Want to know about an ideal backtesting scenario? Mostly all traders have a trading model or strategy to analyze risk or rewards associated with investing their money, but unfortunately, not all of them have assessed it right.
Due to which many traders have to incur losses. In order to avoid this situation, the backtesting technique was introduced. Backtesting has been applied in trading strategy since then.
Backtesting gained popularity within a little period of time because of aiding traders to test their trading strategy before actually investing real capital in the market. But, it also only helps to give accurate results if traders consider all market conditions.
What is the Ideal Backtesting Strategy?
The ideal or optimum backtest chooses sample data from a period of time that reflects a variety of market conditions. This is one way through which we can conclude whether backtesting results are just a coincidence or a sound strategy.
The sample data from the relevant time period means it should also include representation of sample stocks of companies that went liquidated or bankrupt or sold etc. If it sounds hectic then the alternative is to only pick historical data from the stocks that still exist today.
How to Conclude The Efficiency Of A Trading System?
A backtest should includes all trading risks or costs, as these can drastically affect the backtesting strategy. So traders should always ensure that their backtesting strategy covers or accounts for all these costs. Then the out-of-sample testing and further/forward testing actually confirms the system’s effectiveness or true colors before rolling it out in the real world.
Good relation between the out-of-sample testing and further/forward testing is significant for concluding the efficiency of the trading system.