TITLE:
Is the Market Truly in a Random Walk? Searching for the Efficient Market Hypothesis with an AI Assistant Economist
AUTHORS:
Lizhi Xin, Kevin Xin
KEYWORDS:
Random Walk, Efficient Market Hypothesis, Genetic Programming, Machine Learning, Quantum-Like Evolutionary Algorithm, AI Assistant Economist
JOURNAL NAME:
Theoretical Economics Letters,
Vol.15 No.4,
August
4,
2025
ABSTRACT: The equity market is known for its uncertainty and randomness. While the market and the participating traders may seem like independent entities in their own right, but it is the foray of traders that makes the market in a random walk, as the market’s volatility influences the traders’ judgement on which action to take; the market and traders are “entangled together” in this way. This paper presents a methodology to model both the market’s volatility and traders’ actions by drawing on the concept of quantum superposition to illustrate that it is indeed the “interactions” of both the market and traders that result in the random walk, fully conforming to the efficient market hypothesis. We’ve also developed an AI assistant economist that’s powered by a quantum-like evolutionary algorithm to produce short-horizon predictions of the future trend of the market based on Darwinian natural selection.