How to Use ChatGPT to Backtest Forex Strategies – a Step-by-Step Guide

I always recommend that traders backtest their strategies. AI platforms now make this much easier by writing code and generally speeding up the process. I’ve spoken to many traders who tell me they never back-tested before AI arrived on the scene.

ChatGPT is considered one of the best AI models for generating code to backtest, and many traders have gravitated towards it for this reason. Let’s take a closer look at how to use ChatGPT to backtest Forex strategies.

What Backtesting Is and Why It Matters for Forex Traders

Backtesting is the process of applying a trading strategy to historical data to assess its performance. In other words, backtesting shows whether a trading strategy would have been successful.

Without backtesting, the only other way to assess its performance is in real time, known as “forward testing.” Forward testing is an essential step for evaluating a trading strategy, but it can be time-consuming. In contrast, backtesting can immediately tell a trader whether a trading strategy is profitable over a long period, e.g., a year, without requiring they wait a whole year to find out!

Although backtesting does not guarantee future profitability, it’s unlikely that any strategy will perform well in real time if the backtest results are unprofitable. That’s why backtesting matters because it weeds out unprofitable trading strategies before you begin in real-time.

What Is the Purpose of Backtesting Forex Strategies?

Backtesting any Forex strategy will answer the three most critical questions for any strategy:

1. Does my strategy have a statistical edge?
2. How does it perform during different market conditions?
3. What drawdowns should I expect?

To find the answer to the above three questions, a backtest will provide the strategy’s performance, including the following metrics:

1. Win rate and expectancy
2. Profit factor
3. Maximum drawdown
4. Net Profit or Loss
5. Percentage Gain or Loss

How to Use ChatGPT to Design Robust Backtests

Step 1: Define the Strategy’s Concept

I like to begin by defining the concept first, so it’s clear in my head what the strategy is trying to achieve. For example, “This strategy aims to capitalize on an engulfing candlestick reversal in the direction of a trend, defined by two moving averages.” Then I detail the entire plan in writing.

Step 2: Translate the Strategy’s Concept into Hard Trading Rules

Remember, a complete trading strategy must contain the following four rules:

1. Trade entry rules
2. Stop-loss rules
3. Take profit rules
4. Risk management rules

Defining these rules will give ChatGPT what it requires to get to the next step in testing a strategy.

Step 3: Ask ChatGPT to Generate Code or Upload Data to Test the Strategy

ChatGPT can either write code for a platform such as TradingView or MetaTrader 4, or test my strategy, if I upload price data. I recommend that, in most cases, ChatGPT write code to test the strategy on a third-party trading platform.

Step 4: Analyze and Refine Results

ChatGPT can also help at this stage. If I prompt it, it can analyze the results and suggest improvements to the strategy.

What ChatGPT Can and Cannot Do

What ChatGPT can do:

• Help to clearly define strategy rules
• Generate code for a variety of platforms to backtest strategies
• Explain the results and performance metrics
• Suggest optimizations and stress tests
• Process and summarize large volumes of news, reports, or social media to identify sentiment or opportunities

What ChatGPT cannot do:

• In most cases, ChatGPT cannot define the core strategy or check the results.
• Cannot connect to live markets or act on its own to place live trades.
• Cannot make the “final decision” on whether to run a strategy.
• ChatGPT does not predict future Forex prices

I like to think of ChatGPT and AI in general as a research assistant rather than a trading bot or human-level trader. Remember, AI models are not financial advisors, and you should not consider any information from AI as professional financial guidance.

Preparing Your Forex Strategy for ChatGPT

Before prompting ChatGPT, prepare your strategy details:

1. Entry. What are the parameters or indicators to enter a trade?
2. Timeframes. On what timeframe(s) does the strategy operate? E.g., M15, H1, Daily, etc.
3. Currency pair(s). On which currency pairs should the strategy run?
4. Time of Day. Are there times of the day the strategy should run (particularly important for intraday trading)?
5. Exclusion days. Should the strategy exclude entering trades near specified economic announcements?
6. Stop-loss. What are the stop-loss rules? For example, this could be a fixed pip amount, or dependent on indicators, e.g., when a candle closes below a moving average.
7. Take profit. When should the strategy take profits? Should there be a trailing stop-loss? Should the take-profit be relative to the size of the stop-loss, e.g., automatically take profits at a 2:1 reward/risk ratio?
8. Risk management. What are the position sizing rules? What is the maximum each trade should be allowed to risk as a percentage of the account if it gets stopped out? Should each trade have the same position size, or the same percent risk on the account?

The more precisely you define the strategy, the better ChatGPT will handle your requests.

Using ChatGPT to Formalize Strategy Rules

Converting ideas into objective rules can be challenging, especially when the strategy is complex or relies on discretionary concepts, such as chart patterns. I have found that ChatGPT excels at this step and has allowed me to mechanically test ideas I would not have been able to write as formal rules without its help.

How to Prompt ChatGPT

Instead of asking broad questions, the best way to prompt is to specify what you want in terms of clear outputs. Communicating in this style to ChatGPT can take practice, but I believe everyone can get the hang of it over time.

Let’s take an example of a highly discretionary chart pattern, the Head and Shoulders (H&S). I can prompt ChatGPT to: “Give me a mechanical trading strategy that uses the Head & Shoulder reversal pattern on the hourly timeframe but follows the daily trend. I want you to suggest take-profit and stop-loss levels.”

ChatGPT will then produce a strategy along with those parameters for me to examine and refine. Try it yourself!

Suggested Prompt Templates

Prompts can be as varied as your imagination, but here are a few to help you get started:

• “Give me a Pin Bar reversal trading strategy on the daily timeframe that places trades in line with support and resistance levels.”
• “I want a GBPUSD trading strategy that places trades on the breakout of the Asian range.”
• “I want a strategy to buy on pull-backs on the 15-minute chart in the direction of an established trend, using MACD and RSI.”

These are very broad strategy requests, and I can use these to see what ChatGPT gives. Or I can make them more specific based on my own requirements before requesting the prompt.

Generating Backtest Code with ChatGPT

ChatGPT can generate code for trading strategies almost instantly, for use on some of the most popular trading platforms.

Supported programming languages include:

• MetaTrader (MQL4/MQL5 Expert Advisors)
• TradingView (which uses the Pine Script programming language)
• Python—many automated forex trading software and brokers support Python through their own APIs or third-party libraries.

Traders can use ChatGPT to request:

• Strategy templates
• Indicator calculations
• Trade execution logic

Validating and Debugging Backtest Scripts

AI is far from 100% accurate, and there is a reasonable possibility of errors in the code, which can lead to incorrect conclusions.

First, if the code does not run on the trading platform (e.g., MetaTrader 5 or TradingView), paste the error message into ChatGPT to help with debugging.

Second, there can still be errors even if the code runs fine without any bugs. I recommend comparing the trades in the backtest with manual spot checks, i.e., manually test sample periods of the strategy and compare the results to the backtest results, and ensure the two sets of results are identical. For example, I may find that the indicator setting used by ChatGPT does not match the one I had in mind, or there are differences in the position sizing or execution timing. Do not blindly trust the results without verification.

To help me validate a strategy, I may consider a prompt to list “edge case scenarios,” with a prompt such as:

“List all possible edge cases and exceptional scenarios in the trading strategy. Consider data gaps, zero volume periods, sudden price spikes, and conditions where indicators might be undefined.”

Interpreting Backtest Results with ChatGPT

A backtest will provide a lot of performance data, which can sometimes be overwhelming. Use ChatGPT to help explain key metrics such as:

• Win rate vs. expectancy
• Maximum drawdown
• Profit factor
• Risk-adjusted returns

Understanding how to evaluate performance in a way that’s useful for my trading goals will help me decide whether to move forward with a strategy. For example, I may wish to have short drawdown periods, because I want to withdraw profits each week or month. Traders will often have a variety of goals beyond simple profitability.

Using ChatGPT to Improve and Stress-test Strategies

Stress-testing a strategy means intentionally trying to "break" it by exposing it to extreme, unusual, or adverse market conditions (such as crashes, high volatility, or range-bound markets) to assess its robustness.

Practical Examples and Prompt Templates

I can ask ChatGPT for recommendations to stress-test a strategy with prompts such as:

• “How can I stress-test this Forex strategy?”
• “Suggest robustness checks for this backtest.”
• “Which parameters are most sensitive?”

I may also want to run my strategy through past periods of shock to see how it performed, e.g., when U.S. tariffs were announced, or when central banks made unexpected interest rate decisions.

Risks, Limitations, and Best Practices

Backtesting is no guarantee for future performance, but here are some best practices to mitigate the risks and improve strategies:

1. Avoid over-optimization. If a backtest is successful, rerun it on a different period to ensure it has similar results.
2. Test across multiple pairs. There may be strategies designed to run on specific pairs, but if the strategy is neutral to the pair, run tests on different pairs.
3. Rolling test. Continuously re-optimize parameters on a rolling in-sample period and test on the subsequent out-of-sample period to simulate real-time adaptation and prevent data snooping.
4. Optimize Parameters (Parameter Sweep): Once the core test produces robust results, use ChatGPT to help set up a parameter optimization process to find better inputs. Prompt example: “Generate a method to test variations of EMA periods 5, 8, 13 and 21 and ATR multiplier (e.g., 1, 2, 3) to find the combination that provides the highest Sharpe Ratio and net profit.”

Essentially, never rely on a single backtest!

Conclusion

Backtesting is a skill all traders should master, and ChatGPT makes it much more accessible. Traders without programming skills can formalize their models almost instantly and run backtests. While backtesting is not a guarantee of profitable trading, it can quickly help a trader determine whether a strategy has the potential to be profitable, needs improvement, or should be discarded. ChatGPT can help formalize a trading strategy and generate code to run backtests on platforms such as TradingView, MetaTrader and third-party APIs using Python. Remember, there must be human oversight to ensure the strategy runs the intended concept and is not over-optimized to a particular data set. AI should support disciplined research - not replace it.