Takeaki Kariya – författare

Generalised Least Squares adopts a concise and mathematically rigorous approach.  It will provide an up-to-date self-contained introduction to the unified theory of generalized least squares estimations, adopting a concise and mathematically rigorous approach. The book covers in depth the ''lower and upper bounds approach'', pioneered by the first author, which is widely regarded as a very powerful and useful tool for generalized least squares estimation, helping the reader develop their understanding of the theory. The book also contains exercises at the end of each chapter and applications to statistics, econometrics, and biometrics, enabling use for self-study or as a course text.

 

This text aims to provide practical models and methods for the quantitative analysis of financial asset prices, construction of various portfolios, and computer-assisted trading systems. In particular, it should be helpful reading for "Quants" (quantitatively-inclined analysts) in financial industries, financial engineers in investment banks; securities companies, derivative-trading companies, and software houses who are developing portfolio trading systems; graduate students and specialists in the areas of finance, business, hardbound economics, statistics, financial engineering; investors who are interested in Japanese financial markets. Throughout the book the emphasis is placed on the originality and usefulness of models and methods for the construction of portfolios and investment decision making, and examples are provided to demonstrate, analysis, models for Japanese financial markets.

The theory of asset pricing has grown markedly more sophisticated since the early 1980s, with the application of powerful mathematical tools such as probability theory, stochastic processes and numerical analysis. The main goal of this text is to provide a systematic exposition, with practical applications, of the no-arbitrage theory for asset pricing in financial engineering in the framework of a discrete time approach. Useful as a textbook on financial asset pricing, the book should also appeal to practitioners in financial and related industries, as well as to students in MBA or graduate/advanced undergraduate programs in finance, financial engineering, financial econometrics, or financial information science.

Robustness of Statistical Tests provides a general, systematic finite sample theory of the robustness of tests and covers the application of this theory to some important testing problems commonly considered under normality. This eight-chapter text focuses on the robustness that is concerned with the exact robustness in which the distributional or optimal property that a test carries under a normal distribution holds exactly under a nonnormal distribution. Chapter 1 reviews the elliptically symmetric distributions and their properties, while Chapter 2 describes the representation theorem for the probability ration of a maximal invariant. Chapter 3 explores the basic concepts of three aspects of the robustness of tests, namely, null, nonnull, and optimality, as well as a theory providing methods to establish them. Chapter 4 discusses the applications of the general theory with the study of the robustness of the familiar Student''s r-test and tests for serial correlation. This chapter also deals with robustness without invariance. Chapter 5 looks into the most useful and widely applied problems in multivariate testing, including the GMANOVA (General Multivariate Analysis of Variance). Chapters 6 and 7 tackle the robust tests for covariance structures, such as sphericity and independence and provide a detailed description of univariate and multivariate outlier problems. Chapter 8 presents some new robustness results, which deal with inference in two population problems. This book will prove useful to advance graduate mathematical statistics students.

This book presents a comprehensive, innovative, integrated, and empirically effective system for cross-sectionally analyzing prices of government bonds (GBs) and corporate bonds (CBs) to timely obtain practically useful information on yield curves and default curves. The system consists of (1) GB-pricing model that values coupon GB and gives yield curve, (2) credit risk rating model of each CB, and (3) CB-pricing model that gives default curve or equivalently term structure of default probabilities (TSDP), which prices credit default swap (CDS). And in view of data science, the empirical effectiveness of the modeling concept, formulated models with price correlations, and estimation procedures in the system is verified with monthly data through various applications of the models to practically important analyses on prices of Japanese GBs and CBs, the USA GBs and CBs, and European GBs (EUGBs) where GBs of Germany, France, Italy, Spain, and Greece. Fact, both yield curves and default curves over a future time horizon.  The system enables us to get practically and timely predictive information for making decisions in investment, formation of effective bond portfolio, asset and liability management (ALM), and risk management of yield curve and default curve in banks, trust funds, pension funds, life insurance firms, among others.