Investing in the stock market requires taking some calculated risks. Backtesting is one such method that traders use to understand how well their business models will work.
Usually, historical data is used to understand the effectiveness of the trading model during backtesting. Most experienced traders use backtesting to optimize their trading strategy.
They simulate trading scenarios to understand the risks and analyze the profitability of an idea before they risk it with any actual capital.
We throw light on backtesting and talk about its merits and shortcomings. We also discuss the things you need to keep in mind while backtesting stocks.
The world of technical analysis revolves around studying the market, its indexes, and stocks to identify patterns.
Once a repetitive pattern is identified, traders determine the key indicators based on which a strategy is prepared. The indicators can be anything from an entry and exit signal to the trading time frame.
While the core idea of backtesting is like that of paper trading, the main difference is that the testing happens in the past market rather than on the current one.
On a broad scale, backtesting systems can be classified as below.
When you start your backtesting journey, chances are you may have multiple strategies.
Your research-based backtesting approach would need you to evaluate each of them to identify the ones that deserve testing.
In this approach, your focus will be on speed, and you need to decide on each shortlisted strategy’s potential. It is helpful to list down each strategy’s advantages and disadvantages to make a call.
Event-driven backtesting is an automated process, and you need to have decent coding skills to create such a process. Here, you simulate a market environment by taking historical market data.
Based on the triggering events in your code, buy and sell will be initiated, thus mimicking a real trade experience.
Advantages of Backtesting
At first sight, it may look like backtesting is too much effort. However, knowing how well your pattern identification or strategy works without monetary investment helps in decision making.
The major advantage of backtesting is that its usage will help you decide whether you should trade on the stock, twerk it or just let it pass.
The results of backtesting also help you size your positions to maximize the gains. Depending on the reliability of the pattern, you can make suitable adjustments to your portfolio with minimal manual effort on your part.
Things To Do While Creating Backtesting Strategies
Now that you realize the perks of a backtesting strategy, the next step is to go ahead and create one on your own. Keep the following pointers in mind while backtesting your stocks.
Experiment With Variables
If your model involves multi-variable rules, try toying with one variable to understand what goes different. Repeat this for all the variables to create a robust backtesting mechanism that gives accurate results.
The accuracy of any algo trading api depends on the number of parameters involved. The thumb rule is to keep the parameters specific to the type of trade so that you can avoid mixed results.
Within these boundaries, the more the parameters, the higher is the accuracy of your results.
In the world of backtesting, you need to remember that a successful backtest does not mean the end of the road. Make sure that you keep up with the price action, setups, and other latest market trends.
The stock market is a dynamic world, and the key to successful backtesting is constantly improving.
Things To Avoid While Creating Backtesting Strategies
While it is true that the advantages of backtesting in the stock market outweigh the challenges, you still need to be cautious with your approach.
Knowing the things to avoid in the testing model will allow you to do away with any unnecessary risk to your capital.
Do Not Neglect The Fees While Testing
While creating a backtesting model, you need to realize that not every broker gives a commission-free model. This makes it important to include interest charges and borrow fees in your model.
That way, you can evaluate if a trade is profitable after all the commission and other fees deductions.
Do Not Neglect The Importance Of Blind Data
Many crypto traders look for data to support the hypothesis that they present in their backtesting models. While some of them do this consciously, others do not realize that they are biased.
Make sure that the historical data that you use for backtesting is completely blind and randomized.
An efficient way of ensuring the blindness of your data would be shifting the timescale of the collected data before the testing.
Do Not Ignore The Big Picture
An important thing in backtesting is to ensure that your strategy covers a varied market scenario. It is recommended that you test the backtesting model over different time frames, sectors, and market conditions.
That way, you will avoid a situation wherein the strategy that you created for a bull market fails because you are implementing it in a bear market without any trials.
Limitations Of Backtesting
The accuracy, detail, and depth of historical data play a crucial role in determining any backtesting model’s success.
It may not always be feasible from a practical perspective to get access to such detailed past market data for different market conditions.
Moreover, potential overfitting is another cause of worry and often proves to be the biggest limitation of the backtesting trading model.
Lastly, when you opt for backtesting, you need to realize that your current work on historical data cannot model the factors contributing to the historical price fluctuation of the stock in question.
Thus, rookie traders need to be on your toes and ensure that they do not get overconfident in their backtesting methods.
Backtesting has its fair share of pros and cons. However, if you approach backtesting with caution and skilfully use trading bots, you will make better-informed decisions about your trades.
That will pave the way for better monetary gains from your positions and make you a much better trader