Optimal Statistical Inference in Financial Engineering

This book examines how stochastic models can effectively describe actual financial data and illustrates how to properly estimate the proposed models. It discusses the probability, statistical inference, testing hypothesis, and discriminant analysis for independent observations. The book also explores stochastic processes, time series models, their asymptotically optimal inference, prediction, option pricing theory, the statistical estimation for portfolio coefficients, and VaR problems. The final chapters cover models for interest rates and discount bonds, their no-arbitrage pricing theory, problems of credit rating, and the clustering of stock returns.