Blindly trading crypto without backtesting your strategy is the equivalent of running around like a headless chicken. You can study charts and come up with strategies for hours, but if you don’t test it before trading, you’re bound to lose money.
Backtesting is a process that’s time consuming and labor intensive. Some think that optimizing a backtest is even more complicated than optimizing trading strategies. And how can it not be? If your backtest is inefficient, it might give you false-positive results. That’s why if you’re going to backtest, you’ll want to do it the right way.
In this article, I’m going to show you how to successfully backtest a crypto strategy. I’ll explain how backtesting works and give you a real-world example by backtesting a rebalancing strategy with Shrimpy.
What Is Backtesting?
Backtesting is a process where you apply a trading strategy to historical trading data to find out how it would have performed. If the strategy performs well, it’s an indication that it might perform similarly in the future. However, a strategy that performed well in the past does not have a 100% chance to perform well in the future.
Read this article to learn more about backtesting
After backtesting a strategy, you can apply it to a real market environment. Doing so shows you whether the strategy is profitable, and whether the backtesting process is effective. Repeatedly backtesting crypto strategies leads to removing unprofitable strategies – increasing your profitability in the process.
Why Is Backtesting Important?
Backtesting is important because it shows you whether a strategy is profitable. It filters out bad strategies and provides you with guidelines on what works and what doesn’t work. You can then revise the strategy and optimize it until it becomes profitable. Alternatively, you can scrap the strategy and approach the market from a different perspective.
You don't know whether a strategy will work without backtesting. Therefore, backtesting is a crucial step to deploying capital to a volatile market such as crypto.
Should you perform manual or automated backtesting?
There are two types of backtesting: manual and automated.
Manual backtesting is when you observe a historical point in an asset’s chart and papertrade the asset using your strategy. Traders commonly use TradingView’s replay feature to rewatch a chart and buy or sell the asset depending on what their strategy or indicator tells them to do.
The next step is to log the trades in a document, and after resuming the chart, gain a glimpse into how profitable the strategy is. The final step is to optimize the strategy and revisit it with the replay feature until it works profitably.
Automated backtesting is when you use software to automatically execute trades on a historical price data set. The software will review the strategy, provide results, and show helpful statistics – all of which require dozens of hours when done manually. Traders can automate backtests via paid 3rd-party software and or program their own algorithms.
Deciding between manual and automated backtesting depends on how accurate you want your backtest results to be. You can only test your strategy on so much data with your limited time, while automated backtests deliver limitless sample sizes.
However, not every strategy requires an in-depth backtest. You can manually backtest a simple strategy and receive accurate results. But if you have the money for automated backtesting, it wouldn’t hurt to backtest more efficiently.
How to Run a Backtest for a Crypto Strategy With Shrimpy
Shrimpy is an portfolio management platform that offers automated trading strategies – the main one being portfolio rebalancing. Portfolio rebalancing is a strategy where investors set fixed allocations for assets. Assets can drift from their initial allocation by rising in value. Shrimpy will automatically sell the excess profit and redistribute it to assets that haven’t moved yet.
The purpose of rebalancing is to stabilize a portfolio by keeping its allocations on target. You benefit from this by selling assets while they’re in profit and utilizing the capital to purchase more tokens from projects that haven’t seen much progress. Alternatively, you will cut losses by selling assets who fell in value on time.
You can run a backtest on Shrimpy and compare the potential performance of your portfolio against historical market data. You can pick the assets you’re going to invest in and decide how many times the portfolio should be rebalanced. It’s also possible to select trading fees and a rebalancing threshold for your allocations.
For the purpose of this backtest, I have created a custom portfolio with the following assets:
Each asset has an initial allocation of 20%. I use the standard trade fee of 0.25% and haven’t applied any thresholds. I’ve selected the range between January 1st 2019 and 4th June 2022 as the timeline for the backtest. I’ve come to an interesting conclusion after running the backtest. The portfolio has been rebalanced on a bi-monthly basis.
Shrimpy’s rebalancing algorithm has outperformed HODLing for a majority of the bull run. The only time HODL beat rebalancing was during the large price spikes – probably caused by ATHs on certain assets. Logically, holding the assets makes more sense during a parabolic move. But predicting that an asset will move up without retracing is incredibly difficult.
Shrimpy’s portfolio was 52.35% larger than its counterpart by the end of the backtest date.
If you want to learn more about backtesting crypto strategies, I recommend reading the following articles:
Marko is a crypto enthusiast who has been involved in the blockchain industry since 2018. When not charting, tweeting on CT, or researching Solana NFTs, he likes to read about psychology, InfoSec, and geopolitics.