How to Backtest a Trading Strategy in Algo: Backtesting Guidance
Algo trading is becoming popular among traders due to unlimited number of Algo trading software introduced in the market. These Algo trading software are equipped with all types of trading strategies from simple intraday to complex option strategies. These strategies are also working in the various market conditions giving the promising results.
However, the success of the Algo trading software is highly dependent on the quality and quantity of training data with the right algorithms used to develop the programming of the software. And to check the strength and accuracy of such Algo software you need to backtest the trading strategies before you implement them into the live market.
What Does it Mean to Backtest a Trading Strategy?
Backtesting of a trading strategy in the stock market, especially of an automated software is the process of evaluating the performance of the trading strategies, how it would have been performed in past. The historical data is used to determine the potential and accuracy of the strategy in various market conditions giving valuable insights into Algo’s performance.
Also Read: Top 10 Different Types of Trading Strategies in Stock Market
For backtesting you can use the historical data and check the performance whether it worked as per your expectations or how much it can give the returns or losses. It also helps to discover the potential flaws in the strategy and based on that you can modify the parameters or optimize the strategy before implementing it into the live market.
Why Backtesting is Important in Algo Trading?
The backtesting of such automated trading software is very important to evaluate the performance of Algo in various market conditions. Based on outperform or underperform, you can adjust the parameters or modify the other strategy as per the desired outputs. You can adjust the trading rules or change the entry and exit points to improve the returns and reduce the risks.
Also Read: How to Decide Best Entry & Exit Points in Intraday Trading
Another reason for backtesting the Algo trading strategy is to manage the risk associated with various types of trading strategies to minimize the impact of risks. Based on the outputs you can adjust the position sizing or modify the stop loss to reduce the chances of losses.
Also Read: How to Set Target Price and Stop Loss in Intraday Trading
When able to identify the performance and accuracy of the Algo, it will develop the confidence level for the traders to use the strategy in the live market for trading. You can rely on the strategy with the conviction that it will work as per your expectations even during the inevitable market conditions helping you to enhance the profitability.
How much Backtesting Would be enough?
Though, there are no restrictions on backtesting the Algo software, but unnecessary backtesting would be a waste of time and effort. In fact the need for backtesting depends on the complexities and risk with the expectations of reward from the trading strategy.
If you want to test a simple strategy, you need a few days or months of historical data to run the testing procedure. While, if you are backtesting a highly risky or complex level of trading strategy, then you need years of historical data to get the accurate results.
Backtesting is not a foolproof idea to judge the performance of the Algo trading software as during the real-time trading hours the trend and market conditions can change with unexpected scenarios. Hence, it is recommended to run the backtesting process many times under different types of market conditions with different time periods to get consistent results.
How to Backtest a Trading Strategy in Algo?
The backtesting process of trading strategy might differ from Algo to Algo trading software, but in all the cases, you have to use the historical data and backtest the strategy as per the market conditions and your risk profile and trading goals. However, for a common understanding, you can follow the guidance given below to backtest any Algo trading software.
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