Static Beta for Pair and Quant Trading A beta coefficient shows the volatility of an individual stock compared to the systematic risk of the entire market. Beta represents the slope of the line through a regression of data points. In finance, each point represents an individual stock's returns against the market.
Beta effectively describes the activity of a security's returns as it responds to swings in the market. It is used in the capital asset pricing model (CAPM), which describes the relationship between systematic risk and expected return for assets. CAPM is used to price risky securities and to estimate the expected returns of assets, considering the risk of those assets and the cost of capital.
Calculating Beta
A security's beta is calculated by dividing the product of the covariance of the security's returns and the market's returns by the variance of the market's returns over a specified period. The calculation helps investors understand whether a stock moves in the same direction as the rest of the market. It also provides insights into how volatile—or how risky—a stock is relative to the rest of the market.
For beta to provide useful insight, the market used as a benchmark should be related to the stock. For example, a bond ETF's beta with the S&P 500 as the benchmark would not be helpful to an investor because bonds and stocks are too dissimilar.
Beta Values
Beta equal to 1: A stock with a beta of 1.0 means its price activity correlates with the market. Adding a stock to a portfolio with a beta of 1.0 doesn’t add any risk to the portfolio, but it doesn’t increase the likelihood that the portfolio will provide an excess return.
Beta less than 1: A beta value less than 1.0 means the security is less volatile than the market. Including this stock in a portfolio makes it less risky than the same portfolio without the stock. Utility stocks often have low betas because they move more slowly than market averages.
Beta greater than 1: A beta greater than 1.0 indicates that the security's price is theoretically more volatile than the market. If a stock's beta is 1.2, it is assumed to be 20% more volatile than the market. Technology stocks tend to have higher betas than the market benchmark. Adding the stock to a portfolio will increase the portfolio’s risk, but may also increase its return.
Negative beta: A beta of -1.0 means that the stock is inversely correlated to the market benchmark on a 1:1 basis. Put options and inverse ETFs are designed to have negative betas. There are also a few industry groups, like gold miners, where a negative beta is common.
LET'S START
Now I'll give my own definition.
Beta:
If we assume market caps are equal ,
it is an indicator that shows how much of the second instrument we should buy if we buy one of the first, taking into account the price volatility of two instruments.
But if the market caps are not equal:
For example, the ETF for A is $300.
The ETF for B is $600.
If static beta predicted by this script is 0.5:
300 * 1 * a = 600 * 0.5 * b
Then we should use 1 b for 1 a.
(Long a and short b or vice versa )
So, we can try pair trading for a/b or a-b.
However, these values are generally close to each other, such as 0.8 and 0.93. However, the closer we can adjust our lot purchases to bring the double beta to a value closer to 1, the higher the hedge ratio will be.
Large commercials use dynamic betas, which are updated periodically, in addition to static betas
However, scaling this is very difficult for individual investors with limited investment tools.
But a static beta of 5,000 bars is still much better than not considering any beta at all.
Note: The presence of a beta value for two instruments does not necessarily mean they can be included in pair trading.
It is also important (%99) to consider historically very high correlations and cointegration relationships, as well as the compatibility of security structures.
Note 2 : This script is designed for low timeframes.
Do not use betas from different timeframes.
Beta dynamics are different for each timeframe.
Note 3 : I created this script with the help of ChatGPT.
Source for beta definition ( ) :
www.investopedia.com
Regards. Indicator
Indicator
Pairs Trading Scanner [BackQuant]Pairs Trading Scanner
What it is
This scanner analyzes the relationship between your chart symbol and a chosen pair symbol in real time. It builds a normalized “spread” between them, tracks how tightly they move together (correlation), converts the spread into a Z-Score (how far from typical it is), and then prints clear LONG / SHORT / EXIT prompts plus an at-a-glance dashboard with the numbers that matter.
Why pairs at all?
Markets co-move. When two assets are statistically related, their relationship (the spread) tends to oscillate around a mean.
Pairs trading doesn’t require calling overall market direction you trade the relative mispricing between two instruments.
This scanner gives you a robust, visual way to find those dislocations, size their significance, and structure the trade.
How it works (plain English)
Step 1 Pick a partner: Select the Pair Symbol to compare against your chart symbol. The tool fetches synchronized prices for both.
Step 2 Build a spread: Choose a Spread Method that defines “relative value” (e.g., Log Spread, Price Ratio, Return Difference, Price Difference). Each lens highlights a different flavor of divergence.
Step 3 Validate relationship: A rolling Correlation checks if the pair is moving together enough to be tradable. If correlation is weak, the scanner stands down.
Step 4 Standardize & score: The spread is normalized (mean & variability over a lookback) to form a Z-Score . Large absolute Z means “stretched,” small means “near fair.”
Step 5 Signals: When the Z-Score crosses user-defined thresholds with sufficient correlation , entries print:
LONG = long chart symbol / short pair symbol,
SHORT = short chart symbol / long pair symbol,
EXIT = mean reversion into the exit zone or correlation failure.
Core concepts (the three pillars)
Spread Method Your definition of “distance” between the two series.
Guidance:
Log Spread: Focuses on proportional differences; robust when prices live on different scales.
Price Ratio: Classic relative value; good when you care about “X per Y.”
Return Difference: Emphasizes recent performance gaps; nimble for momentum-to-mean plays.
Price Difference: Straight subtraction; intuitive for similar-scale assets (e.g., two ETFs).
Correlation A rolling score of co-movement. The scanner requires it to be above your Min Correlation before acting, so you’re not trading random divergence.
Z-Score “How abnormal is today’s spread?” Positive = chart richer than pair; negative = cheaper. Thresholds define entries/exits with transparent, statistical context.
What you’ll see on the chart
Correlation plot (blue line) with a dashed Min Correlation guide. Above the line = green zone for signals; below = hands off.
Z-Score plot (white line) with colored, dashed Entry bands and dotted Exit bands. Zero line for mean.
Normalized spread (yellow) for a quick “shape read” of recent divergence swings.
Signal markers :
LONG (green label) when Z < –Entry and corr OK,
SHORT (red label) when Z > +Entry and corr OK,
EXIT (gray label) when Z returns inside the Exit band or correlation drops below the floor.
Background tint for active state (faint green for long-spread stance, faint red for short-spread stance).
The two built-in dashboards
Statistics Table (top-right)
Pair Symbol Your chosen partner.
Correlation Live value vs. your minimum.
Z-Score How stretched the spread is now.
Current / Pair Prices Real-time anchors.
Signal State NEUTRAL / LONG / SHORT.
Price Ratio Context for ratio-style setups.
Analysis Table (bottom-right)
Avg Correlation Typical co-movement level over your window.
Max |Z| The recent extremes of dislocation.
Spread Volatility How “lively” the spread has been.
Trade Signal A human-readable prompt (e.g., “LONG A / SHORT B” or “NO TRADE” / “LOW CORRELATION”).
Risk Level LOW / MEDIUM / HIGH based on current stretch (absolute Z).
Signals logic (plain English)
Entry (LONG): The spread is unusually negative (chart cheaper vs pair) and correlation is healthy. Expect mean reversion upward in the spread: long chart, short pair.
Entry (SHORT): The spread is unusually positive (chart richer vs pair) and correlation is healthy. Expect mean reversion downward in the spread: short chart, long pair.
Exit: The spread relaxes back toward normal (inside your exit band), or correlation deteriorates (relationship no longer trusted).
A quick, repeatable workflow
1) Choose your pair in context (same sector/theme or known macro link). Think: “Do these two plausibly co-move?”
2) Pick a spread lens that matches your narrative (ratio for relative value, returns for short-term performance gaps, etc.).
3) Confirm correlation is above your floor no corr, no trade.
4) Wait for a stretch (Z beyond Entry band) and a printed LONG / SHORT .
5) Manage to the mean (EXIT band) or correlation failure; let the scanners’ state/labels keep you honest.
Settings that matter (and why)
Spread Method Defines the “mispricing” you care about.
Correlation Period Longer = steadier regime read, shorter = snappier to regime change.
Z-Score Period The window that defines “normal” for the spread; it sets the yardstick.
Use Percentage Returns Normalizes series when using return-based logic; keep on for mixed-scale assets.
Entry / Exit Thresholds Set your stretch and your target reversion zone. Wider entries = rarer but stronger signals.
Minimum Correlation The gatekeeper. Raising it favors quality over quantity.
Choosing pairs (practical cheat sheet)
Same family: two index ETFs, two oil-linked names, two gold miners, two L1 tokens.
Hedge & proxy: stock vs. sector ETF, BTC vs. BTC index, WTI vs. energy ETF.
Cross-venue or cross-listing: instruments that are functionally the same exposure but price differently intraday.
Reading the cues like a pro
Divergence shape: The yellow normalized spread helps you see rhythm fast spike and snap-back versus slow grind.
Corr-first discipline: Don’t fight the “Min Correlation” line. Good pairs trading starts with a relationship you can trust.
Exit humility: When Z re-centers, let the EXIT do its job. The edge is the journey to the mean, not overstaying it.
Frequently asked (quick answers)
“Long/Short means what exactly?”
LONG = long the chart symbol and short the pair symbol.
SHORT = short the chart symbol and long the pair symbol.
“Do I need same price scales?” No. The spread methods normalize in different ways; choose the one that fits your use case (log/ratio are great for mixed scales).
“What if correlation falls mid-trade?” The scanner will neutralize the state and print EXIT . Relationship first; trade second.
Field notes & patterns
Snap-back days: After a one-sided session, return-difference spreads often flag cleaner intraday mean reversions.
Macro rotations: Ratio spreads shine during sector re-weights (e.g., value vs. growth ETFs); look for steady corr + elevated |Z|.
Event bleed-through: If one symbol reacts to news and its partner lags, Z often flags a high-quality, short-horizon re-centering.
Display controls at a glance
Show Statistics Table Live state & key numbers, top-right.
Show Analysis Table Context/risk read, bottom-right.
Show Correlation / Spread / Z-Score Toggle the sub-charts you want visible.
Show Entry/Exit Signals Turn markers on/off as needed.
Coloring Adjust Long/Short/Neutral and correlation line colors to match your theme.
Alerts (ready to route to your workflow)
Pairs Long Entry Z falls through the long threshold with correlation above minimum.
Pairs Short Entry Z rises through the short threshold with correlation above minimum.
Pairs Trade Exit Z returns to neutral or the relationship fails your correlation floor.
Correlation Breakdown Rolling correlation crosses your minimum; relationship caution.
Final notes
The scanner is designed to keep you systematic: require relationship (correlation), quantify dislocation (Z-Score), act when stretched, stand down when it normalizes or the relationship degrades. It’s a full, visual loop for relative-value trading that stays out of your way when it should and gets loud only when the numbers line up.
Indicator
Market Strength Buy Sell Indicator [TradeDots]A specialized tool designed to assist traders in evaluating market conditions through a multifaceted analysis of relative performance, beta-adjusted returns, momentum, and volume—allowing you to identify optimal points for long or short trades. By integrating multiple benchmarks (default S&P 500) and percentile-based thresholds, the script provides clear, actionable insights suitable for both day trading and higher-level timeframe assessments.
📝 HOW IT WORKS
1. Multi-Factor Composite Score
Relative Performance (RS Ratio): Compares your asset’s performance to a chosen benchmark (default: SPY). Values above 1.0 indicate outperformance, while below 1.0 suggest underperformance.
Beta-Adjusted Returns: Checks the ticker’s excess movement relative to expected market-related moves. This helps distinguish pure “alpha” from broad market effects.
Volume & Correlation: Volume spikes often confirm the momentum behind a move, while correlation measures how closely the asset tracks or diverges from its benchmark.
These components merge into a 0–100 composite score. Scores above 50 frequently imply bullish strength; drops below 50 often point to underperformance—potentially flagging short opportunities.
2. Intraday & Day Trading Focus
Monitoring Below 50: During the trading day, the script calculates live data against the benchmark, offering an intraday-sensitive composite score. A dip under 50 may indicate a short bias for that session, especially when accompanied by high volume or momentum shifts.
3. Higher Timeframe Monitoring
Daily Strategies: On daily or weekly charts, the script reveals overall relative strength or weakness compared to the S&P 500. This higher-level perspective helps form broader trading biases—crucial for swing or position trades spanning multiple days.
Long/Short Thresholds: Persistent readings above 50 on a daily chart typically reinforce a long bias, while consistent dips below 50 can sustain a short or cautious outlook.
4. Pair Trading Applications
Custom Benchmark Selection: By setting a specific ticker pair as your benchmark instead of the default S&P 500, you can identify spread trading opportunities between two correlated assets. This allows you to go long the outperforming asset while shorting the underperforming one when the spread reaches extreme levels.
4. Color-Coded Signals & Alerts
Visual Zones (25–75): Color-coded bands highlight strong outperformance (above 75) or pronounced underperformance (below 25).
Alerts on Strong Shifts: Automatic alerts can notify you of sudden entries or exits from bullish or bearish zones, so you can potentially act on new market information without delay.
⚙️ HOW TO USE
1. Select Your Timeframe: For scalping or day trading, lower intervals (e.g., 5-minute) offer immediate data resets at the session’s start. For multi-day insight, daily or weekly charts reveal broader performance trends.
2. Watch Key Levels Around 50: Intraday dips under 50 may be a cue to consider short trades, while bounces above 50 can confirm renewed strength.
3. Assess Benchmark Relationships: Compare your asset’s score and signals to the broader market. A stock falling below its pair’s relative strength line might lag overall market momentum.
4. Combine Tools & Validate: This script excels when integrated with other technical analysis methods (e.g., support/resistance, chart patterns) and fundamental factors for a holistic market view.
❗ LIMITATIONS
No Direction Guarantee: The indicator identifies relative strength but does not guarantee directional price moves.
Delayed Updates: Since calculations update after each bar close, sudden intrabar changes may not immediately reflect.
Market-Specific Behaviors: Some assets or unusual market conditions may deviate from typical benchmarks, weakening signal reliability.
Past ≠ Future: High or low relative strength in the past may not predict continued performance.
RISK DISCLAIMER
All forms of trading and investing involve risk, including the possible loss of principal. This indicator analyzes relative performance but cannot assure profits or eliminate losses. Past performance of any strategy does not guarantee future results. Always combine analysis with proper risk management and your broader trading plan. Consult a licensed financial advisor if you are unsure of your individual risk tolerance or investment objectives. Indicator
Indicator
Statistical Pairs Trading IndicatorZ-Score Stat Trading — Statistical Pairs Trading Indicator
📊🔗
---
What is it?
Z-Score Stat Trading is a powerful indicator for statistical pairs trading and quantitative analysis of two correlated assets.
It calculates the Z-Score of the log-price spread between any two symbols you choose, providing both long-term and short-term Z-Score signals.
You’ll also see real-time correlation, volatility, spread, and the number of long/short signals in a handy on-chart table!
---
How to Use 🛠️
1. Add the indicator to your chart.
2. Select two assets (symbols) to analyze in the settings.
3. Watch the Z-Score plots (blue and orange lines) and threshold levels (+2, -2 by default).
4. Check the info table for:
- Correlation
- Volatility
- Spread
- Number of long (NL) and short (NS) signals in the last 1000 bars
5. Set up alerts for signal generation or threshold crossings if you want to be notified automatically.
---
Trading Strategy 💡
- This indicator is designed for statistical arbitrage (mean reversion) strategies.
- Long Signal (🟢):
When both Z-Scores drop below the negative threshold (e.g., -2), a long signal is generated.
→ Buy Symbol A, Sell Symbol B, expecting the spread to revert to the mean.
- Short Signal (🔴):
When both Z-Scores rise above the positive threshold (e.g., +2), a short signal is generated.
→ Sell Symbol A, Buy Symbol B, again expecting mean reversion.
- The info table helps you quickly assess the frequency of signals and the current statistical relationship between your chosen assets.
---
Best Practices & Warnings 🚦
- Avoid high leverage! Pairs trading can be risky, especially during periods of divergence. Use conservative position sizing.
- Check for cointegration: Before using this indicator, make sure both assets are cointegrated or have a strong historical relationship. This increases the reliability of mean reversion signals.
- Check correlation: Only use asset pairs with a high correlation (preferably 0.8–0.9 or higher) for best results. The correlation value is shown in the info table.
- Scale in and out gradually: When entering or exiting positions, consider doing so in parts rather than all at once. This helps manage slippage and risk, especially in volatile markets.
---
⚠️ Note on Performance:
This indicator may work a bit slowly, especially on large timeframes or long chart histories, because the calculation of NL and NS (number of long/short signals) is computationally intensive.
---
Disclaimer ⚠️
This script is provided for educational and informational purposes only .
It is not financial advice or a recommendation to buy or sell any asset.
Use at your own risk. The author assumes no responsibility for any trading decisions or losses.
Indicator
Indicator
Strategy
Symbols Correlation, built for pair tradingOverview:
This script is designed for pairs trading. If you are not familiar with pairs trading, I suggest learning about it, as it can be a profitable strategy in neutral markets (or neutral trends between two assets). The correlation between two assets is the foundation of pairs trading, and without it, the chances of making a profit are low.
Correlation can be described in two opposite ways:
1: Absolute positive correlation (meaning the asset prices move together).
-1: Absolute negative correlation (meaning the asset prices move in opposite directions).
Any value between 1 and -1 indicates some degree of correlation, but generally, values higher than 0.7 or lower than -0.7 are considered significant.
Features:
Typically, correlation is measured using the closing prices. This script adds three more correlation studies based on open, high, and low prices. By using all four lines, we can get a better understanding of the pair's correlation.
How to Read This Indicator:
To use this indicator effectively, you need to input your pair as a ratio. For example, if your pair is TSN and ZBH, enter it in the symbol search as: TSN/ZBH
Gray Area : This area indicates "no high correlation" (default is between -0.8 and 0.8, adjustable in the settings).
Gray Line : This represents the close correlation within the "no high correlation" range.
Green Line : This represents the close correlation within the "high correlation" range.
Dot Lines : These represent the open, high, and low correlations.
Example Interpretations:
A : All four lines are close together & the line is green – very good correlation!
B : The line is gray, and the dot lines are apart – not a strong correlation.
C : When the close correlation remains green for a long time, it signals a strong correlation.
Application in Pairs Trading:
In pairs trading, aim for the highest possible correlation, and it is important to have a sustained correlation over a long period. Pairs that correlate only part of the year but not consistently are less reliable for pairs trading.
This is an example for good correlation for pairs trading:
This is an example for bad correlation for pairs trading:
Here is a view of my full indicators when doing pairs trading:
Indicator
Trend Momentum Strength Indicator, Built for Pairs TradingOverview:
This script combines multiple indicators to provide a comprehensive analysis of both trend strength and trend momentum. It is tailored specifically for pairs trading strategies but can also be used for other trading strategies.
Benefit of Comprehensive Analysis:
Having an indicator that evaluates both trend strength and trend momentum is crucial for traders looking to make informed decisions. It allows traders to not only identify the direction and intensity of a trend but also gauge the momentum behind it. This dual capability helps in confirming potential trade opportunities, whether for entering trades with strong trends or considering reversals during overbought or oversold conditions. By integrating both aspects into one tool, traders can gain a holistic view of market dynamics, enhancing their ability to time entries and manage risk effectively.
Features:
* Trend Strength:
Enhanced ADX Formula: The script includes modifications to the standard ADX formula along with DI+ and DI- to provide more responsive trend strength readings.
Directional Indicators: DI+ (green line) indicates positive directional movement, while DI- (red line) indicates negative directional movement.
Trend Momentum:
Modified Stochastic Indicators: The script uses %K and %D indicators, modified and combined with ADX to give a clear indication of trend momentum.
Momentum Strength: This helps determine the strength and direction of the momentum.
Trading Signals:
Combining Indicators: The script combines ADX, DI+, DI-, %K, and %D to generate comprehensive trading signals.
Optimal Entry Points: Designed to identify optimal entry points for trades, particularly in pairs trading.
Colored Area at Bottom:
This area provides two easy-to-read functions:
Color:
Green: Upward momentum (ratio above 1)
Red: Downward momentum (ratio below 1)
Height:
Higher in green: Stronger upward momentum
Lower in red: Stronger downward momentum
Legend:
Green Line: DI+ (Positive)
Red Line: DI- (Negative)
Black Line: ADX
How to Read This Indicator:
1) Trend Direction:
DI+ above DI-: Indicates an upward trend.
DI- above DI+: Indicates a downward trend.
2) Trend Strength:
ADX below 20: Indicates a neutral trend.
ADX between 20 and 25: Indicates a weak trend.
ADX above 25: Indicates a strong trend.
Trading Signals in Pairs Trading:
Neutral Trend: Ideal for pairs trading when no strong trend is detected.
Overbought/Oversold: Uses %K and %D to identify overbought/oversold conditions that support trade decisions.
Entry Signals: Green signals for long positions, red signals for short positions, based on combined criteria of neutral trend strength and supportive momentum.
Application in Pairs Trading:
Neutral trend: In pairs trading strategies, where neutral movement is often sought, this indicator provides signals that are especially relevant during periods of neutral trend strength and supportive momentum, aiding traders in identifying optimal entry
Risk Management: Combining signals from ADX, DI+, DI-, %K, and %D helps traders make more informed decisions regarding entry points, enhancing risk management.
Example Chart (The indicator is on the upper right corner):
Clean Presentation: The chart only includes the necessary elements to demonstrate the indicator’s functionality.
Demonstrates: Overbought/oversold conditions, upward/downward/no momentum, and trading signals with/without specific scenarios.
Indicator
Indicator
Indicator
Indicator
Strategy
TASC 2022.07 Pairs Rotation With Ehlers Loops█ OVERVIEW
TASC's July 2022 edition of Traders' Tips includes an article by John Ehlers titled "Pairs Rotation With Ehlers Loops". This is the code that implements the Ehlers Loops applied to pairs rotation trading.
█ CONCEPTS
John Ehlers developed Ehlers loops as a tool to visualize the performance of one data stream versus another. Initially, he used this tool to chart price versus volume. However, Ehlers loops proved to be suitable for determining the timing of the pairs rotation strategy . This strategy works by having a long position in only one of two securities, depending on which one is considered stronger at a given time.
When the prices of two securities (filtered and scaled with a standard deviation for consistent presentation) are plotted against each other, the curvature and direction of rotation on the chart can help guide decisions on long positions. For example, when plotting a stock versus a referenced symbol, a vertical upward movement while rotating clockwise is a sign of going long the stock. Similarly, a horizontal movement to the right while rotating counterclockwise is the sign to go long the reference. A higher probability of a reversal is expected when the price moves more than one or two standard deviations.
█ CALCULATIONS
The script uses the following steps to calculate the Ehlers Loops:
The price data of both securities in the pair are individually filtered using identical high-pass and SuperSmoother filters. This results in two band-limited data streams, having a nominally zero mean. The input parameters Low-Pass Period and High-Pass Period control the filter bandwidth and thus can modify the shape of the Ehlers Loops.
Subsequently, the filtered data streams are scaled in terms of standard deviation by dividing each of them by their root-mean-square (RMS) values. These data streams are plotted as zero-mean oscillators.
Finally, the scaled data streams are displayed one against another for the selected time interval (defined by the input parameter Loop Segments ). In the resulting scatterplot, the thicker line corresponds to the later data points. The fluctuations of the filtered price data of the chart symbol are plotted along the y -axis, and the price changes of the referenced symbol are shown along the x -axis.
Indicator
Indicator
Indicator
Strategy
Indicator
