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How can you backtest technical analysis strategies on a budget?

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Backtesting is a method of testing how a technical analysis strategy would have performed on historical data. It can help you evaluate the effectiveness, risk, and profitability of your trading system. However, backtesting can also be costly and time-consuming, especially if you need to access high-quality data, software, and hardware. In this article, you will learn how to backtest technical analysis strategies on a budget, using some free or low-cost resources and tools.

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Mukund Bagaria

Founder, M Bagaria FinCorp | Wealth Management Expert | Crafting Paths for Your Insurance Needs
Samaara Das

Financial Market Algorithm Developer | Happy to share my free algos

1 Choose a backtesting platform

The first step to backtest your technical analysis strategies is to choose a platform that suits your needs and budget. There are many options available, ranging from online services, desktop applications, and programming languages. Some of the factors to consider are the features, ease of use, data availability, and price of the platform. For example, you can use TradingView, a free online charting and analysis platform that allows you to backtest your strategies using pine script, a custom programming language. Alternatively, you can use MetaTrader, a popular desktop platform that supports backtesting with MQL, another custom programming language. Both platforms offer a large database of historical data for various markets and instruments.

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Dan Blystone

Writer @ FX Empire | Web Content Writing
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cTrader is another free platform that allows you to backtest strategies. You can create automated trading strategies using cTrader cBots, which are trading algorithms written in Microsoft C#. cBots can be backtested using historical market data.

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2 Define your strategy and parameters

The next step is to define your technical analysis strategy and the parameters that you want to backtest. A strategy is a set of rules and conditions that determine when to enter and exit a trade, based on technical indicators, patterns, or signals. You should have a clear and objective definition of your strategy, as well as the assumptions and limitations that you are making. For example, you can define a simple moving average crossover strategy that buys when the 50-day moving average crosses above the 200-day moving average, and sells when the opposite happens. You should also specify the parameters that you want to test, such as the time frame, the market, the instrument, the position size, the stop loss, and the take profit levels.

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3 Run and analyze the backtest results

The final step is to run and analyze the backtest results. Depending on the platform and the data that you are using, this may take from a few seconds to several minutes or hours. Once the backtest is completed, you should review the results and evaluate the performance of your strategy. Some of the common metrics that you can use are the net profit, the return on investment, the win rate, the drawdown, the profit factor, and the Sharpe ratio. You should also look at the equity curve, the trade history, and the distribution of returns. You should compare the results with your expectations and goals, and identify the strengths and weaknesses of your strategy.

Backtesting technical analysis strategies on a budget is possible if you use the right resources and tools. However, you should also be aware of the limitations and pitfalls of backtesting, such as data quality, curve fitting, over-optimization, and survivorship bias. You should always test your strategies on multiple data sets, scenarios, and markets, and validate them with forward testing and live trading.

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Samaara Das

Financial Market Algorithm Developer | Happy to share my free algos
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Your strategy might be over-fitted. That means that you've optimized it so much that it only works for a particular backtesting range. If a strategy is over-fitted, it might fail to work on other instruments. 1 way you could avoid this is by increasing the number of trades a.k.a. sample size. Do this by increasing your backtesting range. The more trades, the more reliable your strategy.

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4 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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Mukund Bagaria

Founder, M Bagaria FinCorp | Wealth Management Expert | Crafting Paths for Your Insurance Needs
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How long should a trading strategy be backtested? When backtesting trading strategies, it's important to consider both the number of trades and the duration of the test. Aiming for 250-750 trades can provide statistical reliability. For day trading strategies, which typically have one trade per day, use 2-3 years of data to get enough trades, but extending the backtest to around 20 years is better to capture various market conditions. For swing trading strategies with fewer monthly trades, backtest over at least 10 years. Overall, a longer testing period with more trades is generally more effective in ensuring the strategy's robustness across different market phases.

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How can you backtest technical analysis strategies on a budget?

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1 Choose a backtesting platform

2 Define your strategy and parameters

3 Run and analyze the backtest results

4 Here’s what else to consider

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How can you backtest technical analysis strategies on a budget?

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1 Choose a backtesting platform

2 Define your strategy and parameters

3 Run and analyze the backtest results

4 Here’s what else to consider

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