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backtesting-frameworks

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About backtesting-frameworks

B

backtesting-frameworks

Robust backtesting systems

backtesting-frameworks is an agent skill from the wshobson/agents collection for building backtesting systems for trading strategies. Its goal is to produce reliable performance estimates by avoiding the common errors that make backtests look better than they are. The skill names look-ahead bias, survivorship bias and overfitting, and covers realistic modeling of transaction costs, slippage and commissions. It describes event-driven and vectorized backtester implementations, so an agent can pick the style that fits the strategy, and it covers walk-forward optimization and Monte Carlo simulation to test how robust a strategy is. The skill is meant for developing trading strategy backtests, building backtesting infrastructure, validating performance, comparing strategy alternatives and implementing walk-forward analysis. It is a software guide, not investment advice: it does not recommend a strategy, and a backtest does not guarantee future results. The skill is installed with the skills CLI from the wshobson/agents repository. Its skills.sh page showed about 16.3K installs and passing results from three security audits at the time of the scan.

View backtesting-frameworksAll AI Skills apps
Price
Free
Made by
wshobson
Category
AI Skills
Website
github.com/wshobson/agents/backtesting-frameworks