Backtesting Crypto Trading Strategies Insights.
Discover how to backtest a crypto trading strategy and why backtesting crypto trading strategies can help you succeed and prosper in the crypto trading space.
Ask any trader behind a successful business if backtesting their crypto trading strategies is an essential part of its development, and the answer will undoubtedly be a Yes.
Backtesting is an essential tool to demonstrate an algorithmic strategy’s minimum viability (or not). A backtest is usually the first step after the trading design has been programmed and formed.
Think of it this way: Before you buy anything, you check its history. You look into the product, how it works, and if it’s worth your money. This same principle applies to trading. Backtesting can help discover its history.
Without backtesting strategies, traders would be taking an insanely high risk while trading cryptocurrency. Backtesting is an essential tool in the trader’s toolbox because, without it, there would be no way to know if a trade would be profitable.
However, many developers cannot help but bring their strategies to the market after completing this first step rather than continuing with more advanced test runs.
For you (the end-user), this move doesn’t have a happy ending. It is almost always disappointing and generally costly.
Luckily for you, we can take advantage of the complementary backtesting tool of the ultimate trading software and test before buying and selling our hard-earned coins.
But let’s find out all about backtesting before. Read on!
Backtesting, What Is It?
Backtesting consists of simulating past transactions using historical data and the programmed trading strategy model, the first hurdle in determining whether the execution of the automated strategy is market-ready.
Backtesting is a vital function in developing a sound trading system. You can always complete the process by taking past data and building past trades that used the rules of a strategy you may be considering yourself.
By comparing the statistics that shine as you build past assumptions, you can determine the strategy’s effectiveness, discover ways to refine your trading method, and spot flaws in the plan before making any solid investments or transactions strategy.
Crypto backtesting is the basic process of fabricating a trading method using historical prices to test how well your strategy would have worked in the past.
Backtesting Crypto Trading Strategies assumes that if a strategy has worked against data and trading scenarios, it will continue to work in the future and vice versa; if the trading plan were not up to par in the past, it would fail attempted in the future.
For your backtest to be successful and get the best possible results in forming your technical crypto trading strategy, you need to collect plenty of data.
More importantly, if you consider a significant investment, taking the time to do a well-thought-out backtest can pay off in the long run. Because if your backtest is successful, your future investment can (and will) be successful as well.
Why is Backtesting Important for a Crypto Trader?
Because backtesting crypto trading strategies allows you to analyze the historical behavior of an investment strategy and determine the profitability of your chosen trading method, if the backtest results show that your plan has high returns and low risk, you will have more confidence in implementing those trading rules.
The main idea is that any trading strategy that has worked well in the past is likely to do so in the future. Conversely, suppose a backtest of a particular trading strategy shows poor performance. In that case, you should reject the strategy because it is unlikely to perform well in the future if it has underperformed in the past.
Backtesting also helps traders understand the behavior of their trading plan during different vital periods of past data, for example, in the 2020 global recession and pandemic. You get to know how much money you expect to lose in these Black Swan events.
For older traders, taking too much risk could significantly delay retirement. A significant drawdown could be a big problem for young traders who invest on margin (borrowed money). Therefore, by backtesting your trading strategy, you can know exactly how much money you will lose during these challenging times, so you can always determine the risk you can afford to take before trading.
If you are considering a significant investment, it may be worthwhile to take the time to do a full backtest, as the backtest results can determine whether or not you are making the right decision.
Do you know why most traders in the crypto market lose money?
It is not only because they don’t understand the market. It is mainly because their trading decisions are not based on sound research and tested trading methods.
Never make your trading decisions based on emotions, or take excessive risks with the hope of getting rich quickly. If you remove your feelings from trading and backtest your ideas before trading, then your chance to trade profitably in the crypto market will be increased.
Benefits of Backtesting Crypto Trading Strategies
The result of your backtest will give you the crucial information you can apply to your trading plan.
Here are four benefits of backtesting
- Find out the best trading setup based on your needs and goals.
- Become aware of your optimal risk per trade.
- Discover on what crypto markets your strategy will work best.
- Gain the ability to fine-tune your entry and exit triggers.
All this information can help you build an accurate trading strategy. Without data from fundamental markets, you cannot understand how your plan will perform in the future and whether it is viable as the market changes.
Do you want an accurate and sound trading strategy?
You won’t have it unless you start incorporating precise market data. Without it, you’re not able to tell if your trading strategy will work in the future.
Crypto Trading Strategies you can Backtest
Generally, any strategy that you can rule you can backtest, ranging from systematic to algorithmic trading.
For example, a trader may be drawn to a strategy that selects ten coins with the lowest price ratio each year. Likewise, a trader who relies on technical analysis may consider buying a cryptocurrency when its fast-moving average exceeds its slow-moving average.
All of these crypto strategies follow a consistent set of rules that you can simulate using historical data. The advantage of rule-based investing is that it removes emotions from the picture.
Every decision to buy or sell a coin is based entirely on logic. This choice prevents traders from making behavioral mistakes, such as panic selling for uncertainty and doubt or buying for fear of missing something.
Backtesting a Systematic Trading Strategy
Moving Averages (MA) is a common indicator-based strategy used by many technical and non-technical traders. The aim is to identify a trend in the price of a coin and capitalize on the direction of that trend. Some traders believe that certain behaviors of moving averages indicate fluctuations or possible movements in the price of altcoins.
For example, a short-term moving average that goes over a long-term moving average is a buy signal. In contrast, a short-term moving average under a long-term moving average can be considered a sell signal.
A pattern widely followed by traders and financial analysts are the 50 and 200-day moving average, known as the golden cross. It occurs when the 50-day moving average exceeds its 200-day moving average. It is considered the sweet spot of moving averages among a huge crowd of investors.
Short moving averages are used chiefly for short-term trading. However, most of the market players use it blindly and without prior backtesting.
Therefore, most traders are unsure whether it works or not, except for those who have been using it for a long time and have done their homework and tried various moving average setups.
As an informed trader, you should generally avoid relying on a single technical indicator when deciding whether or not to enter a trade. However, there is also the phenomenon of self-fulfilling prophecy. If enough market players believe that the golden cross marks a turnaround, it might come true.
Death cross, which is the reverse of the Golden cross, occurs when the 50-day moving average of an asset exceeds the 200-day moving average. This indicator’s name comes from its supposed strength as an indication of a bear market.
Here’s the creation of a death cross in three stages:
- Coin’s uptrend peaks, and momentum begins to weaken.
- A case where the price of the 50-day moving average drops down the 200-day moving average.
- The last phase is a continuation of the downtrend. If the downtrend is short-lived, the death cross is considered a false sign.
Professionals consider the death cross a more reliable indicator if a high volume of operations confirms it.
Backtesting Crypto Trading Strategies
Since the purpose of the backtest is to determine the effectiveness of a trading strategy, it is essential to ensure that your backtest is as realistic as possible. This avoids creating backtests that look very appealing on paper but still perform poorly when you’re live trading on the exchange.
There are several ways to do a more realistic backtest. Identify the situation and retrieve similar cases from the history. Take an economic event or a sudden change in price or volatility and compare past conditions.
Create and execute a strategy
Execute your trading strategy through all the past historical data past while manipulating various variables. These options include entering the market, first and second profit targets, stop loss and risk/reward ratio, etc.
Creating your backtester: You can start from scratch and build your own backtest, and it is up to you to decide the programming language you will use to backtest your trading strategy.
Pine Script (Developed by TradingView) is the most widely used backtesting program. Still, It is not easy to create your own backtest due to learning the program.
Thanks to the Gunbot developers for the integration and our member Allanster you can benefit from ready-made backtesting scripts when you purchase the Gunbot Backtesting addon either separately or when it comes included in your license.
Don’t worry. If you’re not comfortable with the programming language used by TradingView for backtesting crypto trading strategies, you won’t have to program anything or write any code once you own the module. It’s all done and included in the Gunbot Deluxe Tuners for you to use.
Alternatively, you can also try Allanste’s free tuners for backtesting crypto trading strategies like BB, BB with RSI, BB/StepGain, PingPong, StepGain, and the TSSL strategies TradingView to help you visualize and optimize them in Gunbot.
You will not need the TradingView plugin, and it will work with a free account on TradingView. These basic scripts will help you learn and optimize your settings for the built-in strategies included with Gunbot.
Backtesting Crypto Trading Strategies with Gunbot
When you buy your backtesting addon or your Gunbot Pro/Ultimate from CryptoDROI.com, you can open a ticket through Zendesk support, and the Gunthy team will take care of activating it for you and give you access to the Gunbot TradingView Scripts.
After that, all you have to do is head over to Tradingview, open a chart, and search in the Indicators section for “Tuners,” choose by clicking on it and apply it to your chart.
The scripts are programmed with Gunbot strategies, so all you have to do is edit the values to match your rules.
These strategies also include different confirming indicators like ADX, BTC_PND, EMASPREAD, MFI, RSI, STOCH, STOCH-RSI, TrailMe, TakeBuy, and TakeProfit all inside one suitable script.
Read the Backtesting Add-on Frequently Asked Questions article to learn more about this Gunbot excellent feature.
Evaluating Your Backtesting Results
Many strategies can be utilized when it comes to backtesting, and you can also achieve a lot of results if you properly learn what data to interpret and what to extract from the data being compiled.
Below are few tips to help you backtest and choose an effective trading strategy.
The first thing you need to know before backtesting crypto trading strategies to help you improve your crypto trading techniques is the universal statistics behind backtesting that can be used and converted into feedback.
Some of the most important are the timing of the test, the actions that are part of the backtest, which is commonly referred to as the universe, and the net profit or loss, which, of course, is your percentage of profit or loss.
This last part is the real definition of how effective your long-term strategy is when choosing to model your investments around it.
Backtesting crypto trading strategies statistics are what a savvy investor will review and compare various investment strategies. They might help you discover potentially problematic situations with the strategy.
Here’s some information you can collect from your backtesting statistics:
- Annualized returns: The standard deviation of the model’s daily returns over a year.
- Annualized profitability: Percentage of the average annual profit (or loss) of your trading strategy.
- Test time: Backtesting over a long time gives you a better idea of different market conditions.
- Exposure: The percentage of capital you invested. Keep in mind that a higher exposure can lead you to higher profits or higher losses.
- Averages: The percentage of your average gains and average losses.
- Volatility measures: Keeping the volatility low may help you to reduce risk.
Understanding these aspects of statistics can really help your technical crypto trading strategy. Once these are fully understood, defining what you can use on your trading systems for backtesting.
The truth is, any trading system that you can quantify can be used because the calculation will not change. However, qualitative systems that include judgments on human decision-making cannot be used because the results will vary each time.
Your cumulative or absolute return is the total amount of money that your investment has gained or lost over time, independent of the time involved.
To calculate your cumulative return, you will subtract the Final value of your investment from the initial value of your investment, then divide the result by the Initial value of your investment.
Here’s an example: Imagine you invested $10,000 on Bitcoin, then after some months of trading, your investment grows to $15,000. In this example, the cumulative return of your investment is 50%.
You would calculate your Cumulative Return in this example like this: (15000 – 10000) / 10000, and it will give you a cumulative return of 50%
But don’t break your brain yet :). If you’re a Gunbot user, you won’t need to do any manual calculation because your bot PnL (Profit n’ Loss) tab will give you the numbers you need.
All you need to do is click the PNL tab from your Dashboard in your Gunbot GUI and check it out.
Optimization allows the computer to calculate the best combination of the variables mentioned above in a function.
Be careful because optimizing your backtests can lead to overconfidence, and the best combination of inputs for past situations does not guarantee you are making a profit in actual trading.
Overfitting – One problem that can arise with algo trading is overfitting. Overfitting represents a model over-correlated with a particular set of data and contains more parameters than the data itself can justify.
In other words, you’ve designed a trading system that is so closely adapted to historical data that it will become inefficient in the future. Algorithmic trading tends to maximize its results on a set of data and ignore fit for future data.
It would be best if you considered the possibility of overfitting when testing back. Collect more data; the more a model reoccur after the test, the more you tend to predict the situation in the future.
Use set methods – You can use set methods to query and average several different models, as this is much more likely to produce optimal results for actual trading. Also, it would help if you made the model clear and simple while trying to fit in many metrics.
This article shows a simple implementation to backtest your trading strategy. Backtesting Crypto Trading Strategies is an essential step in the development of successful trading plans. The main point here is to develop a strategy that you can use in your daily trading activities.
You want this idea to be implemented as long as the conditions for the strategy are met. Sometimes this only applies to a single pair, but other strategies may apply to the entire crypto industry, altcoins, etc.
Backtesting consists of testing the viability of your plan. You can test the strategy with the actions you want for the desired time. Of course, it’s not 100 percent guaranteed, but it is a step towards verifying the credibility of your idea.
When you backtest your ideas before trading, you will have a better chance of creating profitable trades in the crypto markets.
If it’s done right, Backtesting Crypto Trading Strategies can improve your strategy and strengthen your confidence in it before you put it into practice. With the right data and careful interpretation, you can ensure that your trading system is perfect before applying your strategy to real-world cryptocurrency exchanges.
If you like automation, give Gunbot a try and take advantage of its ability to backtest your crypto trading strategies.