What happens when human psychology collides with the precision of quantitative modeling?
In Quantitative Behavioral Finance, Vincent Bisette fuses the irrational beauty of human behavior with the hard logic of data science, revealing how emotion, cognition, and bias can be measured, modeled, and turned into sustainable alpha.
This isn't another "behavioral finance 101" guide. It's a deep, modern synthesis for the algorithmic age-where traders and investors learn to quantify fear, greed, and overconfidence with mathematical rigor. Bisette translates the chaos of market sentiment into structured, testable signals using Bayesian inference, machine learning, and predictive modeling.
Inside you'll discover:
The cognitive fingerprints of market anomalies, and how to systematize them into quant signals.
Modeling frameworks for behavioral volatility, momentum decay, and irrational herding.
Python-based behavioral simulations that merge decision theory with real-world data.
Cross-disciplinary insights from neuroscience, complexity theory, and behavioral economics.
Practical trading applications that transform psychological tendencies into measurable edge.
By bridging the art of human psychology with the science of quantitative systems, this book rewrites what it means to understand markets, and what it means to profit from them.
Whether you're a portfolio manager, algorithmic trader, or researcher, this is your blueprint for the next frontier of finance: turning human behavior into data, and data into alpha.