In the emerging age of AI in stock trading, the allure of using artificial intelligence to predict stock market trends is a seductive one. The idea often arrives with flashy graphs and claims of high accuracy, tempting many programmers and investors into believing that an AI can predict stock prices. But let’s cut through the hype and address the reality.
First off, let’s consider the basics of stock market probabilities: any stock has a fundamentally binary immediate future—it will either rise or fall. As such, the chance of a correct daily “prediction” is akin to a coin flip—50/50. Neural networks, with their sophisticated algorithms, may seem to have the upper hand in this game, providing a shade more insight than random chance. And, in the very short term, their forecasts might even appear uncannily accurate. But the true test comes when you ask these systems to extend their foresight beyond the present day. Here, their performance typically falters, revealing the limits of this kind of analysis.
Our AI Stock Trading Approach
At our company, we’ve taken a different route. Instead of asking the AI to predict the future, we focus on the trading strategy. Each AI is given different strategies to use. Then, they compete with other AI’s. We use AI to evaluate the current day’s trading patterns in the context of their unique strategy. The AI’s verdict then passes through additional proprietary filters we’ve crafted. This enhances the decision-making process to produce more reliable signals for each stock. We then use what’s called a genetic algorithm to incrementally tune the best strategies.
Our approach mimics the principles of evolution by pitting AIs against each other to identify the most effective trading strategy. Each strategy is rigorously tested against 20 years of historical stock data and across hundreds of stocks. The goal is to find the strategy that maximizes profits while minimizing drawdowns. This competitive process involves ‘breeding’ and evaluating tens of thousands of strategies, ensuring that only the most successful ones emerge as winners. By continuously refining and optimizing these strategies, we harness the full potential of AI to navigate the complexities of the stock market effectively.
Conclusion
So, what’s the takeaway for those interested in AI and stock trading? It’s that success lies not in seeking a crystal ball but in leveraging AI for what it excels at: data analysis. Using AI to sift through the vast quantities of market data to extract meaningful patterns requires a blend of statistical techniques, computational power, and, most importantly, a well-thought-out approach to data science. This is where the true potential of our AI-assisted trading lies—not in predicting the unpredictable but in providing informed insights that guide better investment decisions.
