Learn RealTest the Right Way

Alright, let’s dive into an example of backtesting. Imagine you’ve got a trading strategy that uses two moving averages to generate buy and sell signals. Here’s how you’d go about backtesting it:

• Define Your Strategy: First, clearly outline the rules of your strategy. For instance, you might decide to buy when the short-term moving average crosses above the long-term moving average and sell when it crosses below.
• Choose Your Software: Use backtesting software to input your strategy. This software will apply your rules to historical market data.
• Run the Backtest: The software will simulate all the trades your strategy would have made over a specified period, generating buy and sell signals based on your moving average rules.
• Analyze the Results: Look at the performance metrics like compound annual return, drawdown, percentage of winning trades, and average win/loss size. This helps you understand how your strategy would have performed historically.
• Refine and Validate: Check if the strategy is robust across different market conditions and parameter values. Ensure it wasn’t just a fluke by testing various combinations of moving averages.

This process helps you determine if your strategy is worth trading in real-time. If it didn’t perform well in the past, it’s unlikely to succeed in the future .

AmiBroker and RealTest are both powerful tools for backtesting and trading system development, but they have some key differences:

• Ease of Use: RealTest is generally easier to program and backtests faster than AmiBroker. It allows for multi-system backtests and can generate orders across multiple systems in a single step, which is a significant advantage for traders looking to streamline their processes .
• Charting and Technical Analysis: AmiBroker offers more advanced charting and technical analysis capabilities compared to RealTest. While RealTest is designed primarily for algorithmic trading strategies, its charting functionality is more rudimentary .
• Community and Support: AmiBroker has a larger user base and more community support, which can be beneficial for new users seeking help and resources. RealTest, being relatively new, has a smaller community, which might mean less readily available support .
• Cost and Performance: Both platforms are cost-effective, but RealTest is noted for its ability to handle multi-system portfolios and optimize capital allocations between systems efficiently. AmiBroker, on the other hand, is known for its speed and affordability, making it a top choice for many traders .

Ultimately, the choice between AmiBroker and RealTest may depend on your specific needs, such as the importance of charting capabilities versus ease of programming and backtesting speed . If you’re exploring these platforms, consider what aspects are most critical for your trading strategy. 

Absolutely, backtesting is worth it. It’s one of the most powerful tools in your trading toolbox if you use it correctly. Backtesting allows you to apply your trading system rules to historical data, generating buy and sell signals that would have occurred in the past. This process gives you valuable performance statistics like compound annual return, drawdown, and win/loss ratios .

The real value of backtesting lies in its ability to show whether your strategy was profitable in the past. If it wasn’t, it’s unlikely to be profitable in the future. Conversely, if it was profitable, there’s a chance it might continue to be so. Backtesting helps eliminate unprofitable systems and builds confidence in your strategy by revealing how it performs across different market conditions .

Without backtesting, you’re essentially trading blind, hoping your strategy works without any evidence. It’s not just about finding the best historical performance, it’s about ensuring your strategy is robust and adaptable to future market conditions. So, yes, backtesting is definitely worth the effort .

To get reliable results from backtesting, you generally need a substantial number of trades. Ideally, you should aim for at least 500 to 1,000 trades to start understanding a system’s performance . This amount of data helps ensure that your backtest results are statistically significant and not just a result of random chance or overfitting to past data .

If your system is complex with many rules, you’ll need even more trades to validate it properly. The more rules you have, the more data you need to avoid overfitting . Backtesting over a long period, like 30 years, across a wide universe of stocks, can provide a comprehensive evaluation of your trading systems .

Remember, the goal is to test through various market conditions bull, bear, and sideways markets to get a true sense of how your system performs .

To backtest your own strategy effectively, follow these steps:

• Document Your Trading Rules: Clearly outline your strategy using pseudocode. This means writing your rules in logical statements, like “If this and this happens, buy” .
• Ensure Objectivity: Make sure your rules are 100% objective. Avoid subjective criteria like “trending up” without a clear definition. Use specific indicators, such as a stock being above the 200-day moving average .
• Fully Define Your Strategy: Cover all scenarios, including buy/sell signals, position sizing, stop losses, and exit conditions. This ensures there are no subjective decisions during the backtest .
• Code Your Strategy: Convert your pseudocode into the programming language of your chosen backtesting software. Ensure there are no syntax or logic errors .
• Run the Backtest: Execute the backtest and verify that the signals are generated and executed correctly. Check different trade outcomes to ensure accuracy .
• Analyze Performance: Once verified, analyze the performance metrics like return, drawdown, and win/loss ratio. This helps evaluate the strategy’s effectiveness .

By following these steps, you can ensure your strategy is robust and ready for real-time trading.

The time it takes to backtest a trading strategy can vary significantly based on your experience and the complexity of the strategy. Initially, it might take a fair bit of time as you familiarize yourself with the process and ensure everything is set up correctly. However, with practice, this time can be reduced substantially.

• Initial Learning Curve: When you’re just starting, it might feel like it takes ages. You could spend days or even weeks getting everything right, especially if you’re new to coding your strategy and using backtesting software .
• With Experience: Once you’re more comfortable with the process, you can streamline it significantly. For example, I’ve managed to go from concept to a fully automated system in about 2 hours, though typically, it might take a few days to ensure everything is thoroughly tested and ready for live trading .
• Efficient Backtesting: Using software like AmiBroker, once your strategy is coded, running a backtest over 30 years of data across thousands of stocks can take just a minute. The key is having the right setup and process in place .

So, while it might seem daunting at first, with the right tools and practice, backtesting can become a quick and efficient part of your trading routine.

Testing your trading strategy involves several key steps to ensure it’s robust and reliable. Here’s a concise guide to get you started:

• Document Your Rules: Begin by clearly documenting your trading rules in pseudocode. This means writing out the logic in plain language, like “If this and this happens, buy” . This step is crucial to avoid jumping straight into coding without a clear plan.
• Ensure Objectivity: Make sure your rules are 100% objective. Avoid subjective terms like “trending up” without a specific definition. For example, define “trending up” as when a stock is above the 200-day moving average .
• Fully Define Your Strategy: Cover all scenarios, including buy/sell signals, position sizing, stop losses, and exit conditions. This ensures there are no subjective decisions during the backtest .
• Code Your Strategy: Convert your pseudocode into the programming language of your chosen backtesting software. Ensure there are no syntax or logic errors .
• Run the Backtest: Execute the backtest and verify that the signals are generated and executed correctly. Check different trade outcomes to ensure accuracy .
• Analyze Performance: Once verified, analyze the performance metrics like return, drawdown, and win/loss ratio. This helps evaluate the strategy’s effectiveness .

By following these steps, you can ensure your strategy is robust and ready for real-time trading.