How to backtest trading strategies in excel
Contents:
How To Backtest a Trading Strategy Using Excel
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System Based Trade Execution
I deleted out those lines and it seemed to run OK. RSI does not correct for splits. Price does. This website uses cookies to improve your experience. We'll assume you're ok with this, but you can opt-out if you wish.
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These cookies will be stored in your browser only with your consent. You also have the option to opt-out of these cookies. You can get this information from a data provider like Yahoo Finance for free. Here is the data I downloaded for Tesla.
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It consists of daily price—open, high, low, close, and adjusted close price—and the daily volume from when Tesla launched its initial public offering in through October 9, The price and volume data are sufficient to start building the framework for our testing. You will need to develop a model in Excel to automate the testing process. This requires some time upfront to build out the formulas, but once it is built, all you'll need to do is to simply import the required data into the model. The model I used includes a variety of metrics to analyze the strategy performance, such as total return, CAGR, Net Profit, of winning trades vs.
The next step in the backtesting process is to establish which indicator s you will used for your trading criteria.
Successful Backtesting of Algorithmic Trading Strategies - Part I | QuantStart
Depending on strategies you are looking to test, there are four main groups of indicators you can choose from: 1 Trend Indicator, 2 Momentum Indicator, 3 Volatility Indicator, and 4 Volume Indicator. These indicators are based on mathematical formula that can be calculated in Excel.
For backtesting Tesla, I decided to use Relative Strength Index RSI , which is a Momentum Indicator used in technical analysis that measures the magnitude of recent price changes to evaluate when the price of a stock is overbought or oversold. A stock price can have a RSI range from 0 to , and is generally considered overbought when the RSI is close to or above 70 and oversold when it is close to or below After establishing that RSI is the indicator I'll be using, I can now calculate it on Tesla's historical price data in my backtesting Excel spreadsheet.
The RSI calculation is computed with a two-part calculation as shown below:. I won't go through the specific details of the calculation in this article, but basically I used 14 periods of the adjusted close price column M to compute the initial RSI value.
With the RSI values calculated, we can now come up with some initial assumptions and construct trading rules to determine the condition under which to enter and exit a trade. I find it is easier to this by asking questions. With these questions in mind, below are the criteria I came up with for Tesla. You can come up with your own criteria based on the trading strategy you are looking to test. Maximum position size: 1, shares minimum position size is whatever amount the capital can afford. But if the account grow beyond the value of 1, share, I will take profit off the table and only reinvest the maximum position size.
After entering the assumptions and programing the trading logic in the Excel spreadsheet, the result was possible long trades that can be backtested. We can flip the entry and exit RSI criteria were we testing short trades.
Now that we have our metrics establish, let's review the results. The important thing to look for in the graph is whether the results have been consistent overtime or whether specific market conditions influenced the outcome. While the results were consistent for the most part, we can see that there was a huge spike towards the end of the investment period. Obviously, this was due to the market's precipitous decline in response to the Covid pandemic in March , and the subsequent V-shaped recovery.
Considering that this was an anomalous event, let's take a look at how the graph without results. Once we remove the results, you can see in Graph 2 that the results were more consistent over the investment period. Even more important, the two different exit criteria are more closely aligned. This gives more confidence to employ this strategy going forward. Excel is a powerful tool that can calculate virtually any metrics. Table 1 below shows the metrics based on investment period of