Cointegration
Cointegration
The Cointegration section of this library provides powerful tools to analyze relationships between stock pairs using statistical techniques. Cointegration is a valuable concept in pairs trading, where two or more stocks move together over time, despite short-term deviations. These tools allow traders to identify potential mean-reverting pairs, enabling more informed trading strategies based on statistical dependencies.
In this section, you will find tools designed to help you perform in-depth cointegration analysis, calculate mean reversion metrics, and visualize relationships between stock pairs. These tools are highly configurable and can be easily integrated into your trading systems and data analysis pipelines.
Available Classes and Tools:
MeanAnalyzer()
A versatile tool to analyze and compare two stock tickers based on their price movements, log returns, and statistical relationships.
The MeanAnalyzer class allows you to:
Fetch historical stock data.
Normalize price movements and calculate log returns.
Generate buy/sell signals based on deviations in log return spreads.
Plot customizable, interactive charts to visualize price movements and signals.
Learn more about using MeanAnalyzer →
HurstHalfLifeCointegration()
A robust tool to identify mean-reverting pairs using advanced statistical methods such as cointegration tests, Hurst exponent calculation, half-life estimation, and mean crossing analysis.
The HurstHalfLifeCointegration class enables you to:
Perform the Engle-Granger cointegration test between pairs of stocks.
Calculate the Hurst exponent to detect mean-reverting behavior.
Estimate the half-life of mean reversion in stock pair spreads.
Analyze mean crossings to validate potential trading signals.
Learn more about using HurstHalfLifeCointegration →
Key Features of the Cointegration Tools:
Cointegration Analysis: Use advanced statistical techniques to identify stock pairs that move together over time, allowing for mean-reversion trading strategies.
Mean Reversion Metrics: Calculate key metrics such as Hurst exponent, half-life, and mean crossings to evaluate the likelihood of price convergence.
Customizable Analysis: Configure parameters like p-value thresholds, Hurst limits, half-life ranges, and minimum mean crossings to fine-tune your pair selection criteria.
Visualization: Easily generate interactive charts to visualize price movements, spread analysis, and buy/sell signals for selected stock pairs.
These tools are designed to help you make better trading decisions by identifying statistical dependencies between stock pairs, offering a powerful edge in mean-reversion strategies.
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