Applied Game Theory & Behavioral Finance: Strategic Incentives, Market Psychology, and Decision Models for Modern Finance (Quantitative Economics & Python Series Book 15)

Reactive Publishing Financial markets are not efficient machines. They are adaptive ecosystems driven by incentives, beliefs, deception, cooperation, and conflict. While classical finance assumes rational actors, real-world decision makers bluff, anchor, panic, imitate, herd, and occasionally behave like predators.

This book brings modern game theory into direct contact with behavioral finance to explain how strategic agents actually think, coordinate, and compete under uncertainty. Rather than treating markets as static puzzles, it examines them as dynamic games, complete with hidden information, payoffs, signaling, adverse selection, moral hazard, commitment strategies, and recursive forecasting.

Inside you’ll learn how to:

• Model markets as competitive and cooperative games
• Identify behavioral biases that distort valuation and risk
• Understand how incentives reshape market equilibria
• Use signaling theory to analyze price action and sentiment
• Detect information asymmetries in trading and negotiation
• Map the strategic structure of bubbles, crashes, and panics
• Compare rational equilibrium vs. real-world outcomes
• Forecast adversarial behavior in trading, M&A, and macro strategy

For traders, investors, analysts, allocators, and strategic operators, this is a guide to seeing financial markets as they truly are: social games played by imperfect minds with competing goals. Master the patterns, and advantage becomes structural.