US Macro Cycle (Z-Score Model)US Macro Cycle (Z-Score Model)
This indicator tracks the US economic cycle in real time using a weighted composite of seven macro and market-based indicators, each converted into a rolling Z-score for comparability. The model identifies the current phase of the cycle — Expansion, Peak, Contraction, or Recovery — and suggests sector tilts based on historical performance in each phase.
Core Components:
Yield Curve (10y–2y): Positive & steepening = growth; inverted = slowdown risk.
Credit Spreads (HYG/LQD): Tightening = risk-on; widening = risk-off.
Sector Leadership (Cyclicals vs. Defensives): Measures market leadership regime.
Copper/Gold Ratio: Higher copper = growth signal; higher gold = defensive.
SPY vs. 200-day MA: Equity trend strength.
SPY/IEF Ratio: Stocks vs. bonds relative strength.
VIX (Inverted): Low/falling volatility = supportive; high/rising = risk-off.
Methodology:
Each series is transformed into a rolling Z-score over the selected lookback period (optionally using median/MAD for robustness and winsorization to clip outliers).
Z-scores are combined using user-defined weights and normalized.
The smoothed composite is compared against phase thresholds to classify the macro environment.
Features:
Customizable Weights: Emphasize the indicators most relevant to your strategy.
Adjustable Thresholds: Fine-tune cycle phase definitions.
Background Coloring: Visual cue for the current phase.
Summary Table: Displays composite Z, confidence %, and individual Z-scores.
Alerts: Trigger when the phase changes, with details on the composite score and recommended tilt.
Use Cases:
Align sector rotation or relative strength strategies with the macro backdrop.
Identify favorable or defensive phases for tactical allocation.
Monitor macro turning points to manage portfolio risk.
It's doesn't fill nan gaps so there is quite a bit of zeroes, non-repainting.
Cerca negli script per "spy"
Dynamic 5DMA/EMA with Color for Multiple Products🔹 Dynamic 5DMA/EMA with Slope-Based Coloring (All Timeframes)
This indicator plots a dynamic 5-period moving average that adapts intelligently to your chart's timeframe and product type — giving you a clean, slope-sensitive visual edge across intraday, daily, and weekly views.
✅ Key Features:
📈 Dynamic MA Length Scaling:
On intraday timeframes, the MA adjusts for your selected market session (RTH, ETH, VIX, or Futures), calculating a true 5-day average based on actual session length — not just a flat bar count.
🔄 Automatic Timeframe Detection:
Daily Chart: Uses standard 5DMA or 5EMA.
Weekly Chart: Applies a true 5-week MA.
Intraday Charts: Converts 5 days into bar-length equivalent dynamically.
🎨 Color-Coded Slope Logic:
Green = Rising MA (bullish slope)
Red = Falling MA (bearish slope)
Neutral slope = previous color held for visual continuity
No more guessing — direction is instantly clear.
⚠️ Built-In Slope Flip Alerts:
Set alerts when the slope of the MA turns up or down. Ideal for timing pullback entries or exits across any product.
⚙️ Session Settings for Proper Scaling:
Choose your product's market structure to ensure accurate 5-day conversion on intraday charts:
Stocks - RTH: 390 mins/day
Stocks - ETH: 780 mins/day
VIX: 855 mins/day
Futures: 1440 mins/day
This ensures the MA reflects 5 full trading days, regardless of session irregularities or bar interval.
📌 Why Use This Indicator?
Most MAs misrepresent trend direction on intraday charts because they assume static daily bar counts. This tool corrects that, then adds slope-based coloring to give you a fast, visual read on short-term momentum. Whether you’re swing trading SPY, scalping VIX, or position trading futures, this indicator keeps your view aligned with how institutions see moving averages across timeframes.
🔧 Best For:
VIX & volatility traders
Short-term SPY/SPX traders
Swing traders who value clean setups
Anyone wanting a true 5-day trend anchor on any chart
EMA Crossover Visual Setup (RS Clásico Confirmado)Overview
This script is designed to visually highlight classic swing trading setups based on the crossover of exponential moving averages (EMAs), with additional confirmation using Relative Strength (RS) compared to a benchmark asset (e.g., SPY).
The goal is to identify bullish momentum shifts that align both with technical structure (EMA crossover) and relative outperformance, helping traders focus on strong stocks in strong markets.
Logic
A signal is triggered when the following conditions are met:
The fast EMA (e.g., 10) crosses above the slow EMA (e.g., 20).
The closing price is above a third EMA (e.g., 50) to confirm bullish structure.
The asset's Relative Strength (RS) versus a benchmark is confirmed manually, based on an RSI comparison (not calculated inside the script).
The script is meant to be used alongside manual RS confirmation, using a secondary chart or overlay of the RS ratio.
Features
Visual labels and markers for clean charting of valid entry setups
Fully customizable EMA lengths
Optional highlighting of candle patterns near entry
Ideal for use with top-down analysis and watchlist filtering
Suggested Use
Works best on daily and 4H charts for swing trading setups
Combine with volume and price action analysis for higher probability trades
Use manual RS validation: confirm that the RSI of the selected stock is stronger than the RSI of SPY (or any benchmark of your choice)
Notes
This script does not execute trades or include stop loss/take profit logic, as it is intended for discretionary traders who want to visually scan for opportunities.
It also does not calculate RS internally, allowing flexibility in how you define strength (RS line, RSI comparison, or price ratio).
Advanced Correlation Monitor📊 Advanced Correlation Monitor - Pine Script v6
🎯 What does this indicator do?
Monitors real-time correlations between 13 different asset pairs and alerts you when historically strong correlations break, indicating potential trading opportunities or changes in market dynamics.
🚀 Key Features
✨ Multi-Market Monitoring
7 Forex Pairs (GBPUSD/DXY, EURUSD/GBPUSD, etc.)
6 Index/Stock Pairs (SPY/S&P500, DAX/NASDAQ, TSLA/NVDA, etc.)
Fully configurable - change any pair from inputs
📈 Dual Correlation Analysis
Long Period (90 bars): Identifies historically strong correlations
Short Period (6 bars): Detects recent breakdowns
Pearson Correlation using Pine Script v6 native functions
🎨 Intuitive Visualization
Real-time table with 6 information columns
Color coding: Green (correlated), Red (broken), Gray (normal)
Visual states: 🟢 OK, 🔴 BROKEN, ⚫ NORMAL
🚨 Smart Alert System
Only alerts previously correlated pairs (>80% historical)
Detects breakdowns when short correlation <80%
Consolidated alert with all affected pairs
🛠️ Flexible Configuration
Adjustable Parameters:
📅 Periods: Long (30-500), Short (2-50)
🎯 Threshold: 50%-99% (default 80%)
🎨 Table: Configurable position and size
📊 Symbols: All pairs are configurable
Default Pairs:
FOREX: INDICES/STOCKS:
- GBPUSD vs DXY • SPY vs S&P500
- EURUSD vs GBPUSD • DAX vs S&P500
- EURUSD vs DXY • DAX vs NASDAQ
- USDCHF vs DXY • TSLA vs NVDA
- GBPUSD vs USDCHF • MSFT vs NVDA
- EURUSD vs USDCHF • AAPL vs NVDA
- EURUSD vs EURCAD
💡 Practical Use Cases
🔄 Pairs Trading
Detects when strong correlations break for:
Statistical arbitrage
Mean reversion trading
Divergence opportunities
🛡️ Risk Management
Identifies when "safe" assets start moving independently:
Portfolio diversification
Smart hedging
Regime change detection
📊 Market Analysis
Understand underlying market structure:
Forex/DXY correlations
Tech sector rotation
Regional market disconnection
🎓 Results Interpretation
Reading Example:
EURUSD vs DXY: -98.57% → -98.27% | 🟢 OK
└─ Perfect negative correlation maintained (EUR rises when DXY falls)
TSLA vs NVDA: 78.12% → 0% | ⚫ NORMAL
└─ Lost tech correlation (divergence opportunity)
Trading Signals:
🟢 → 🔴: Broken correlation = Possible opportunity
Large difference: Indicates correlation tension
Multiple breaks: Market regime change
Rolling Log Returns [BackQuant]Rolling Log Returns
The Rolling Log Returns indicator is a versatile tool designed to help traders, quants, and data-driven analysts evaluate the dynamics of price changes using logarithmic return analysis. Widely adopted in quantitative finance, log returns offer several mathematical and statistical advantages over simple returns, making them ideal for backtesting, portfolio optimization, volatility modeling, and risk management.
What Are Log Returns?
In quantitative finance, logarithmic returns are defined as:
ln(Pₜ / Pₜ₋₁)
or for rolling periods:
ln(Pₜ / Pₜ₋ₙ)
where P represents price and n is the rolling lookback window.
Log returns are preferred because:
They are time additive : returns over multiple periods can be summed.
They allow for easier statistical modeling , especially when assuming normally distributed returns.
They behave symmetrically for gains and losses, unlike arithmetic returns.
They normalize percentage changes, making cross-asset or cross-timeframe comparisons more consistent.
Indicator Overview
The Rolling Log Returns indicator computes log returns either on a standard (1-period) basis or using a rolling lookback period , allowing users to adapt it to short-term trading or long-term trend analysis.
It also supports a comparison series , enabling traders to compare the return structure of the main charted asset to another instrument (e.g., SPY, BTC, etc.).
Core Features
✅ Return Modes :
Normal Log Returns : Measures ln(price / price ), ideal for day-to-day return analysis.
Rolling Log Returns : Measures ln(price / price ), highlighting price drift over longer horizons.
✅ Comparison Support :
Compare log returns of the primary instrument to another symbol (like an index or ETF).
Useful for relative performance and market regime analysis .
✅ Moving Averages of Returns :
Smooth noisy return series with customizable MA types: SMA, EMA, WMA, RMA, and Linear Regression.
Applicable to both primary and comparison series.
✅ Conditional Coloring :
Returns > 0 are colored green ; returns < 0 are red .
Comparison series gets its own unique color scheme.
✅ Extreme Return Detection :
Highlight unusually large price moves using upper/lower thresholds.
Visually flags abnormal volatility events such as earnings surprises or macroeconomic shocks.
Quantitative Use Cases
🔍 Return Distribution Analysis :
Gain insight into the statistical properties of asset returns (e.g., skewness, kurtosis, tail behavior).
📉 Risk Management :
Use historical return outliers to define drawdown expectations, stress tests, or VaR simulations.
🔁 Strategy Backtesting :
Apply rolling log returns to momentum or mean-reversion models where compounding and consistent scaling matter.
📊 Market Regime Detection :
Identify periods of consistent overperformance/underperformance relative to a benchmark asset.
📈 Signal Engineering :
Incorporate return deltas, moving average crossover of returns, or threshold-based triggers into machine learning pipelines or rule-based systems.
Recommended Settings
Use Normal mode for high-frequency trading signals.
Use Rolling mode for swing or trend-following strategies.
Compare vs. a broad market index (e.g., SPY or QQQ ) to extract relative strength insights.
Set upper and lower thresholds around ±5% for spotting major volatility days.
Conclusion
The Rolling Log Returns indicator transforms raw price action into a statistically sound return series—equipping traders with a professional-grade lens into market behavior. Whether you're conducting exploratory data analysis, building factor models, or visually scanning for outliers, this indicator integrates seamlessly into a modern quant's toolbox.
Out of the Noise Intraday Strategy with VWAP [YuL]This is my (naive) implementation of "Beat the Market An Effective Intraday Momentum Strategy for S&P500 ETF (SPY)" paper by Carlo Zarattini, Andrew Aziz, Andrea Barbon, so the credit goes to them.
It is supposed to run on SPY on 30-minute timeframe, there may be issues on other timeframes.
I've used settings that were used by the authors in the original paper to keep it close to the publication, but I understand that they are very aggressive and probably shouldn't be used like that.
Results are good, but not as good as they are stated in the paper (unsurprisingly?): returns are smaller and Sharpe is very low (which is actually weird given the returns and drawdown ratio), there are also margin calls if you enable margin check (and you should).
I have my own ideas of improvements which I will probably implement separately to keep this clean.
Failed 2U/2D + 50% Retrace Scanner📈 Multi-Ticker Failed 2U/2D Scanner with Daily Retrace & Market Breadth Table
This TradingView indicator is a multi-symbol price action scanner designed to catch high-probability reversal signals using The Strat’s failed 2U/2D patterns and daily 50% retrace logic, while also displaying market breadth metrics ( USI:TICK and USI:ADD ) for context.
Monitored Symbols:
SPY, SPX, QQQ, IWM, NVDA, AMD, AAPL, META, MSTR
🔍 Detection Logic
1. Failed 2U / Failed 2D Setups
Failed 2U: Price breaks above the previous candle’s high but closes back below the open → Bearish reversal
Failed 2D: Price breaks below the previous candle’s low but closes back above the open → Bullish reversal
Timeframes Monitored:
🕐 1-Hour (1H)
⏰ 4-Hour (4H)
2. Daily 50% Candle Retrace
Checks if price has retraced 50% or more of the previous day’s candle body
Highlights potential trend exhaustion or reversal confluence
3. Market Breadth Metrics (Display Only)
USI:TICK : Measures real-time NYSE up vs. down ticks
USI:ADD : Advance-Decline Line (net advancing stocks)
Not used in signal logic — just displayed in the table for overall market context
🖼️ Visual Elements
✅ Chart Markers
🔺 Red/Green Arrows for 1H Failed 2U/2D
🟨 Yellow Squares for 4H Failed 2U/2D
Visual markers are plotted directly on the relevant candles
📊 Signal Table
Lists all 9 tickers in rows
Columns for:
1H Signal
4H Signal
Daily 50% Retrace
USI:TICK Value
USI:ADD Value
Color-Coded Cells:
🔴 Red = Failed 2U
🟢 Green = Failed 2D
⚠️ Highlight if 50% Daily Retrace condition is true
🟦 Neutral-colored cells for TICK/ADD numeric display
🔔 Alerts
Hardcoded alerts fire when:
A 1H or 4H Failed 2U/2D is detected
The Daily 50% retrace condition is met
Each alert is labeled clearly by symbol and timeframe:
"META 4H Failed 2D"
"AAPL Daily 50% Retrace"
🎯 Use Case
Built for:
Reversal traders using The Strat
Swing or intraday traders watching hourly setups
Traders wanting quick visual context on market breadth without relying on it for confirmation
Monitoring multiple tickers in one clean view
This is scan 2
Add scan 1 for spx, spy, iwm, qqq, aapl
This indicator is not financial advice. Use the alerts to check out chart and when tickers trigger.
Yelober - Intraday ETF Dashboard# How to Read the Yelober Intraday ETF Dashboard
The Intraday ETF Dashboard provides a powerful at-a-glance view of sector performance and trading opportunities. Here's how to interpret and use the information:
## Basic Dashboard Reading
### Color-Coding System
- **Green values**: Positive performance or bullish signals
- **Red values**: Negative performance or bearish signals
- **Symbol colors**: Green = buy signal, Red = sell signal, Gray = neutral
### Example 1: Identifying Strong Sectors
If you see XLF (Financials) with:
- Day % showing +2.65% (green background)
- Symbol in green color
- RSI of 58 (not overbought)
**Interpretation**: Financial sector is showing strength and momentum without being overextended. Consider long positions in top financial stocks like JPM or BAC.
### Example 2: Spotting Weakness
If you see XLK (Technology) with:
- Day % showing -1.20% (red background)
- Week % showing -3.50% (red background)
- Symbol in red color
- RSI of 35 (approaching oversold)
**Interpretation**: Technology sector is showing weakness across multiple timeframes. Consider avoiding tech stocks or taking short positions in names like MSFT or AAPL, but be cautious as the low RSI suggests a bounce may be coming.
## Advanced Interpretations
### Example 3: Sector Rotation Detection
If you observe:
- XLE (Energy) showing +2.10% while XLK (Technology) showing -1.50%
- Both sectors' Week % values showing the opposite trend
**Interpretation**: This suggests money is rotating out of technology into energy stocks. This rotation pattern is actionable - consider reducing tech exposure and increasing energy positions (look at XOM, CVX in the Top Stocks column).
### Example 4: RSI Divergences
If you see XLU (Utilities) with:
- Day % showing +0.50% (small positive)
- RSI showing 72 (overbought, red background)
**Interpretation**: Despite positive performance, the high RSI suggests the sector is overextended. This divergence between price and indicator suggests caution - the rally in utilities may be running out of steam.
### Example 5: Relative Strength in Weak Markets
If SPY shows -1.20% but XLP (Consumer Staples) shows +0.30%:
**Interpretation**: Consumer staples are showing defensive strength during market weakness. This is typical risk-off behavior. Consider defensive positions in stocks like PG, KO, or PEP for protection.
## Practical Application Scenarios
### Day Trading Setup
1. **Morning Market Assessment**:
- Check which sectors are green pre-market
- Focus on sectors with Day % > 1% and RSI between 40-70
- Identify 2-3 stocks from the Top Stocks column of the strongest sector
2. **Midday Reversal Hunting**:
- Look for sectors with symbol color changing from red to green
- Confirm with RSI moving away from extremes
- Trade stocks from that sector showing similar pattern changes
### Swing Trading Application
1. **Trend Following**:
- Identify sectors with positive Day % and Week %
- Look for RSI values in uptrend but not overbought (45-65)
- Enter positions in top stocks from these sectors, using daily charts for confirmation
2. **Contrarian Setups**:
- Find sectors with deeply negative Day % but RSI < 30
- Look for divergence (price making new lows but RSI rising)
- Consider counter-trend positions in the stronger stocks within these oversold sectors
## Reading Special Conditions
### Example 6: Risk-Off Environment
If you observe:
- XLP (Consumer Staples) and XLU (Utilities) both green
- XLK (Technology) and XLY (Consumer Disc) both red
- SPY slightly negative
**Interpretation**: Classic risk-off rotation. Investors are moving to safety. Consider defensive positioning and reducing exposure to growth sectors.
### Example 7: Market Breadth Analysis
Count the number of sectors in green vs. red:
- If 7+ sectors are green: Strong bullish breadth, consider aggressive long positioning
- If 7+ sectors are red: Weak market breadth, consider defensive positioning or shorts
- If evenly split: Market is indecisive, focus on specific sector strength instead of broad market exposure
Remember that this dashboard is most effective when combined with broader market analysis and appropriate risk management strategies.
Multifractal Forecast [ScorsoneEnterprises]Multifractal Forecast Indicator
The Multifractal Forecast is an indicator designed to model and forecast asset price movements using a multifractal framework. It uses concepts from fractal geometry and stochastic processes, specifically the Multifractal Model of Asset Returns (MMAR) and fractional Brownian motion (fBm), to generate price forecasts based on historical price data. The indicator visualizes potential future price paths as colored lines, providing traders with a probabilistic view of price trends over a specified trading time scale. Below is a detailed breakdown of the indicator’s functionality, inputs, calculations, and visualization.
Overview
Purpose: The indicator forecasts future price movements by simulating multiple price paths based on a multifractal model, which accounts for the complex, non-linear behavior of financial markets.
Key Concepts:
Multifractal Model of Asset Returns (MMAR): Models price movements as a multifractal process, capturing varying degrees of volatility and self-similarity across different time scales.
Fractional Brownian Motion (fBm): A generalization of Brownian motion that incorporates long-range dependence and self-similarity, controlled by the Hurst exponent.
Binomial Cascade: Used to model trading time, introducing heterogeneity in time scales to reflect market activity bursts.
Hurst Exponent: Measures the degree of long-term memory in the price series (persistence, randomness, or mean-reversion).
Rescaled Range (R/S) Analysis: Estimates the Hurst exponent to quantify the fractal nature of the price series.
Inputs
The indicator allows users to customize its behavior through several input parameters, each influencing the multifractal model and forecast generation:
Maximum Lag (max_lag):
Type: Integer
Default: 50
Minimum: 5
Purpose: Determines the maximum lag used in the rescaled range (R/S) analysis to calculate the Hurst exponent. A higher lag increases the sample size for Hurst estimation but may smooth out short-term dynamics.
2 to the n values in the Multifractal Model (n):
Type: Integer
Default: 4
Purpose: Defines the resolution of the multifractal model by setting the size of arrays used in calculations (N = 2^n). For example, n=4 results in N=16 data points. Larger n increases computational complexity and detail but may exceed Pine Script’s array size limits (capped at 100,000).
Multiplier for Binomial Cascade (m):
Type: Float
Default: 0.8
Purpose: Controls the asymmetry in the binomial cascade, which models trading time. The multiplier m (and its complement 2.0 - m) determines how mass is distributed across time scales. Values closer to 1 create more balanced cascades, while values further from 1 introduce more variability.
Length Scale for fBm (L):
Type: Float
Default: 100,000.0
Purpose: Scales the fractional Brownian motion output, affecting the amplitude of simulated price paths. Larger values increase the magnitude of forecasted price movements.
Cumulative Sum (cum):
Type: Integer (0 or 1)
Default: 1
Purpose: Toggles whether the fBm output is cumulatively summed (1=On, 0=Off). When enabled, the fBm series is accumulated to simulate a price path with memory, resembling a random walk with long-range dependence.
Trading Time Scale (T):
Type: Integer
Default: 5
Purpose: Defines the forecast horizon in bars (20 bars into the future). It also scales the binomial cascade’s output to align with the desired trading time frame.
Number of Simulations (num_simulations):
Type: Integer
Default: 5
Minimum: 1
Purpose: Specifies how many forecast paths are simulated and plotted. More simulations provide a broader range of possible price outcomes but increase computational load.
Core Calculations
The indicator combines several mathematical and statistical techniques to generate price forecasts. Below is a step-by-step explanation of its calculations:
Log Returns (lgr):
The indicator calculates log returns as math.log(close / close ) when both the current and previous close prices are positive. This measures the relative price change in a logarithmic scale, which is standard for financial time series analysis to stabilize variance.
Hurst Exponent Estimation (get_hurst_exponent):
Purpose: Estimates the Hurst exponent (H) to quantify the degree of long-term memory in the price series.
Method: Uses rescaled range (R/S) analysis:
For each lag from 2 to max_lag, the function calc_rescaled_range computes the rescaled range:
Calculate the mean of the log returns over the lag period.
Compute the cumulative deviation from the mean.
Find the range (max - min) of the cumulative deviation.
Divide the range by the standard deviation of the log returns to get the rescaled range.
The log of the rescaled range (log(R/S)) is regressed against the log of the lag (log(lag)) using the polyfit_slope function.
The slope of this regression is the Hurst exponent (H).
Interpretation:
H = 0.5: Random walk (no memory, like standard Brownian motion).
H > 0.5: Persistent behavior (trends tend to continue).
H < 0.5: Mean-reverting behavior (price tends to revert to the mean).
Fractional Brownian Motion (get_fbm):
Purpose: Generates a fractional Brownian motion series to model price movements with long-range dependence.
Inputs: n (array size 2^n), H (Hurst exponent), L (length scale), cum (cumulative sum toggle).
Method:
Computes covariance for fBm using the formula: 0.5 * (|i+1|^(2H) - 2 * |i|^(2H) + |i-1|^(2H)).
Uses Hosking’s method (referenced from Columbia University’s implementation) to generate fBm:
Initializes arrays for covariance (cov), intermediate calculations (phi, psi), and output.
Iteratively computes the fBm series by incorporating a random term scaled by the variance (v) and covariance structure.
Applies scaling based on L / N^H to adjust the amplitude.
Optionally applies cumulative summation if cum = 1 to produce a path with memory.
Output: An array of 2^n values representing the fBm series.
Binomial Cascade (get_binomial_cascade):
Purpose: Models trading time (theta) to account for non-uniform market activity (e.g., bursts of volatility).
Inputs: n (array size 2^n), m (multiplier), T (trading time scale).
Method:
Initializes an array of size 2^n with values of 1.0.
Iteratively applies a binomial cascade:
For each block (from 0 to n-1), splits the array into segments.
Randomly assigns a multiplier (m or 2.0 - m) to each segment, redistributing mass.
Normalizes the array by dividing by its sum and scales by T.
Checks for array size limits to prevent Pine Script errors.
Output: An array (theta) representing the trading time, which warps the fBm to reflect market activity.
Interpolation (interpolate_fbm):
Purpose: Maps the fBm series to the trading time scale to produce a forecast.
Method:
Computes the cumulative sum of theta and normalizes it to .
Interpolates the fBm series linearly based on the normalized trading time.
Ensures the output aligns with the trading time scale (T).
Output: An array of interpolated fBm values representing log returns over the forecast horizon.
Price Path Generation:
For each simulation (up to num_simulations):
Generates an fBm series using get_fbm.
Interpolates it with the trading time (theta) using interpolate_fbm.
Converts log returns to price levels:
Starts with the current close price.
For each step i in the forecast horizon (T), computes the price as prev_price * exp(log_return).
Output: An array of price levels for each simulation.
Visualization:
Trigger: Updates every T bars when the bar state is confirmed (barstate.isconfirmed).
Process:
Clears previous lines from line_array.
For each simulation, plots a line from the current bar’s close price to the forecasted price at bar_index + T.
Colors the line using a gradient (color.from_gradient) based on the final forecasted price relative to the minimum and maximum forecasted prices across all simulations (red for lower prices, teal for higher prices).
Output: Multiple colored lines on the chart, each representing a possible price path over the next T bars.
How It Works on the Chart
Initialization: On each bar, the indicator calculates the Hurst exponent (H) using historical log returns and prepares the trading time (theta) using the binomial cascade.
Forecast Generation: Every T bars, it generates num_simulations price paths:
Each path starts at the current close price.
Uses fBm to model log returns, warped by the trading time.
Converts log returns to price levels.
Plotting: Draws lines from the current bar to the forecasted price T bars ahead, with colors indicating relative price levels.
Dynamic Updates: The forecast updates every T bars, replacing old lines with new ones based on the latest price data and calculations.
Key Features
Multifractal Modeling: Captures complex market dynamics by combining fBm (long-range dependence) with a binomial cascade (non-uniform time).
Customizable Parameters: Allows users to adjust the forecast horizon, model resolution, scaling, and number of simulations.
Probabilistic Forecast: Multiple simulations provide a range of possible price outcomes, helping traders assess uncertainty.
Visual Clarity: Gradient-colored lines make it easy to distinguish bullish (teal) and bearish (red) forecasts.
Potential Use Cases
Trend Analysis: Identify potential price trends or reversals based on the direction and spread of forecast lines.
Risk Assessment: Evaluate the range of possible price outcomes to gauge market uncertainty.
Volatility Analysis: The Hurst exponent and binomial cascade provide insights into market persistence and volatility clustering.
Limitations
Computational Intensity: Large values of n or num_simulations may slow down execution or hit Pine Script’s array size limits.
Randomness: The binomial cascade and fBm rely on random terms (math.random), which may lead to variability between runs.
Assumptions: The model assumes log-normal price movements and fractal behavior, which may not always hold in extreme market conditions.
Adjusting Inputs:
Set max_lag based on the desired depth of historical analysis.
Adjust n for model resolution (start with 4–6 to avoid performance issues).
Tune m to control trading time variability (0.5–1.5 is typical).
Set L to scale the forecast amplitude (experiment with values like 10,000–1,000,000).
Choose T based on your trading horizon (20 for short-term, 50 for longer-term for example).
Select num_simulations for the number of forecast paths (5–10 is reasonable for visualization).
Interpret Output:
Teal lines suggest bullish scenarios, red lines suggest bearish scenarios.
A wide spread of lines indicates high uncertainty; convergence suggests a stronger trend.
Monitor Updates: Forecasts update every T bars, so check the chart periodically for new projections.
Chart Examples
This is a daily AMEX:SPY chart with default settings. We see the simulations being done every T bars and they provide a range for us to analyze with a few simulations still in the range.
On this intraday PEPPERSTONE:COCOA chart I modified the Length Scale for fBm, L, parameter to be 1000 from 100000. Adjusting the parameter as you switch between timeframes can give you more contextual simulations.
On BITSTAMP:ETHUSD I modified the L to be 1000000 to have a more contextual set of simulations with crypto's volatile nature.
With L at 100000 we see the range for NASDAQ:TLT is correctly simulated. The recent pop stays within the bounds of the highest simulation. Note this is a cherry picked example to show the power and potential of these simulations.
Technical Notes
Error Handling: The script includes checks for array size limits and division by zero (math.abs(denominator) > 1e-10, v := math.max(v, 1e-10)).
External Reference: The fBm implementation is based on Hosking’s method (www.columbia.edu), ensuring a robust algorithm.
Conclusion
The Multifractal Forecast is a powerful tool for traders seeking to model complex market dynamics using a multifractal framework. By combining fBm, binomial cascades, and Hurst exponent analysis, it generates probabilistic price forecasts that account for long-range dependence and non-uniform market activity. Its customizable inputs and clear visualizations make it suitable for both technical analysis and strategy development, though users should be mindful of its computational demands and parameter sensitivity. For optimal use, experiment with input settings and validate forecasts against other technical indicators or market conditions.
CDP - Counter-Directional-Pivot🎯 CDP - Counter-Directional-Pivot
📊 Overview
The Counter-Directional-Pivot (CDP) indicator calculates five critical price levels based on the previous day's OHLC data, specifically designed for multi-timeframe analysis. Unlike standard pivot points, CDP levels are calculated using a unique formula that identifies potential reversal zones where price action often changes direction.
⚡ What Makes This Script Original
This implementation solves several technical challenges that existing pivot indicators face:
🔄 Multi-Timeframe Consistency: Values remain identical across all timeframes (1m, 5m, 1h, daily) - a common problem with many pivot implementations
🔒 Intraday Stability: Uses advanced value-locking technology to prevent the "stepping" effect that occurs when pivot lines shift during the trading session
💪 Robust Data Handling: Optimized for both liquid and illiquid stocks with enhanced data synchronization
🧮 CDP Calculation Formula
The indicator calculates five key levels using the previous day's High (H), Low (L), and Close (C):
CDP = (H + L + C) ÷ 3 (Central Decision Point)
AH = 2×CDP + H – 2×L (Anchor High - Strong Resistance)
NH = 2×CDP – L (Near High - Moderate Resistance)
AL = 2×CDP – 2×H + L (Anchor Low - Strong Support)
NL = 2×CDP – H (Near Low - Moderate Support)
✨ Key Features
🎨 Visual Elements
📈 Five Distinct Price Levels: Each with customizable colors and line styles
🏷️ Smart Label System: Shows exact price values for each level
📋 Optional Value Table: Displays all levels in an organized table format
🎯 Clean Chart Display: Minimal visual clutter while maximizing information
⚙️ Technical Advantages
🔐 Session-Locked Values: Prices are locked at market open, preventing intraday shifts
🔄 Multi-Timeframe Sync: Perfect consistency between daily and intraday charts
✅ Data Validation: Built-in checks ensure reliable calculations
🚀 Performance Optimized: Efficient code structure for fast loading
💼 Trading Applications
🔄 Reversal Zones: AH and AL often act as strong turning points
💥 Breakout Confirmation: Price movement beyond these levels signals trend continuation
🛡️ Risk Management: Use levels for stop-loss and take-profit placement
🏗️ Market Structure: Understand daily ranges and potential price targets
📚 How to Use
🚀 Basic Setup
Add the indicator to your chart (works on any timeframe)
Customize colors for easy identification of support/resistance zones
Enable the value table for quick reference of exact price levels
📈 Trading Strategy Examples
🟢 Long Bias: Look for bounces at NL or AL levels
🔴 Short Bias: Watch for rejections at NH or AH levels
💥 Breakout Trading: Enter positions when price decisively breaks through anchor levels
↔️ Range Trading: Use CDP as the central reference point for range-bound markets
🎯 Advanced Strategy Combinations
RSI Integration for Enhanced Signals: 📊
📉 Oversold Bounces: Combine RSI below 30 with price touching AL/NL levels for high-probability long entries
📈 Overbought Rejections: Look for RSI above 70 with price rejecting AH/NH levels for short opportunities
🔍 Divergence Confirmation: When RSI shows bullish divergence at support levels (AL/NL) or bearish divergence at resistance levels (AH/NH), it often signals stronger reversal potential
⚡ Momentum Confluence: RSI crossing 50 while price breaks through CDP can confirm trend direction changes
⚙️ Configuration Options
🎨 Line Customization: Adjust width, style (solid/dashed/dotted), and colors
👁️ Display Preferences: Toggle individual levels, labels, and value table
📍 Table Position: Place the value table anywhere on your chart
🔔 Alert System: Get notifications when price crosses key levels
🔧 Technical Implementation Details
🎯 Data Reliability
The script uses request.security() with lookahead settings to ensure historical accuracy while maintaining real-time functionality. The value-locking mechanism prevents the common issue where pivot levels shift during the trading day.
🔄 Multi-Timeframe Logic
⏰ Intraday Charts: Display previous day's calculated levels as stable horizontal lines
📅 Daily Charts: Show current day's levels based on yesterday's OHLC
🔍 Consistency Check: All timeframes reference the same source data
🤔 Why CDP vs Standard Pivots?
Counter-Directional Pivots often provide more accurate reversal points than traditional pivot calculations because they incorporate the relationship between high/low ranges and closing prices more effectively. The formula creates levels that better reflect market psychology and institutional trading behaviors.
💡 Best Practices
💧 Use on liquid markets for most reliable results
📊 RSI Combination: Add RSI indicator for overbought/oversold confirmation and divergence analysis
📊 Combine with volume analysis for confirmation
🔍 Consider multiple timeframe analysis (daily levels on hourly charts)
📝 Test thoroughly in paper trading before live implementation
💪 Example Market Applications
NASDAQ:AAPL AAPL - Tech stock breakouts through AH levels
$NYSE:SPY SPY - Index trading with CDP range analysis
NASDAQ:TSLA TSLA - Volatile stock reversals at AL/NL levels
⚠️ This indicator is designed for educational and analytical purposes. Always combine with proper risk management and additional technical analysis tools.
Ergodic Market Divergence (EMD)Ergodic Market Divergence (EMD)
Bridging Statistical Physics and Market Dynamics Through Ensemble Analysis
The Revolutionary Concept: When Physics Meets Trading
After months of research into ergodic theory—a fundamental principle in statistical mechanics—I've developed a trading system that identifies when markets transition between predictable and unpredictable states. This indicator doesn't just follow price; it analyzes whether current market behavior will persist or revert, giving traders a scientific edge in timing entries and exits.
The Core Innovation: Ergodic Theory Applied to Markets
What Makes Markets Ergodic or Non-Ergodic?
In statistical physics, ergodicity determines whether a system's future resembles its past. Applied to trading:
Ergodic Markets (Mean-Reverting)
- Time averages equal ensemble averages
- Historical patterns repeat reliably
- Price oscillates around equilibrium
- Traditional indicators work well
Non-Ergodic Markets (Trending)
- Path dependency dominates
- History doesn't predict future
- Price creates new equilibrium levels
- Momentum strategies excel
The Mathematical Framework
The Ergodic Score combines three critical divergences:
Ergodic Score = (Price Divergence × Market Stress + Return Divergence × 1000 + Volatility Divergence × 50) / 3
Where:
Price Divergence: How far current price deviates from market consensus
Return Divergence: Momentum differential between instrument and market
Volatility Divergence: Volatility regime misalignment
Market Stress: Adaptive multiplier based on current conditions
The Ensemble Analysis Revolution
Beyond Single-Instrument Analysis
Traditional indicators analyze one chart in isolation. EMD monitors multiple correlated markets simultaneously (SPY, QQQ, IWM, DIA) to detect systemic regime changes. This ensemble approach:
Reveals Hidden Divergences: Individual stocks may diverge from market consensus before major moves
Filters False Signals: Requires broader market confirmation
Identifies Regime Shifts: Detects when entire market structure changes
Provides Context: Shows if moves are isolated or systemic
Dynamic Threshold Adaptation
Unlike fixed-threshold systems, EMD's boundaries evolve with market conditions:
Base Threshold = SMA(Ergodic Score, Lookback × 3)
Adaptive Component = StDev(Ergodic Score, Lookback × 2) × Sensitivity
Final Threshold = Smoothed(Base + Adaptive)
This creates context-aware signals that remain effective across different market environments.
The Confidence Engine: Know Your Signal Quality
Multi-Factor Confidence Scoring
Every signal receives a confidence score based on:
Signal Clarity (0-35%): How decisively the ergodic threshold is crossed
Momentum Strength (0-25%): Rate of ergodic change
Volatility Alignment (0-20%): Whether volatility supports the signal
Market Quality (0-20%): Price convergence and path dependency factors
Real-Time Confidence Updates
The Live Confidence metric continuously updates, showing:
- Current opportunity quality
- Market state clarity
- Historical performance influence
- Signal recency boost
- Visual Intelligence System
Adaptive Ergodic Field Bands
Dynamic bands that expand and contract based on market state:
Primary Color: Ergodic state (mean-reverting)
Danger Color: Non-ergodic state (trending)
Band Width: Expected price movement range
Squeeze Indicators: Volatility compression warnings
Quantum Wave Ribbons
Triple EMA system (8, 21, 55) revealing market flow:
Compressed Ribbons: Consolidation imminent
Expanding Ribbons: Directional move developing
Color Coding: Matches current ergodic state
Phase Transition Signals
Clear entry/exit markers at regime changes:
Bull Signals: Ergodic restoration (mean reversion opportunity)
Bear Signals: Ergodic break (trend following opportunity)
Confidence Labels: Percentage showing signal quality
Visual Intensity: Stronger signals = deeper colors
Professional Dashboard Suite
Main Analytics Panel (Top Right)
Market State Monitor
- Current regime (Ergodic/Non-Ergodic)
- Ergodic score with threshold
- Path dependency strength
- Quantum coherence percentage
Divergence Metrics
- Price divergence with severity
- Volatility regime classification
- Strategy mode recommendation
- Signal strength indicator
Live Intelligence
- Real-time confidence score
- Color-coded risk levels
- Dynamic strategy suggestions
Performance Tracking (Left Panel)
Signal Analytics
- Total historical signals
- Win rate with W/L breakdown
- Current streak tracking
- Closed trade counter
Regime Analysis
- Current market behavior
- Bars since last signal
- Recommended actions
- Average confidence trends
Strategy Command Center (Bottom Right)
Adaptive Recommendations
- Active strategy mode
- Primary approach (mean reversion/momentum)
- Suggested indicators ("weapons")
- Entry/exit methodology
- Risk management guidance
- Comprehensive Input Guide
Core Algorithm Parameters
Analysis Period (10-100 bars)
Scalping (10-15): Ultra-responsive, more signals, higher noise
Day Trading (20-30): Balanced sensitivity and stability
Swing Trading (40-100): Smooth signals, major moves only Default: 20 - optimal for most timeframes
Divergence Threshold (0.5-5.0)
Hair Trigger (0.5-1.0): Catches every wiggle, many false signals
Balanced (1.5-2.5): Good signal-to-noise ratio
Conservative (3.0-5.0): Only extreme divergences Default: 1.5 - best risk/reward balance
Path Memory (20-200 bars)
Short Memory (20-50): Recent behavior focus, quick adaptation
Medium Memory (50-100): Balanced historical context
Long Memory (100-200): Emphasizes established patterns Default: 50 - captures sufficient history without lag
Signal Spacing (5-50 bars)
Aggressive (5-10): Allows rapid-fire signals
Normal (15-25): Prevents clustering, maintains flow
Conservative (30-50): Major setups only Default: 15 - optimal trade frequency
Ensemble Configuration
Select markets for consensus analysis:
SPY: Broad market sentiment
QQQ: Technology leadership
IWM: Small-cap risk appetite
DIA: Blue-chip stability
More instruments = stronger consensus but potentially diluted signals
Visual Customization
Color Themes (6 professional options):
Quantum: Cyan/Pink - Modern trading aesthetic
Matrix: Green/Red - Classic terminal look
Heat: Blue/Red - Temperature metaphor
Neon: Cyan/Magenta - High contrast
Ocean: Turquoise/Coral - Calming palette
Sunset: Red-orange/Teal - Warm gradients
Display Controls:
- Toggle each visual component
- Adjust transparency levels
- Scale dashboard text
- Show/hide confidence scores
- Trading Strategies by Market State
- Ergodic State Strategy (Primary Color Bands)
Market Characteristics
- Price oscillates predictably
- Support/resistance hold
- Volume patterns repeat
- Mean reversion dominates
Optimal Approach
Entry: Fade moves at band extremes
Target: Middle band (equilibrium)
Stop: Just beyond outer bands
Size: Full confidence-based position
Recommended Tools
- RSI for oversold/overbought
- Bollinger Bands for extremes
- Volume profile for levels
- Non-Ergodic State Strategy (Danger Color Bands)
Market Characteristics
- Price trends persistently
- Levels break decisively
- Volume confirms direction
- Momentum accelerates
Optimal Approach
Entry: Breakout from bands
Target: Trail with expanding bands
Stop: Inside opposite band
Size: Scale in with trend
Recommended Tools
- Moving average alignment
- ADX for trend strength
- MACD for momentum
- Advanced Features Explained
Quantum Coherence Metric
Measures phase alignment between individual and ensemble behavior:
80-100%: Perfect sync - strong mean reversion setup
50-80%: Moderate alignment - mixed signals
0-50%: Decoherence - trending behavior likely
Path Dependency Analysis
Quantifies how much history influences current price:
Low (<30%): Technical patterns reliable
Medium (30-50%): Mixed influences
High (>50%): Fundamental shift occurring
Volatility Regime Classification
Contextualizes current volatility:
Normal: Standard strategies apply
Elevated: Widen stops, reduce size
Extreme: Defensive mode required
Signal Strength Indicator
Real-time opportunity quality:
- Distance from threshold
- Momentum acceleration
- Cross-validation factors
Risk Management Framework
Position Sizing by Confidence
90%+ confidence = 100% position size
70-90% confidence = 75% position size
50-70% confidence = 50% position size
<50% confidence = 25% or skip
Dynamic Stop Placement
Ergodic State: ATR × 1.0 from entry
Non-Ergodic State: ATR × 2.0 from entry
Volatility Adjustment: Multiply by current regime
Multi-Timeframe Alignment
- Check higher timeframe regime
- Confirm ensemble consensus
- Verify volume participation
- Align with major levels
What Makes EMD Unique
Original Contributions
First Ergodic Theory Trading Application: Transforms abstract physics into practical signals
Ensemble Market Analysis: Revolutionary multi-market divergence system
Adaptive Confidence Engine: Institutional-grade signal quality metrics
Quantum Coherence: Novel market alignment measurement
Smart Signal Management: Prevents clustering while maintaining responsiveness
Technical Innovations
Dynamic Threshold Adaptation: Self-adjusting sensitivity
Path Memory Integration: Historical dependency weighting
Stress-Adjusted Scoring: Market condition normalization
Real-Time Performance Tracking: Built-in strategy analytics
Optimization Guidelines
By Timeframe
Scalping (1-5 min)
Period: 10-15
Threshold: 0.5-1.0
Memory: 20-30
Spacing: 5-10
Day Trading (5-60 min)
Period: 20-30
Threshold: 1.5-2.5
Memory: 40-60
Spacing: 15-20
Swing Trading (1H-1D)
Period: 40-60
Threshold: 2.0-3.0
Memory: 80-120
Spacing: 25-35
Position Trading (1D-1W)
Period: 60-100
Threshold: 3.0-5.0
Memory: 100-200
Spacing: 40-50
By Market Condition
Trending Markets
- Increase threshold
- Extend memory
- Focus on breaks
Ranging Markets
- Decrease threshold
- Shorten memory
- Focus on restores
Volatile Markets
- Increase spacing
- Raise confidence requirement
- Reduce position size
- Integration with Other Analysis
- Complementary Indicators
For Ergodic States
- RSI divergences
- Bollinger Band squeezes
- Volume profile nodes
- Support/resistance levels
For Non-Ergodic States
- Moving average ribbons
- Trend strength indicators
- Momentum oscillators
- Breakout patterns
- Fundamental Alignment
- Check economic calendar
- Monitor sector rotation
- Consider market themes
- Evaluate risk sentiment
Troubleshooting Guide
Too Many Signals:
- Increase threshold
- Extend signal spacing
- Raise confidence minimum
Missing Opportunities
- Decrease threshold
- Reduce signal spacing
- Check ensemble settings
Poor Win Rate
- Verify timeframe alignment
- Confirm volume participation
- Review risk management
Disclaimer
This indicator is for educational and informational purposes only. It does not constitute financial advice. Trading involves substantial risk of loss and is not suitable for all investors. Past performance does not guarantee future results.
The ergodic framework provides unique market insights but cannot predict future price movements with certainty. Always use proper risk management, conduct your own analysis, and never risk more than you can afford to lose.
This tool should complement, not replace, comprehensive trading strategies and sound judgment. Markets remain inherently unpredictable despite advanced analysis techniques.
Transform market chaos into trading clarity with Ergodic Market Divergence.
Created with passion for the TradingView community
Trade with insight. Trade with anticipation.
— Dskyz , for DAFE Trading Systems
Sector Relative StrengthDescription
This script compares sector performance relative to the S&P 500. Sector price levels or charts alone can mislead, because they tend to move with the broader market. An increase in a sector’s price does not necessarily indicate strength, as it may simply be following the index.
For more a more reliable picture, the script calculates a ratio between each sector ETF and SPY. If the ratio has increased, the sector has outperformed the index. In case it has declined, the sector has underperformed. If the value is near zero, the sector has moved in line with the index. The sectors are presented in a table and sorted on relative performance.
Calculation Method
The performance is expressed as a percentage change in the ratio over a user-defined lookback period. The default lookback is set to 21 bars, which corresponds to one month on a daily chart. This value can be adopted in the settings to match preferred time period.
Z-Score
In addition to the percentage change, the script calculates a Z-score of the ratio, which measures how far the current value deviates from its recent mean. A high positive Z-score indicates that the ratio is significantly above its average, while a negative value indicates it is below. This normalization allows for comparison between sectors with different price levels or volatility profiles.
Table Columns
- Relative %: The sector's performance relative to SPY over the selected lookback period
- Z-Score: Standardized measure of current performance ratio is relative to its average
- Trend Arrow: Indicates the direction of relative performance up down or flat
Example Interpretation
For example, if XLK shows a 3.7% change, it has outperformed SPY over the selected period. Another sector might show a -2.1% change, which indicates underperformance. While both values shows relative strength or weakness, the Z-score is optional and can provide additional context based on how unusual that performance is compared to the sector's own recent behavior.
Use Case
This approach helps evaluate overall market conditions and supports a top-down method. By starting with sector performance, it becomes easier to identify where the market is showing leadership or weakness. This allows the stock selection process to be more deliberate and can help refine or customize screeners based on certain sectors.
Multi-Timeframe Continuity Custom Candle ConfirmationMulti-Timeframe Continuity Custom Candle Confirmation
Overview
The Timeframe Continuity Indicator is a versatile tool designed to help traders identify alignment between their current chart’s candlestick direction and higher timeframes of their choice. By coloring bars on the current chart (e.g., 1-minute) based on the directional alignment with selected higher timeframes (e.g., 10-minute, daily), this indicator provides a visual cue for confirming trends across multiple timeframes—a concept known as Timeframe Continuity. This approach is particularly useful for day traders, swing traders, and scalpers looking to ensure their trades align with broader market trends, reducing the risk of trading against the prevailing momentum.
Originality and Usefulness
This indicator is an original creation, built from scratch to address a common challenge in trading: ensuring that price action on a lower timeframe aligns with the trend on higher timeframes. Unlike many trend-following indicators that rely on moving averages, oscillators, or other lagging metrics, this script directly compares the bullish or bearish direction of candlesticks across timeframes. It introduces the following unique features:
Customizable Timeframes: Users can select from a range of higher timeframes (5m, 10m, 15m, 30m, 1h, 2h, 4h, 1d, 1w, 1M) to check for alignment, making it adaptable to various trading styles.
Neutral Candle Handling: The script accounts for neutral candles (where close == open) on the current timeframe by allowing them to inherit the direction of the higher timeframe, ensuring continuity in trend visualization.
Table: A table displays the direction of each selected timeframe and the current timeframe, helping identify direction in the event you don't want to color bars.
Toggles for Flexibility: Options to disable bar coloring and the debug table allow users to customize the indicator’s visual output for cleaner charts or focused analysis.
This indicator is not a mashup of existing scripts but a purpose-built tool to visualize timeframe alignment directly through candlestick direction, offering traders a straightforward way to confirm trend consistency.
What It Does
The Timeframe Continuity Indicator colors bars on your chart when the direction of the current timeframe’s candlestick (bullish, bearish, or neutral) aligns with the direction of the selected higher timeframes:
Lime: The current bar (e.g., 1m) is bullish or neutral, and all selected higher timeframes (e.g., 10m) are bullish.
Pink: The current bar is bearish or neutral, and all selected higher timeframes are bearish.
Default Color: If the directions don’t align (e.g., 1m bar is bearish but 10m is bullish), the bar remains the default chart color.
The indicator also includes a debug table (toggleable) that shows the direction of each selected timeframe and the current timeframe, helping traders diagnose alignment issues.
How It Works
The script uses the following methodology:
1. Direction Calculation: For each timeframe (current and selected higher timeframes), the script determines the candlestick’s direction:
Bullish (1): close > open / Bearish (-1): close < open / Neutral (0): close == open
Higher timeframe directions are fetched using Pine Script’s request.security function, ensuring accurate data retrieval.
2. Alignment Check: The script checks if all selected higher timeframes are uniformly bullish (full_bullish) or bearish (full_bearish).
o A higher timeframe must have a clear direction (bullish or bearish) to trigger coloring. If any selected timeframe is neutral, alignment fails, and no coloring occurs.
3. Coloring Logic: The current bar is colored only if its direction aligns with the higher timeframes:
Lime if the higher timeframes are bullish and the current bar is bullish or neutral.
Maroon if the higher timeframes are bearish and the current bar is bearish or neutral.
If the current bar’s direction opposes the higher timeframe (e.g., 1m bearish, 10m bullish), the bar remains uncolored.
Users can disable bar coloring entirely via the settings, leaving bars in their default chart color.
4. Direction Table:
A table in the top-right corner (toggleable) displays the direction of each selected timeframe and the current timeframe, using color-coded labels (green for bullish, red for bearish, gray for neutral).
This feature helps traders understand why a bar is or isn’t colored, making the indicator accessible to users unfamiliar with Pine Script.
How to Use
1. Add the Indicator: Add the "Timeframe Continuity Indicator" to your chart in TradingView (e.g., a 1m chart of SPY).
2. Configure Settings:
Timeframe Selection: Check the boxes for the higher timeframes you want to compare against (default: 10m). Options include 5m, 10m, 15m, 30m, 1h, 2h, 4h, 1D, 1W, and 1M. Select multiple timeframes if you want to ensure alignment across all of them (e.g., 10m and 1d).
Enable Bar Coloring: Default: true (bars are colored lime or maroon when aligned). Set to false to disable coloring and keep the default chart colors.
Show Table: Default: true (table is displayed in the top-right corner). Set to false to hide the table for a cleaner chart.
3. Interpret the Output:
Colored Bars: Lime bars indicate the current bar (e.g., 1m) is bullish or neutral, and all selected higher timeframes are bullish. Maroon bars indicate the current bar is bearish or neutral, and all selected higher timeframes are bearish. Uncolored bars (default chart color) indicate a mismatch (e.g., 1m bar is bearish while 10m is bullish) or no coloring if disabled.
Direction Table: Check the table to see the direction of each selected timeframe and the current timeframe.
4. Example Use Case:
On a 1m chart of SPY, select the 10m timeframe.
If the 10m timeframe is bearish, 1m bars that are bearish or neutral will color maroon, confirming you’re trading with the higher timeframe’s trend.
If a 1m bar is bullish while the 10m is bearish, it remains uncolored, signaling a potential misalignment to avoid trading.
Underlying Concepts
The indicator is based on the concept of Timeframe Continuity, a strategy used by traders to ensure that price action on a lower timeframe aligns with the trend on higher timeframes. This reduces the risk of entering trades against the broader market direction. The script directly compares candlestick directions (bullish, bearish, or neutral) rather than relying on lagging indicators like moving averages or RSI, providing a real-time, price-action-based confirmation of trend alignment. The handling of neutral candles ensures that minor indecision on the lower timeframe doesn’t interrupt the visualization of the higher timeframe’s trend.
Why This Indicator?
Simplicity: Directly compares candlestick directions, avoiding complex calculations or lagging indicators.
Flexibility: Customizable timeframes and toggles cater to various trading strategies.
Transparency: The debug table makes the indicator’s logic accessible to all users, not just those who can read Pine Script.
Practicality: Helps traders confirm trend alignment, a key factor in successful trading across timeframes.
Breadth-Driven Swing StrategyWhat it does
This script trades the S&P 500 purely on market breadth extremes:
• Data source : INDEX:S5TH = % of S&P 500 stocks above their own 200-day SMA (range 0–100).
• Buy when breadth is washed-out.
• Sell when breadth is overheated.
It is long-only by design; shorting and ATR trailing stops have been removed to keep the logic minimal and transparent.
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Signals in plain English
1. Long entry
A. A 200-EMA trough in breadth is printed and the trough value is ≤ 40 %.
or
B. A 5-EMA trough appears, its prominence passes the user threshold, and the lowest breadth reading in the last 20 bars is ≤ 20 %.
(Toggle this secondary trigger on/off with “ Enter also on 5-EMA trough ”.)
2. Exit (close long)
First 200-EMA peak whose breadth value is ≥ 70 %.
3. Risk control
A fixed stop-loss (% of entry price, default 8 %) is attached to every long trade.
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Key parameters (defaults shown)
• Long EMA length 200 • Short EMA length 5
• Peak prominence 0.5 pct-pts • Trough prominence 3 pct-pts
• Peak level 70 % • Trough level 40 % • 5-EMA trough level 20 %
• Fixed stop-loss 8 %
• “Enter also on 5-EMA trough” = true (allows additional entries on extreme momentum reversals)
Feel free to tighten or relax any of these thresholds to match your risk profile or account for different market regimes.
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How to use it
1. Load the script on a daily SPX / SPY chart.
(The price chart drives order execution; the breadth series is pulled internally and does not need to be on the chart.)
2. Verify the breadth feed.
INDEX:S5TH is updated after each session; your broker must provide it.
3. Back-test across several cycles.
Two decades of daily data is recommended to see how the rules behave in bear markets, range markets, and bull trends.
4. Adjust position sizing in the Properties tab.
The default is “100 % of equity”; change it if you prefer smaller allocations or pyramiding caps.
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Why it can help
• Breadth signals often lead price, allowing entries before index-level momentum turns.
• Simple, rule-based exits prevent “waiting for confirmation” paralysis.
• Only one input series—easy to audit, no black-box math.
Trade-offs
• Relies on a single breadth metric; other internals (advance/decline, equal-weight returns, etc.) are ignored.
• May sit in cash during shallow pullbacks that never push breadth ≤ 40 %.
• Signals arrive at the end of the session (breadth is EoD data).
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Disclaimer
This script is provided for educational purposes only and is not financial advice. Markets are risky; test thoroughly and use your own judgment before trading real money.
ストラテジー概要
本スクリプトは S&P500 のマーケットブレッド（内部需給） だけを手がかりに、指数をスイングトレードします。
• ブレッドデータ : INDEX:S5TH
（S&P500 採用銘柄のうち、それぞれの 200 日移動平均線を上回っている銘柄比率。0–100 %）
• 買い : ブレッドが極端に売られたタイミング。
• 売り : ブレッドが過熱状態に達したタイミング。
余計な機能を削り、ロングオンリー & 固定ストップ のシンプル設計にしています。
⸻
シグナルの流れ
1. ロングエントリー
• 条件 A : 200-EMA がトラフを付け、その値が 40 % 以下
• 条件 B : 5-EMA がトラフを付け、
・プロミネンス条件を満たし
・直近 20 本のブレッドス最小値が 20 % 以下
• B 条件は「5-EMA トラフでもエントリー」を ON にすると有効
2. ロング決済
最初に出現した 200-EMA ピーク で、かつ値が 70 % 以上 のバーで手仕舞い。
3. リスク管理
各トレードに 固定ストップ（初期価格から 8 %）を設定。
⸻
主なパラメータ（デフォルト値）
• 長期 EMA 長さ : 200 • 短期 EMA 長さ : 5
• ピーク判定プロミネンス : 0.5 %pt • トラフ判定プロミネンス : 3 %pt
• ピーク水準 : 70 % • トラフ水準 : 40 % • 5-EMA トラフ水準 : 20 %
• 固定ストップ : 8 %
• 「5-EMA トラフでもエントリー」 : ON
相場環境やリスク許容度に合わせて閾値を調整してください。
⸻
使い方
1. 日足の SPX / SPY チャート にスクリプトを適用。
2. ブレッドデータの供給 (INDEX:S5TH) がブローカーで利用可能か確認。
3. 20 年以上の期間でバックテスト し、強気相場・弱気相場・レンジ局面での挙動を確認。
4. 資金配分 は プロパティ → 戦略実行 で調整可能（初期値は「資金の 100 %」）。
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強み
• ブレッドは 価格より先行 することが多く、天底を早期に捉えやすい。
• ルールベースの出口で「もう少し待とう」と迷わずに済む。
• 入力 series は 1 本のみ、ブラックボックス要素なし。
注意点・弱み
• 単一指標に依存。他の内部需給（A/D ライン等）は考慮しない。
• 40 % を割らない浅い押し目では機会損失が起こる。
• ブレッドは終値ベースの更新。ザラ場中の変化は捉えられない。
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免責事項
本スクリプトは 学習目的 で提供しています。投資助言ではありません。
実取引の前に必ず自己責任で十分な検証とリスク管理を行ってください。
Session Times + Strenght M7This Script Aims to Define Session Times, and Rank those. It can help to adjust your Strategy to Higher Volatility, if you choose to use the Session Volatility and Strenght Index from 1-10. Your timezone on Trading View should be NY. You can customize the Following in Settings: Weight of Volatility & Narrative Regarding the ranking + Transparency of the Lines. SP:SPX FX:EURUSD OANDA:EURUSD CAPITALCOM:USDJPY AMEX:SPY NASDAQ:QQQ TVC:DXY CAPITALCOM:USDJPY CME_MINI:NQ1! OANDA:XAUUSD FX:GBPUSD
BIN Based Support and Resistance [SS]This indicator presents a version of an alternative way to determine support and resistance, using a method called "Bins".
Bins provide for a flexible and interesting way to determine support and resistance levels.
First off, let's discuss BINS:
Bins are ranges or containers into which your data points can be sorted. For example, if you're grouping ages, you might have bins like 0–18, 19–35, 36–50, and 51+. Any data point within these intervals gets placed in the corresponding bin.
Binning simplifies complex data sets by grouping values into categories. This is useful for such things as
Visualizing data in histograms or bar charts.
Reducing noise and highlighting trends.
This indicator groups the price action into 10 separate bins. It determines the Support / Resistance level by averaging the values in the Bins to find an iteration of the "central tendency" or average reoccurring value.
Pros and Cons
Since this is a different approach to support and resistance, I think its important to highlight some of the pros and advantages, but also be open about the cons.
First off the PROS
Bin Based Support and Resistance Levels dynamically adjust to ranges as opposed to hard / fast peaks and valleys. This makes them better at analyzing price action vs simply drawing lines at random peaks and valleys.
Because Bins are analyzing ALL PA within a period's max and min range, Bin Support and Resistance can actually be used similar to Volume profile, where you are able to identify a pseudo-POC, or areas where price tends to consolidate. Take a look at this example on SPY:
You can see these 2 SR lines are close together. This represents that this general price range is an area where price likes to accumulate/consolidate. You can see the SPY ended up coming back to this range and consolidating there for a bit.
This is a strength of using a BIN based approach to calculating support and resistance, because as indicated before, it looks at price action vs peaks and valleys.
As a tip, these areas are areas you want to wait for a break in one direction or the other.
The indicator provides for backtest results of the support and resistance lines, to see how many times certain areas acted as resistance or support. Because this is analyzing and distributing PA evenly throughout the period's max and min, the indicator can tell you which areas tend to have higher rejection zones and which have higher support zones.
Now the CONS
Because bin based SR take an average approach, the SR lines can sometimes be slightly broken before the ticker finds rejection:
To combat this, make sure there is confirmed support. How the indicator actually backtests these lines is by waiting to see if the ticker has 3 consecutive closes above the support line or below the resistance line. So these are things to be mindful of.
It doesn't consider pivots. Most support and resistance indicators either identify max and min peaks and valleys or use pivot points. Pivot points are a great way to identify peaks and valleys and thus by extension support and resistance. However, this is also somewhat of a strength, as using BINS forces the indicator to consider ALL price action and not just the extremes (highs and lows).
Can be slightly skewed in highly volatile environments. Any time there is a massive drop or rally, it can skew the indicator to give extreme ranges to both ends. For example, the Tariff news collapse on ES1!:
Owning to limitations in lookback length, sometimes the min and max range can be exceeded and other traditional areas of support / resistance is where a ticker will find support.
Using the indicator
Here are some basic use/functionalities of the indicator:
Selecting display of backtest results: You can select to have the backtest results shown in a table:
Or directly on the lines:
Inversely, you can toggle them off completely:
You can modify the lookback length. The suggested lookback length is between 250 to 500 candles on smaller timeframes. I also suggest 252 on daily timeframes (which represents 1 trading year).
And that's the indicator!
It is very easy to use, so you should pick it up in no time!
Enjoy and as always, 🚀🚀 safe trades! 🚀🚀
Chop ZonesThis indicator plots two "zones" in the form of shaded boxes, one between PMH and PML and one between PDH and PDL, the area that is shaded more has the highest probability of price action to be "choppy", the lesser shaded area has less probability for "choppy" action whilst outside the shaded areas there is high probability of a trend.
This indicator can be used to determine one of the three types of day:
Chop day
Bullish trend day
Bearish trend day
Chop day example today on AMEX:SPY
Bullish trend day example on NASDAQ:DLTR
Bearish trend day example on NASDAQ:UAL
Normalized Equity/Bond RatioThis indicator calculates a normalized equity-to-bond ratio over a 252-day lookback (~1 trading year) to assess risk-on vs. risk-off sentiment. It addresses the issue of direct ratios (e.g., SPY/TLT) being visually dominated by high nominal stock prices, which can obscure bond price movements.
A rising ratio indicates equities are outperforming bonds, suggesting risk-on conditions, while a declining ratio signals a shift toward bonds, often associated with risk-off behavior. The normalization ensures better visibility and comparability of the trend over time.
A ratio > 1 means the equity (e.g., SPY) is outperforming the bond (e.g., AGG) since the lookback. A ratio < 1 means bonds are outperforming.
15-Minute ORB by @RhinoTradezOverview
Hey traders, ready to jump on the morning breakout train? The 15-Minute ORB by @RhinoTradez
is your go-to pal for rocking the Opening Range Breakout (ORB) scene, zeroing in on the first 15 minutes of the U.S. market day—9:30 to 9:45 AM Eastern Time. Picture this: sleek orange lines mark the high and low of that opening rush, but they only hang out during regular trading hours (9:30 AM-4:00 PM ET) and reset fresh each day—no old baggage here! Built in Pine Script v6 for that cutting-edge feel, it’s loaded with breakout signals and alerts to keep your trading game strong—ideal for SPY, QQQ, or any ticker you love.
Crafted by @RhinoTradez
to fuel your daily grind—let’s hit those breakouts running!
What It Does
The ORB strategy is all about that early market spark: the 9:30-9:45 AM range sets the battlefield, and breakouts signal the charge. Here’s the rundown:
Captures the Range : Snags the high and low from the 9:30-9:45 AM ET candle—U.S. market kickoff, locked in.
Daily Refresh : Wipes yesterday’s lines at 9:30 AM ET each day—today’s all that matters.
Regular Hours Focus : Orange lines shine from 9:45 AM to 4:00 PM ET, vanishing outside those hours.
Breakout Signals : Green triangles for upside breaks, red for downside, all within regular hours.
Alerts You : Chimes in with “Price broke above 15-min ORB High: 597” (or below the low) when the move hits.
It’s your morning breakout blueprint—simple, focused, and trader-ready.
Functionality Breakdown:
15-Minute ORB Snap:
Locks the high and low of the 9:30-9:45 AM ET candle on a 15-minute chart (EST/EDT auto-adjusted).
Resets daily at 9:30 AM ET—yesterday’s range is outta here.
Regular Hours Only:
Lines glow from 9:45 AM to 4:00 PM ET, keeping pre-market and after-hours clean.
Breakout Flags:
Marks price busting above the ORB high (green triangle below bar) or below the low (red triangle above), only during 9:30 AM-4:00 PM.
Alert Action:
Drops a custom alert with the breakout price (e.g., “Price broke below 15-min ORB Low: 594”)—stay in the know, hands-free.
Customization Options
Keep it chill with one slick tweak:
ORB Line Color : Starts at orange—vibrant and trader-cool! Flip it to blue, purple, or any shade you dig in the settings. Make it yours.
How to Use It
Pop It On: Add it to a 15-minute chart—SPY, QQQ, or your hot pick works like a dream.
Time It Right: Set your chart to “America/New_York” time (Chart Settings > Time Zone) to sync with 9:30 AM ET.
Choose Your Color: Dive into the indicator settings and pick your ORB line color—orange kicks it off, but you’re in charge.
Set Alerts: Right-click the indicator, add an alert with “Any alert() function call,” and catch breakouts live.
Ride the Wave: Green triangle? Upward vibe. Red? Downside alert. Mix with volume or candles for extra punch.
Pro Tips
15-Minute Only : Tailored for that 9:30-9:45 AM ET candle—other timeframes won’t sync up.
Daily Reset : Lines refresh at 9:30 AM ET—always today’s play.
Breakout Boost : High volume or RSI can seal the deal on those triangle signals.
No Clutter : Lines stick to 9:30 AM-4:00 PM ET—your chart stays tidy.
Brought to you by @RhinoTradez
in Pine Script v6, this ORB script’s your morning breakout wingman. Slap it on, pick a color, and let’s chase those moves together! Happy trading!
IronCondor 10am 30TF by RMThe IronCondor 10am 30TF indicator shows Iron Condor trades win rate over a large number of days.
The default ETFs in this indicators are "QQQ", "SPY", "RUT" , "CBTX" and "SPX", other entries have not been tested.
Iron Condor quick explanation:
- Iron Condors trades have four options, generally, are based around a Midpoint price (Current Market Price Strike) and
- Two equally distances Strikes for the SELL components (called the Body of the Iron Condor)
- Further away from the two SELLs, another Two BUYs for protection (not considered in this indicator)
- Iron Condors are used for Passive Income based on small gains most of the time.
The IronCondor 10am 30TF has its logic created based on the premises that:
- Most days the market prices stay within a range.
- As example the S&P market prices would stay within 1% on about 80% of the time
- The moving markets (bullish or bearish) occur about 20% of the time
- The biggest market price volatility generally occurs before market opens and then around the first hour or so of trade in the day.
- After the first hour or so of the market the prices would be most likely to stay within a range.
The operation is simple:
- At the Trade Star time in the day (say 10:30 Hrs.) draws a vertical yellow line, then
- Creates two blue horizontal lines for the SELL limits in the Iron Condor Body, at +/- 1% price boundary (check Ticker list below for values)
- At the Trade End time (say 16:00 Hrs.) checks that none of the SELL limits have been broken by highs or lows during the trade day
(The check is done calculating at Trade End time the high/lows 10 bars back for 30 min TF - timeframe)
- There is a label at each Trade End time with Win/Loss and Body value.
- There is one final label with overall calculated past performance in Win percentage out of 'n' trades
Defaults and User Entries:
- The User can modify the Midpoint price called 'IronCondor Midpoint STRIKE' (default is the Candle Close at the selected time)
- The User can modify the Body value called 'IronCondor Body' (default is the Ticker's selected value as per list below)
"QQQ" or "SPY" Body = 5
"RUT" or "CBTX" Body = 20
"SPX" Body = 60
* Disclaimer: This is not a Financial tool, it cannot used as any kind of advice to invest or risk moneys in any market,
Markets are volatile in nature - with little or no warning - and will drain your account if you are not careful.
Use only as an academic demonstrator => * Use at your own risk *
FACTOR MONITORThe Factor Monitor is a comprehensive designed to track relative strength and standard deviation movements across multiple market segments and investment factors. The indicator calculates and displays normalized percentage moves and their statistical significance (measured in standard deviations) across daily, 5-day, and 20-day periods, providing a multi-timeframe view of market dynamics.
Key Features:
Real-time tracking of relative performance between various ETF pairs (e.g., QQQ vs SPY, IWM vs SPY)
Standard deviation scoring system that identifies statistically significant moves
Color-coded visualization (green/red) for quick interpretation of relative strength
Multiple timeframe analysis (1-day, 5-day, and 20-day moves)
Monitoring of key market segments:
Style factors (Value, Growth, Momentum)
Market cap segments (Large, Mid, Small)
Sector relative strength
Risk factors (High Beta vs Low Volatility)
Credit conditions (High Yield vs Investment Grade)
The tool is particularly valuable for:
Identifying significant factor rotations in the market
Assessing market breadth through relative strength comparisons
Spotting potential trend changes through statistical deviation analysis
Monitoring sector leadership and market regime shifts
Quantifying the magnitude of market moves relative to historical norms
Employee Portfolio Generator [By MUQWISHI]▋ INTRODUCTION :
The “Employee Portfolio Generator” simplifies the process of building a long-term investment portfolio tailored for employees seeking to build wealth through investments rather than traditional bank savings. The tool empowers employees to set up recurring deposits at customizable intervals, enabling to make additional purchases in a list of preferred holdings, with the ability to define the purchasing investment weight for each security. The tool serves as a comprehensive solution for tracking portfolio performance, conducting research, and analyzing specific aspects of portfolio investments. The output includes an index value, a table of holdings, and chart plots, providing a deeper understanding of the portfolio's historical movements.
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▋ OVERVIEW:
● Scenario (The chart above can be taken as an example) :
Let say, in 2010, a newly employed individual committed to saving $1,000 each month. Rather than relying on a traditional savings account, chose to invest the majority of monthly savings in stable well-established stocks. Allocating 30% of monthly saving to AMEX:SPY and another 30% to NASDAQ:QQQ , recognizing these as reliable options for steady growth. Additionally, there was an admired toward innovative business models of NASDAQ:AAPL , NASDAQ:MSFT , NASDAQ:AMZN , and NASDAQ:EBAY , leading to invest 10% in each of those companies. By the end of 2024, after 15 years, the total monthly deposits amounted to $179,000, which would have been the result of traditional saving alone. However, by sticking into long term invest, the value of the portfolio assets grew, reaching nearly $900,000.
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▋ OUTPUTS:
The table can be displayed in three formats:
1. Portfolio Index Title: displays the index name at the top, and at the bottom, it shows the index value, along with the chart timeframe, e.g., daily change in points and percentage.
2. Specifications: displays the essential information on portfolio performance, including the investment date range, total deposits, free cash, returns, and assets.
3. Holdings: a list of the holding securities inside a table that contains the ticker, last price, entry price, return percentage of the portfolio's total deposits, and latest weighted percentage of the portfolio. Additionally, a tooltip appears when the user passes the cursor over a ticker's cell, showing brief information about the company, such as the company's name, exchange market, country, sector, and industry.
4. Indication of New Deposit: An indication of a new deposit added to the portfolio for additional purchasing.
5. Chart: The portfolio's historical movements can be visualized in a plot, displayed as a bar chart, candlestick chart, or line chart, depending on the preferred format, as shown below.
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▋ INDICATOR SETTINGS:
Section(1): Table Settings
(1) Naming the index.
(2) Table location on the chart and cell size.
(3) Sorting Holdings Table. By securities’ {Return(%) Portfolio, Weight(%) Portfolio, or Ticker Alphabetical} order.
(4) Choose the type of index: {Assets, Return, or Return (%)}, and the plot type for the portfolio index: {Candle, Bar, or Line}.
(5) Positive/Negative colors.
(6) Table Colors (Title, Cell, and Text).
(7) To show/hide any of selected indicator’s components.
Section(2): Recurring Deposit Settings
(1) From DateTime of starting the investment.
(2) To DateTime of ending the investment
(3) The amount of recurring deposit into portfolio and currency.
(4) The frequency of recurring deposits into the portfolio {Weekly, 2-Weeks, Monthly, Quarterly, Yearly}
(5) The Depositing Model:
● Fixed: The amount for recurring deposits remains constant throughout the entire investment period.
● Increased %: The recurring deposit amount increases at the selected frequency and percentage throughout the entire investment period.
(5B) If the user selects “ Depositing Model: Increased % ”, specify the growth model (linear or exponential) and define the rate of increase.
Section(3): Portfolio Holdings
(1) Enable a ticker in the investment portfolio.
(2) The selected deposit frequency weight for a ticker. For example, if the monthly deposit is $1,000 and the selected weight for XYZ stock is 30%, $300 will be used to purchase shares of XYZ stock.
(3) Select up to 6 tickers that the investor is interested in for long-term investment.
Please let me know if you have any questions
Real Relative Strength Indicator (Multi-Index Comparison)The Real Relative Strength (RRS) indicator implements the "Real Relative Strength" equation, as detailed on the Real Day Trading subreddit wiki. This equation measures whether a stock is outperforming a benchmark (such as SPY or any preferred ETF/index) by calculating price change normalized by the Average True Range (ATR) of both the stock and the indices it’s being compared to.
The RRS metric often highlights potential accumulation by institutional players. For example, in this chart, you can observe accumulation in McDonald’s beginning at 1:25 pm ET on the 5-minute chart and continuing until 2:55 pm ET. When used in conjunction with other indicators or technical analysis, RRS can provide valuable buy and sell signals.
This indicator also supports multi-index analysis, allowing you to plot relative strength against two indices simultaneously—defaulting to SPY and QQQ—to gain insights into the "real relative strength" across different benchmarks. Additionally, this indicator includes an EMA line and background coloring to help automatically identify relative strength trends, providing a clearer visualization than typical Relative Strength Comparison indicators.
