Analyzing Stock Market Dynamics: A Game-Theoretic Perspective

Trading in the stock market is quite risky due to the high level of fluctuations in the stock prices, which are not merely governed by stock fundamentals, technical indicators, trend indicators, etc. Also, machine learning techniques that rely on the historical price data of the stock (expecting past price trends to repeat in the future) are not adequate for accurate stock price predictions. Some additional tool like game theory which can capture all the associated factors affecting the stock price is required to make proper stock price predictions. This paper conducts a game-theoretic analysis of stock market dynamics, focusing on the strategic interactions among institutional investors, individual investors, and market makers, and examines the stability, liquidity, and efficiency of the key players. A payoff matrix is developed to identify potential equilibrium scenarios, offering insights into strategic stability under different market conditions. In this paper, a game theory-based framework for the stock market comprises three key players who navigate strategically to attain an equilibrium state. This study contributes to the growing literature on the application of game theory in finance, providing a structured approach to understanding the strategic dynamics driving stock market behavior.