AI-Trader: Critical Backtesting Bug - Future Data Leak!

Hey everyone! I'm super excited to dive into a critical issue I found while exploring the awesome AI-Trader project. Big thanks to the team for creating such a cool agent-based trading framework. In my deep dive into the detailed thought and action logs, I uncovered a serious problem that could totally mess up the backtesting results: Future Information Leakage, also known as Lookahead Bias. Let's break down the issue and what we can do to fix it. This is a crucial topic for anyone using this project, so pay close attention!

The Problem: Data from the Future is Sneaking In! 🕵️‍♀️

The Core Issue: Future Information Leakage is a big deal in backtesting. Imagine trying to predict the stock market, but you already know what's going to happen tomorrow! That's essentially what's happening with the get_information tool in AI-Trader. This tool is designed to fetch market news and data, but it's unintentionally grabbing information from future dates. This is a massive problem because it lets the trading agent make decisions based on information it shouldn't have access to, thus giving unrealistic, and incorrect, results.

The Culprit: The get_information Tool. This tool is the gateway for the agent to access market data, often using search engines or similar services. The problem lies in how it fetches and filters this information. The current setup doesn't always prevent it from pulling up news articles and data that were published after the date being backtested. This means the agent gets a sneak peek at future events, like stock prices soaring due to upcoming news, which skews its trading decisions and makes the backtest results invalid.

The Consequence: Invalid Backtest Results. When the agent can see into the future, it's like cheating in a game. It'll make trades that look great in the backtest because they're based on knowledge that wasn't available at the time. This makes the backtest results completely unreliable for judging the agent's real-world performance. You might think your agent is a superstar trader, but in reality, it's just benefiting from future knowledge. This is not good!

Why This Matters

• Accuracy: The most important thing is that backtesting results must be reliable and reflect what is likely to happen in reality. This bug undermines the very foundation of the backtesting process.
• Trust: If we can't trust the backtesting results, we can't trust the agent's performance. This erodes confidence in the project and its potential.
• Development: Fixing this issue is necessary to ensure we are improving the agent's strategies based on reliable feedback.

The Smoking Gun: How I Found the Leak 🔍

I was deep into analyzing the verbose logs of the trading agent during a backtest, and that's when I found the smoking gun. It all started with my work on PR #73, where I wanted to improve the agent's logging. While reviewing these logs, I came across undeniable evidence of the Future Information Leakage. Let me show you exactly what happened:

The Backtest Date: October 6, 2025

I ran a backtest for October 6, 2025. The agent was making decisions, and I was watching closely, examining every move. The agent needed information, and it turned to get_information.

The Crucial AMD-OpenAI Partnership Search

The agent was trying to decide whether to buy AMD stock. It made two calls to get_information. The second call was crucial. The agent was looking for info on the AMD-OpenAI partnership. This search was vital for its decision.

The Leakage: Future News Revealed

Here’s where it went wrong. The get_information tool returned an article, but the article was published four days later! Here's the key excerpt from the log:

[tool/start] [chain:... > tool:get_information] Entering Tool run with input:
"{ 'query': 'AMD OpenAI partnership October 2025 stock performance'}"
content='\nURL: https://www.fool.com/investing/2025/10/10/amds-stock-surged-24-on-its-openai-partnership-and/\nTitle: AMD's Stock Surged 24% on Its OpenAI Partnership and Is Near an All-Time High. Is It Still a Buy?\nDescription: AMD has played second fiddle to Nvidia throughout the AI arms race.\nPublish Time: **2025-10-10T10:00:00.000Z** ...'
// Note: The transaction happens on **2025-10-06**, but the news is published on **2025-10-10**.

As you can see, the agent made its decision on October 6, 2025, but the news article about AMD's stock surge was published on October 10, 2025! This is a clear example of Future Information Leakage.

The Impact: A Buy Decision Based on Future Knowledge

This future news heavily influenced the agent's decision-making process, directly leading to a trade. Here's how the agent reacted to that future data:

AI: Now I can buy AMD shares:
Tool: {"NVDA":8,"MSFT":4,"AAPL":7,"...","AMD":1, ...} // Purchase successfully executed

The agent bought AMD shares because of the information it got from the future. This is a clear case of lookahead bias. The agent bought AMD stock because it