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README.md
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README.md
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## Overview
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The system is designed to backtest pairs trading strategies on historical market data. It allows users to select different strategies, configure parameters, and analyze the performance of these strategies.
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The system is designed to backtest pairs trading strategies on historical market data.
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It allows users to select different strategies, configure parameters, and analyze the
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performance of these strategies.
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## Core Concepts
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### Trading Pair
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A trading pair consists of two financial instruments (e.g., stocks or cryptocurrencies) whose prices are believed to have a long-term statistical relationship (cointegration). The strategy aims to profit from temporary deviations from this relationship.
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A trading pair consists of two financial instruments (e.g., stocks or cryptocurrencies)
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whose prices are believed to have a long-term statistical relationship (cointegration).
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The strategy aims to profit from temporary deviations from this relationship.
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### Strategy
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The system supports different strategies for identifying and exploiting trading opportunities. Each strategy has its own set of configurable parameters.
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### Trading Signals
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Trading signals indicate when to open or close a position based on the configured strategy and parameters. These signals are typically generated when the "dis-equilibrium" (the deviation from the long-term relationship) crosses certain thresholds.
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Trading signals indicate when to open or close a position based on the configured strategy
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and parameters. These signals are typically generated when the "dis-equilibrium" (the
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deviation from the long-term relationship) crosses certain thresholds.
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## Running a Backtest
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@ -54,7 +60,11 @@ The system currently offers two main strategies: `StaticFitStrategy` and `Slidin
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STRATEGY = SlidingFitStrategy()
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```
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- **`StaticFitStrategy`**: This strategy fits the cointegration model once at the beginning of each trading day (or for the entire dataset if run on a single file without a rolling window logic in the strategy itself). The parameters (mean, standard deviation of dis-equilibrium) derived from this initial fit are used for generating trading signals throughout the day.
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- **`StaticFitStrategy`**: This strategy fits the cointegration model once at the beginning
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of each trading day (or for the entire dataset if run on a single file without a rolling
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window logic in the strategy itself). The parameters (mean, standard deviation of
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dis-equilibrium) derived from this initial fit are used for generating trading signals
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throughout the day.
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- **Pros**: Simpler, computationally less intensive.
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- **Cons**: May not adapt well to changing market conditions during the day.
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