Backtesting analyzes trading strategies by applying them to historical data to determine their potential performance. It is used to test the viability and success of trading strategies or to compare different strategies against each other.
How Is Backtesting Applied?
Backtesting allows the performance of various trading strategies to be measured without risking capital. The fundamental rationale behind backtesting is the belief that a strategy that has performed well in the past will continue to perform well. Conversely, an approach that has failed in the past will continue to perform poorly.
Backtesting is a technical application that requires a series of programming steps. The first step in backtesting is simulating the trading strategy to be tested. This simulation includes factors such as which assets will be included in the test, how much starting capital there will be, the portfolio size, benchmarking, trading strategy, and risk management strategy.
The trading strategy determines when buy or sell orders will be triggered, while the risk management strategy defines how pending orders like take-profit and stop-loss will be used.
A backtest can have a very simple trading strategy: a buy order is initiated when a shorter moving average crosses above a longer one, and a sell order is triggered when it crosses below. However, much more complex strategies can also be adopted.
The second step involves collecting the necessary historical data for backtesting. The accuracy of historical data is critical for the reliability of the backtest results; therefore, it should be obtained from reliable sources.
Next, coding is performed to automatically apply the selected trading strategy over the defined time range. This coding can be done through various software programs.
Finally, the backtest is conducted, and the results are analyzed. Test results are evaluated based on certain performance metrics such as profit/loss, risk-adjusted return (Sharpe ratio), or maximum drawdown. The primary goal of the analysis is to assess the risk-return profile of the strategy.
Strategies that yield successful results in the test are considered suitable for real-world application and potentially profitable. Conversely, strategies that yield poor results are generally not preferred for real-world application. These strategies may either be shelved or retested with adjustments to parameters to optimize them.
How Can Individual Traders Apply Backtesting?
Backtesting simulations involve complex processes coded by developers; thus, it is not normally feasible for individual traders to test their trading strategies independently.
However, many trading platforms offer individual traders the ability to utilize backtesting. Traders can analyze the performance of their strategies by adjusting various parameters for the desired asset and time range and test the plan they intend to implement in real trades without risking their money.
Conclusion
Backtesting enables the testing and analysis of trading strategies on historical data before implementation. However, traders should remember that the results from backtests do not guarantee the future performance of a plan. Current market conditions can lead to very different pricing outcomes.
Therefore, it is healthier to consider the results from backtests as part of market research before taking a position and to blend this information with current data when making trading decisions.