Applied Stochastic Processes in Finance

This book presents a comprehensive synthesis of the research works conducted by Professor Mohammed Bouasabah on the application of stochastic processes in finance. It explores how randomness and uncertainty can be modeled, quantified, and used to understand and forecast financial phenomena.Through six interconnected chapters, the author examines both classical and modern stochastic frameworks - including the Geometric Brownian Motion (GBM), the Vasicek and Heston models - and applies them to real financial data such as exchange rates, stock market indices, and derivative instruments.The book also investigates parameter calibration techniques, optimization approaches for stochastic volatility models, and the integration of stochastic processes with machine learning algorithms for predictive analysis. Beyond their mathematical formulation, these models are presented as practical tools for financial decision-making, technical analysis, and risk assessment.The work emphasizes the balance between theoretical rigor and empirical validation, illustrating how stochastic modeling remains a cornerstone of modern quantitative finance.

Autorentext
Mohammed Bouasabah is a Professor at Ibn Tofail University. He has dedicated his career to connecting mathematical theory with financial applications, focusing on the use of stochastic processes in finance. He is the author of several scientific articles addressing different aspect of stochastic processes and their applications in finance.