AlphaX: An AI-Based Value Investing Strategy for the Brazilian Stock Market

TL;DR

AlphaX is an AI-driven value investing strategy tailored for the Brazilian stock market, demonstrating superior risk-adjusted returns over benchmarks and technical indicators through bias-controlled simulations.

Contribution

The paper introduces AlphaX, a novel AI-based value investing approach that effectively mitigates overfitting biases, outperforming benchmarks and common technical indicators in the Brazilian market.

Findings

AlphaX outperforms major Brazilian market benchmarks.

AlphaX shows statistically significant better performance than RSI and MFI.

Bias control in simulations enhances strategy robustness.

Abstract

Autonomous trading strategies have been a subject of research within the field of artificial intelligence (AI) for aconsiderable period. Various AI techniques have been explored to develop autonomous agents capable of trading financial assets. These approaches encompass traditional methods such as neural networks, fuzzy logic, and reinforcement learning, as well as more recent advancements, including deep neural networks and deep reinforcement learning. Many developers report success in creating strategies that exhibit strong performance during simulations using historical price data, a process commonly referred to as backtesting. However, when these strategies are deployed in real markets, their performance often deteriorates, particularly in terms of risk-adjusted returns. In this study, we propose an AI-based strategy inspired by a classical investment paradigm: Value Investing. Financial AI models are highly susceptible to lookahead bias and other forms of bias that can significantly inflate performance in backtesting compared to live trading conditions. To address this issue, we conducted a series of computational simulations while controlling for these biases, thereby reducing the risk of overfitting. Our results indicate that the proposed approach outperforms major Brazilian market benchmarks. Moreover, the strategy, named AlphaX, demonstrated superior performance relative to widely used technical indicators such as the Relative Strength Index (RSI) and Money Flow Index (MFI), with statistically significant results. Finally, we discuss several open challenges and highlight emerging technologies in qualitative analysis that may contribute to the development of a comprehensive AI-based Value Investing framework in the future