What is the Difference Between Backtesting and Forward Testing in Algo Trading?

In the complex world of algo trading, there are a lot of uncertainties and scope for error. Traders turn to two methods to boost their confidence regarding their trading strategies: backtesting and forward testing. By performing these vital tests, traders evaluate their strategy and check for any faults, thereby giving them a certain amount of assurance and comfort. In this article, we will examine what backtesting and forward testing is, how they are performed, and why they are important!

Understanding the Terms

Algo trading is a method of trading where a computer program or 'algorithm' is used to execute orders automatically in the financial markets (stocks, futures & options, commodities, etc). The algorithm contains pre-defined instructions like price, volume, etc. These algos execute trades on time and without any bias. But how can you judge which algorithm to use when? Let’s find out below!

Backtesting

Algorithms in trading are built using complex mathematical and statistical models. Just like in a math exam, where using the wrong formula could lead to incorrect answers, algo trading carries the risk of applying the wrong algorithm to specific market conditions. The solution? Much like practising previous years' questions in school to avoid mistakes in the exam, traders use backtesting to find gaps in their strategy. 

Backtesting is a method that allows a trader to test their trading strategy using historical data, and thereby fix potential errors before deploying it in real-world markets. It helps refine the strategy and understand if it could have worked in the past. 

Forward Testing 

Now what if the math syllabus is different this year? The past papers are not a reflection of the required knowledge. What can you do to prepare for the exam? You can simply solve practice papers that are available based on current or real-time requirements. This is what forward testing does!

Forward testing allows you to test your strategy in real time and find out how it performs in the current market. It simulates the real world, so any profits or losses made are just a representation of what would actually happen. 

Backtesting and forward testing ensure your strategy works and is sustained in the dynamic world of trading. But which test is better suited in algo trading? Let’s see below!

Importance in Algo Trading and Key Differences

Now that you understand what each term means, let’s examine why they are important in algo trading. 

Backtesting

• Correct Major Gaps: When you check your strategy against previous scenarios, you can identify significant pitfalls (hidden dangers) that might not be obvious in theoretical models. Backtesting helps find major gaps in your strategy, thereby increasing the overall success rate when applied in live trading markets.

• Proof of Strategy Success: Backtesting is a powerful tool for validating the accuracy of your algorithm. If your strategy performs well in historical data, you can deploy it in live markets with confidence, as you have evidence of its potential effectiveness.

• Ticks Necessary Metrics: Traders can perform comprehensive tests and analyses of metrics like Sharpe Ratio, Maximum Drawdown, and Win/Loss Ratio during backtesting. This detailed examination gives a clear overview of the strategy's performance and helps optimise it. 

Forward Testing 

• Real-Time Analysis: Past successes don’t guarantee future profits, which is why forward testing is crucial. Like a simulation, forward testing allows you to evaluate your strategy in the current market environment. You can test it with virtual trades (paper trading) or real money, giving you a clear view of your strategy’s real-time performance.

• Adaptability Check: Forward testing helps traders combat the question of whether the strategy can adapt to movements. It helps in building dynamic strategies and preparing for unforeseen circumstances. 

• Considers Execution Factors: Your strategy may excel under perfect conditions without any execution troubles. But, in the live market, there are many factors like slippages, (differences between expected and actual prices due to quick market shifts) latency (delay in trade execution), and order fill rates. Forward testing considers all these factors and gives a realistic view. 

Now that we have established the need for the tests, let’s compare both of them:

Criteria	Backtesting	Forward Testing
Type of Data Used	Historical	Real-time
Time and Duration	Quickly performed and processed	Slower, move with live markets
Purpose	Asses major gaps in strategy	Simulate real market and check execution efficiency

Backtesting and forward testing have their own advantages and necessities. It's not a question of which test to conduct. As an algo trader, you must test your strategy using both these tests to gain the best results. By using them simultaneously you can thoroughly optimise your strategy! 

How Are Backtesting and Forward Testing Performed?

With the importance and key differences in mind, we’ll dive into how you can perform each of these tests on your strategy:

Backtesting

1. Outline the Strategy: This means recognising the major moves in the strategy, like entry and exit points, position sizing (the trade size based on your capital and risk appetite), etc. Once you get this information, you can move to the next step. 

2. Gathering Historical Data: Data can be taken either manually or through software platforms. However, manual data collection can take more time and effort. Backtesting platforms, such as Amibroker, TradeTron, and TradingView, are available to run backtests. You must also determine the timeframe for testing your strategy. Consider relevant market conditions, significant events, data availability, and the type of strategy you’re using.

3. Run the Strategy: Backtesting is done in two sets of data samples, in-sample and out-of-sample data. This ensures the strategy isn’t over-optimised and over-fitted for one set of data. It checks reliability in different situations. Run the strategy using in-sample data first, then out-of-sample data. 

(In-sample data is the historical data you use to develop and refine your trading strategy. Out-of-sample data is a different set of historical data that you don’t use when building the strategy. It allows you to test how well your strategy would perform in real market conditions that it hasn’t encountered before.)

4. Analysis and Improvement: Interpret and analyse the results from the backtest. Use metrics like win/loss ratio, Sharpe Ratio, etc. Based on these, make necessary changes in the strategy.

Also Read: Ultimate Guide to Backtesting

Forward Testing

1. Set up Demo Account: The first step to forward testing is to set up a paper trading or demo account on platforms like AlgoTest and TradeTron. This lets you trade without risking real capital—just make sure to size your account based on your true capacity. But that's just one way. To truly uncover real execution issues, forward testing with a small amount of real money is key. Only then can you spot any potential hurdles in live market conditions and fine-tune your strategy for success.

2. Run the Strategy: Once the account is ready, you can start executing the strategy as you would in the live market. 

3. Monitor and Record the Performance: Now sit back and analyse the performance of your strategy, record where there are major faults or where the strategy fails to provide optimal results. 

4. Analysis and Improvement: Take the results and see where you can improve the strategy so it performs better in the live market.

This is how you can backtest and forward-test your strategy before deploying it in the live market! 

Conclusion 

Backtesting and forward testing are essential prerequisites to algo trading. They each have different requirements and steps to perform. Both of the tests offer risk-free ways to verify strategies. Backtesting is quicker to conduct, but forward testing uses live market data to recheck your strategy. As an algo trader, you must conduct both tests to maximise your chances of profits!