Event-Driven Backtest Trading: An Introduction
Trading requires backtesting to evaluate a strategy utilizing prior data. Backtesting helps traders choose strategies by revealing prior performance.
Event-driven backtesting finds trading strategy triggers. This technique encodes trading strategy logic as occurrences, not processes.
Understanding Event-Driven Backtesting
Event-driven backtesting divides a trading strategy into price movements, technical indicators crossing thresholds, and other entry and exit triggers. Trades are made according to guidelines to duplicate strategy performance in backtesting.
Event-driven backtesting replicates real-time trading by executing transactions. Trade delays, slippage, and other issues may be accounted for using this strategy.
Benefits of Event-Driven Backtesting
Events-driven backtesting provides advantages over other methods:
Event-driven backtesting replicates dynamic market trading more accurately by timing and sequencing events.
Flexibility: Event-driven backtesting enables traders adjust strategies by adding or removing events or parameters.
Event-driven backtesting reduces computations and boosts performance by using just actions.
Event-Driven Backtesting
You need Python or a trading platform that supports event-driven architecture to backtest. These systems often include libraries or frameworks for event, rule, and trade definition.
The basics of event-driven backtesting are:
Set trading strategy entry and exit signals.
Implement your strategy’s principles and logic.
To assess your strategy, simulate trades and determine profitability, drawdowns, and risk-adjusted returns.
Iterate your idea based on backtesting.