Why Backtesting is Essential for Quantitative Trading?

Backtesting is the process of testing a trading strategy on historical data. This is an essential step in quantitative trading, as it allows you to evaluate the performance of a strategy and determine if it is profitable. Without backtesting, you would be blindly risking your hard-earned money on strategies that may not work in the future. In this blog post, we will discuss the importance of backtesting and how to go about doing it correctly.

Table of Contents

What is backtesting?

In simple terms, backtesting is the process of testing a strategy on historical data to see how it would have performed. To be more specific, it involves taking historical price data and performing various calculations to determine the profitability or performance of a trading strategy. For example, you could use historical data to calculate the average return over time and assess the level of risk involved in your strategy.

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Main types of backtesting

1-Manual Backtesting – In this method, you manually perform the calculations and evaluate an individual trading signal before making a decision to enter or exit a trade. This is usually done using custom-built spreadsheets or software programs that contain mathematical formulas.

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2-Automated Backtesting – This method uses a computer program to perform the calculations and generate trading signals automatically. It is usually used in more complex strategies that involve multiple factors, such as trend analysis, momentum indicators, and filter conditions. The advantage of automated backtesting is that it can quickly evaluate large amounts of historical data, which would be too cumbersome to evaluate manually.

Why is backtesting Important?

There are several reasons why backtesting is essential for quantitative trading:

1-It allows you to confirm that your strategy has a positive expectancy – If a strategy has a positive expectancy and provides an average profit greater than the losses over time, it can be profitable in the long run.

2-It helps you take calculated risks – Backtesting allows you to find out if a particular trading signal carries a high level of risk, which will help you avoid unsuitable risks that could lead to very large losses.

3-It helps you avoid curve-fitting – Curve-fitting is the process of tweaking a strategy to make it appear profitable on historical data. Backtesting enables you to evaluate a strategy’s performance over a large number of trading signals. Forward testing will mitigate the risks of overfitting.

4-It can help you evaluate the probability of your strategy being profitable – There is no guarantee that a trading strategy will be profitable in the future. Backtesting allows you to estimate its probable performance based on historical data.

5-It helps you find out if your strategy will work in different market conditions – Not all trading strategies are suitable for every market. Backtesting can help you evaluate how your strategy will perform in different market conditions, such as trending or volatile markets.

6-It allows you to continuously improve your trading strategy – Backtesting can help you find out whether the parameters or variables in your strategy are right. Once you identify a problem, you can then re-optimize them to improve the performance of your strategy.

How to Correctly Backtest a Trading Strategy

There are several steps involved in backtesting, which you must perform in the correct order to ensure that the results are not skewed. The following guidelines will help you get started:

1-Collect the data – To get accurate results from your backtest, you must first collect all the necessary historical data for a particular trading instrument. This will include data for the underlying asset, as well as for any technical indicators that you intend to use in your strategy. The historical data should be as long as possible, but at least ten years. If you are using a timeframe of fewer than five minutes, the historical data should include tick data.

2-Code the trading strategy – You will need to the trading signals in a programming language that is compatible with the backtesting software. There are many open-source platforms that allow you to code your strategy in a language like VB.net, C++, or Python. Once you have coded your strategy in a programming language, you can then run it on the backtesting software.

3-Choose a suitable backtesting platform – There are many different software packages that offer extensive functionality for the purpose of backtesting, such as Amibroker, TradeStation, and Metatrader. Some of these platforms also come with demo versions that you can use to test the features. Before you commit to a particular software package, make sure that it has all the functionalities you will need for your trading strategy.

4-Run the backtest – You can then run a complete backtest on your strategy and check if it has a positive expectancy, or if you have over-optimized it. When you are initially testing, use a test period of about two years as this will give you enough data to check for over-optimization.

5-Review the results – You must review the data from all sources, such as your trading platform, the broker, and the backtesting software to ensure that it is accurate. You must also check if there have been any data errors or problems during the backtest.

6-Incorporate any changes – If you find that your strategy has a negative expectancy or over-optimization, you will need to go back to step 3 and make the required changes. Keep repeating this process until you are satisfied with your strategy.

FAQs

What is a backtesting platform?

A backtesting platform is a software that allows you to test trading strategies on historical data. When you use a program like Amibroker, you can use it to code your trading strategy in a particular language and then run a backtest on historical data to see how the strategy would have performed in real-time.

What is a normal backtest?

A normal backtest allows you to simulate your trading strategy on historical data, but it does not include real-time execution. A normal backtest is used for comparison purposes and to run statistical tests to identify the expectancy of a trading system.

Is backtesting good for trading?

Yes, backtesting is an excellent way to test a trading strategy and identify potential problems with it. When you backtest your strategy on historical data, you get an idea of how it would perform in real trading. You can also run statistical tests to ensure that it has a positive expectancy and identify any over-optimization.

How do you backtest a trading strategy without coding?

To backtest a strategy without coding, you need to find a platform that allows you to do this. You can then input the rules for your strategy by selecting the indicators and the timeframe you want to use. Then, the software will run a backtest based on the historical data that is available.

Can you backtest in Excel?

Yes, you can backtest in Excel using the programming language VBA and some of the other add-ons that are available. However, you need to be proficient in the programming language and have experience with Excel functions to use this approach.

Is Python good for backtesting?

Yes, Python is an excellent language for backtesting. It is a highly flexible programming language and you can use it to code in any way that you want. Python also has a number of useful libraries available and many traders use it as an alternative to Amibroker or TradeStation.

How do you know if a backtest is accurate?

To ensure that your backtest is accurate, you should ensure that all the data that you are using is correct. You can do this by checking the historical data from multiple sources, such as your broker and a backtesting software platform. Also, you should check the accuracy of your indicators and make sure that you have coded the trading strategy correctly.

How do I interpret the results from a backtest?

To interpret the results from a backtest, you must first check if the strategy has traded at least 30 times and then look at the expectancy of your strategy. If you have a positive expectancy, then you can continue with the process. Next, you should look at the profit factor, which tells you how profitable your strategy is. Once you have identified any problems with your strategy, you should go back to step 3 and make the necessary changes.

The bottom line

Backtesting is an essential part of system development and it can help you to identify potential problems with your strategy. However, backtesting is not easy and you must use the right tools and resources to get accurate results.

To get started, you need to identify the best backtesting software available. Once you have chosen the right platform for backtesting, you can then look at the data that you are using. Finally, you can check the accuracy of your indicators and make sure that you have coded your trading strategy correctly.