A Practical Guide to Backtesting Toby Crabel's NR and ORB Patterns

Toby Crabel's trading philosophy is built on a foundation of statistical evidence, and the only way to truly adopt this philosophy is to engage in the process of backtesting. Backtesting is the process of applying a trading strategy to historical data to determine its effectiveness. It is a important step in the development of any trading system, and it is particularly important for strategies that are based on statistical patterns, such as Crabel's NR and ORB patterns. This article will provide a practical, step-by-step guide to backtesting these effective patterns.

The first step in backtesting is to acquire the necessary tools and data. The most important tool is a backtesting platform, which can range from a simple spreadsheet to a sophisticated software program. For those who are new to backtesting, a spreadsheet can be a great way to start. It allows for a high degree of flexibility and can be used to test a wide variety of strategies. More advanced traders may prefer to use a dedicated backtesting platform, which can automate much of the process and provide more detailed performance metrics. The other essential component is historical data. This can be obtained from a variety of sources, including brokerage firms, data vendors, and free online sources. It is important to use high-quality data that is free from errors and that covers a long enough period to be statistically significant.

Once the tools and data are in place, the next step is to define the trading rules. This is the most important step in the backtesting process, as it will determine the accuracy of the results. The rules should be clear, objective, and unambiguous. For example, when backtesting the NR7 pattern, the rules might be as follows:

• Entry: Buy on a breakout above the high of the NR7 day, sell on a breakout below the low.
• Stop-loss: Place a stop at the opposite end of the NR7 day's range.
• Profit target: Use a fixed risk-reward ratio of 2:1.

With the trading rules defined, the backtesting process can begin. This involves going through the historical data, bar by bar, and applying the trading rules. For each trade, the entry price, exit price, and profit or loss should be recorded. This can be a tedious process, but it is essential for obtaining accurate results.

Once the backtesting is complete, the next step is to analyze the results. This involves calculating a variety of performance metrics, such as the total profit or loss, the win rate, the average win, the average loss, and the maximum drawdown. These metrics will provide a clear picture of the strategy's performance and will help to determine whether it has a positive expectancy. It is also important to look at the equity curve, which is a graphical representation of the strategy's performance over time. A smooth, upward-sloping equity curve is a sign of a robust and reliable strategy.

Finally, it is important to be aware of the common pitfalls to avoid when backtesting. One of the most common is curve-fitting, which is the process of optimizing a strategy to fit the historical data. This can lead to a strategy that looks great on paper but fails to perform in real-time trading. To avoid curve-fitting, it is important to use a large and diverse data set and to avoid excessive optimization. Another common pitfall is survivorship bias, which is the tendency to only include successful stocks in a backtest. This can lead to an overly optimistic view of a strategy's performance. To avoid survivorship bias, it is important to use a data set that includes delisted stocks.

Backtesting is an essential skill for any serious trader. It is the only way to truly know whether a trading strategy has a statistical edge. By following the steps outlined in this article, traders can develop a robust and reliable backtesting process and can gain the confidence they need to trade with the statistical precision of Toby Crabel.