logic
The indicator automatically tracks if the current period price sweeps above the previous period’s high or below the low.
A "sweep" is simply defined as price exceeding the previous high/low while tracking is active.
The sweep status affects the colors of the premium/discount lines, helping traders see potential liquidity grabs or stop hunts.
What it counts and tracks (Statistics)
The script automatically compiles statistics over time:
✅ Total Touches
Counts how many times the price in a new period touches either the previous period’s high or low.
A “touch” is registered once per side per period.
✅ Midline Returns
Counts how often, after touching the previous high/low, price returns to the previous period’s midline.
Gives you a measure of mean-reversion success.
✅ Open Returns
Similarly, tracks how often price returns to the previous period’s open after touching the previous high/low.
✅ Return Percentages
Displays the percentage of touches that result in a return to midline or open.
These percentages are calculated live on your chart and updated after each period closes.
✅ Stats Table
A customizable on-chart table summarizing all of these stats in real-time.
Helps traders evaluate the effectiveness of range-based trading setups over time.
How it Works (Technical details)
On each new bar, the script checks if a new period (as defined by your timeframe selection) has begun.
When a new period starts, the previous period’s high, low, open, midline, quartiles are recorded and drawn on the chart.
The script then “watches” the current period:
Updates provisional high and low.
Detects sweeps of previous highs/lows.
Tracks if price returns to the previous period’s midline or open after those sweeps.
Increments statistical counters if conditions are met.
Background fills and lines update dynamically based on real-time data.
Intended Use Cases
This indicator is ideal for:
✅ Identifying premium/discount zones for swing or intraday trades.
✅ Spotting liquidity sweeps and possible manipulation zones.
✅ Structuring trades with logical, data-driven target zones (midline, open).
✅ Quantifying the probability of mean-reversion moves after liquidity events.
✅ Developing and backtesting range-based trading models with live stats.
Highly Customizable
Choose any timeframe for defining the premium/discount range.
Toggle visibility of midline, quartiles, open line, current period preview.
Full control over colors, line styles, line widths, and background shading.
Optional real-time statistical table with total counts and return percentages.
ShadowStats vs Official CPI YoY%This chart visualizes and compares the year-over-year (YoY) percentage change in the Consumer Price Index (CPI) as calculated by the U.S. government versus the alternative methodology used by ShadowStats, which reflects pre-1980 inflation measurement techniques. The red line represents ShadowStats' CPI YoY% estimates, while the blue line shows the official CPI YoY% reported by government sources. This side-by-side view highlights the divergence in reported inflation rates over time, particularly from the 1980s onward, offering a visual representation of how different calculation methods can lead to vastly different interpretations of inflation and purchasing power loss.
Trading CalculatorTrading Calculator Indicator
VIBE CODED WITH GROK 3
The Trading Calculator is a Pine Script indicator designed to perform quick and useful trading-related calculations directly on your chart. It allows traders to execute basic arithmetic operations—such as addition, subtraction, multiplication, and division—as well as calculate percent change and average using either numerical values or trading variables (e.g., close, open, high, low, volume). The indicator displays its results in a table that resembles a calculator interface, making it both functional and visually intuitive. Unlike typical indicators, it does not overlay on the price chart but instead appears in a separate pane.
Inputs
Formula (new | old): First value or variable (e.g., 100, close, close ). Example: close uses the current closing price.
Operator: Mathematical operation (e.g., Plus, Minus, Multiply). Example: Plus adds the two inputs.
Second Input: Second value or variable (e.g., 50, open, close ). Example: open uses the current opening price.
