> Blog > What is Backtesting in Crypto?

Published September 21, 2022

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If you’ve been around capital markets for any amount of time, you’ve heard the phrase that “past performance is not indicative of future results.”  

While this is true, what many people don’t know is that backtesting, the practice of applying a trading strategy to past market data, can actually give you an indication of how your trading strategy might perform in the future. As markets mature and develop, historical data becomes a valuable resource to help traders make informed decisions under different market conditions. 

In this article, we’ll take a look at what backtesting is, why traders use it, and how you can go about performing a backtest on your own trading strategies. 

What is the Purpose of Backtesting? 

If you’re investing in a capital market, you’re doing so for one reason: to make money.  

But there are many different ways to make money in the markets. Some people trade for short-term gains, while others take a more long-term approach. And within these two broad categories, there are an endless number of different strategies that can be employed. 

With so many options available, it can be difficult to know which strategy is right for you. This is where backtesting comes in. 

When you backtest a trading strategy, you’re essentially simulating how that strategy would have performed if it had been used in the past. By running your trading strategy through historical data, you can see how it would have fared under different market conditions. 

This information can then be used to make informed decisions about what strategy to use going forward. 

Backtesting Trading Strategies  

manual and automated backtesting

Backtesting gained popularity during the 1990s as personal computers became more powerful and accessible. The ability to quickly and easily test trading strategies made backtesting a common tool for traders looking for insights on how various strategies would have performed in the past.  

Today, there are two main ways that you can backtest a trading strategy: manually or automatically.  

Manual Backtesting 

Manual backtesting, also known as discretionary backtesting, is the process of going through past market data by hand and applying your trading strategy to it. This can be a time-consuming process, but it has the advantage of being very flexible. 

With manual backtesting, you have the ability to customize your trading strategy to fit the specific data set that you’re working with. This can be helpful if you’re trying to test a new strategy or fine-tune an existing one. 

The downside of manual backtesting is that it can be very slow and tedious, especially if you’re working with a large data set, and it can be difficult to backtest multiple strategies at the same time. 

Automated Backtesting  

Automated backtesting, also known as systemic backtesting, is the process of using a computer program to apply your trading strategy to past market data. This is a much faster way to backtest, but it can be less flexible than manual backtesting. 

Automated backtesting used to be reserved for the biggest firms on Wall Street, but today there are a multitude of programs that everyday traders can use to test their strategies. 

The main advantage of automated backtesting is that it’s much faster than manual backtesting. You can also backtest multiple strategies at the same time, which can be helpful if you’re trying to find the best strategy for your needs. 

Many automated backtesting programs also come with pre-built strategies that you can use, which can be a helpful starting point if you’re not sure where to begin. 

How to Perform a Backtest  

graphic of person looking at large chart with someone holding a magnifying glass up to it

Now that we’ve covered what backtesting is and why traders use it, let’s take a look at a real world scenario: how to perform a backtest on your own trading strategy. 

Imagine a trader who’s developed a new strategy for trading the market. They want to see how this strategy would have performed in the past, so they decide to backtest it. 

The first step is to gather historical data. The trader will need data on past prices, volume, and other market indicators. This data can be gathered from a variety of sources, including brokerages, exchanges, and data providers. For cryptocurrency markets, CoinMarketCap and GoinGecko are two popular platforms that aggregate historical price data.

For example, if your trading strategy is based on moving average indicators, you’ll want to:

  • Define time parameters: Be sure to choose backtests based on times when you are trading. For example, if you live in the US, you would not want to backtest during periods where Asia is dominating the price action.
  • Choose your reference: If using moving averages, you will want to find instances in which the moving averages cross over one another (during your defined time parameter).
  • Build reference points: In each instance, place two vertical lines on the price chart, giving a reference that you can gather data from. The more references, the better – more data points will develop more accurate measurements of the success and failure rates of your chosen trading strategy.
  • Be systematic: Set rules for price action that need to be met every time before you open a trade. Having this discipline is what sets analytical trading apart from hopeful trading.
  • Collect data: Now that you have references made and rules set for entering trades, go back through each backtest and determine the win/loss ratio of your trading strategy. 

Doing this manually can take a significant amount of time, but there are programs out there which can automate the backtesting process.

In this case, once the trader has gathered this historical data, they’ll need to input it into a backtesting software program. The software will then apply the trader’s trading strategy to the historical data and generate results. 

These results will show how the strategy would have performed under different market conditions. The trader can tweak their strategy based on these results and then re-run the backtest to see how the changes would have affected the results. 

Challenges of Backtesting 

While historical data can provide valuable insights, it’s important to keep in mind that backtesting is not a perfect science. There are a number of challenges and external factors that can make backtesting results less accurate. 

One challenge is data quality. Not all data sets are created equal, and some data sets may be more accurate than others. This can introduce bias into backtesting results. 

Model risk also poses a challenge. When creating a backtesting model, traders need to make assumptions and simplifications that can’t account for every situation. These assumptions and simplifications can introduce errors into the results, or provide a misleading outcome. 

For example, when testing a trading strategy that relies on moving averages, the trader will need to choose what time period to use for the moving averages. If the time period is too short, the results may be less accurate. If the time period is too long, the results may not be representative of current market conditions. 

Finally, it’s important to remember that past performance is not a guarantee of future success. Backtesting can give traders an edge, but there’s no guarantee that a strategy that worked in the past will continue to work in the future. 

To counter this, using backtesting as a part of your strategy while staying up to date with the market’s current conditions will give you the best chance for success. 

Backtesting can help you identify potential trading strategies, but it’s ultimately up to you to decide how applicable the backtest is to your current situation, and whether or not to implement the strategies you test. 

Backtesting in Crypto

Backtesting can be a valuable tool for crypto traders. It can help you test new strategies and fine-tune existing ones. Additionally, it can give you insights into how your strategy would have performed under different market conditions. 

While backtesting is not a perfect science, it can still give you valuable insights into your trading strategy. Just remember to keep data quality and model risk in mind, and to stay up to date with the market’s current conditions. 

If you’re interested in backtesting your own crypto trading strategy, FTX offers a wide array of trading integrations that can help you get started. From historical data aggregators to journaling and analytics platforms, you can customize your trading experience on FTX to develop, backtest, and implement your own trading strategies. 

You can view the full list of FTX’s trading integrations here. If you’re ready to start backtesting and implementing your own crypto trading strategies, head over to FTX and register for an account today! 

To stay up to date with the latest news and insights from across the cryptocurrency industry, make sure you follow FTT DAO on Twitter, and check back with the FTT DAO blog for more in-depth info about the blockchain industry.   

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