Backtesting

What is Backtesting?

Backtesting refers to the process of applying an analytical method or trade strategies on the existing model in order to observe how accurately the strategies would predict or determine the result of the test. It is used to examine and estimate the performance of a strategy is applied to existing historical data or model in the past. If the backtesting works effectively, analysts or traders would be confident in its ability and apply it to actual data.

Basis Of Backtesting

With backtesting, a trader or an analyst is allowed to simulate a trading strategy using existing or historical data. The result would be used to analyze the risk and profit of using the strategies before applying this to actual capital.

Well-Conducted backtesting that produced the expected result would act as evidence that the strategies are fundamentally sound and when applied to actual data it would yield the expected result.

However, well-conducted backtesting that produced a negative result would convince the trader or analyst that when used on actual data, it might lead to disaster. Backtesting in this category is usually complicated ones like strategies used on the automated trading system, strategies that rely heavily on backtesting to prove their worth and so on.

Backtesting is not restricted in its application, so far the trading ideas can be quantified, it can be backtested. Although to do this traders often seek the expertise of qualified programmers to help construct their ideas into a testable format. With the aid of one of the coding languages hosted by the trading platform, the programmer code the idea into proprietary language. In addition to this, the programmer can include user-defined input variables that permit traders to tweak the system when carrying out backtesting.

What Is An Ideal Backtesting

Ideal backtesting is one that chooses a data sample depicting a variety of market terms and conditions from a relevant time period of duration. With this, one would be able to ascertain whether the result of the backtest is a positive or negative sign.

The historical data selected must entail a valid sample of stocks including those that were sold or liquidated and those that went bankrupt. This is because when historical stocks are chosen from those still in use, there is a high tendency that this would produce artificial high returns in backtesting.

All costs of trading no matter how insignificant they seem should be included in a backtest. All these would affect the result of the backtest

Some Pitfalls of Backtesting

For backtesting to provide substantial results, traders must use this in good faith, not with bias. This implies that backtesting should be done to see how the result would be without any reliance on the historical stock selected.

Also, traders should select their data from those they use in testing their model. Data should not be selected mainly from current stocks. This is to avoid a glowing result that makes no meaning.