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.
Autorentext
Masanobu Taniguchi, Junichi Hirukawa, Kenichiro Tamaki
Zusammenfassung
Until now, few systematic studies of optimal statistical inference for stochastic processes had existed in the financial engineering literature, even though this idea is fundamental to the field. Balancing statistical theory with data analysis, Optimal Statistical Inference in Financial Engineering examines how stochastic models can effectively des
Inhalt
Preface. Introduction. Elements of Probability. Statistical Inference. Various Statistical Methods. Stochastic Processes. Time Series Analysis. Introduction to Statistical Financial Engineering. Term Structure. Credit Rating. Appendix. References. Index.