Statistical Portfolio Estimation
Statistical Portfolio Estimation

Author: Masanobu Taniguchi

Publisher: CRC Press

Published: 2017-09-01

Total Pages: 389

ISBN-13: 1466505613

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The composition of portfolios is one of the most fundamental and important methods in financial engineering, used to control the risk of investments. This book provides a comprehensive overview of statistical inference for portfolios and their various applications. A variety of asset processes are introduced, including non-Gaussian stationary processes, nonlinear processes, non-stationary processes, and the book provides a framework for statistical inference using local asymptotic normality (LAN). The approach is generalized for portfolio estimation, so that many important problems can be covered. This book can primarily be used as a reference by researchers from statistics, mathematics, finance, econometrics, and genomics. It can also be used as a textbook by senior undergraduate and graduate students in these fields.

Statistical Portfolio Estimation
Statistical Portfolio Estimation

Author: Masanobu Taniguchi

Publisher: CRC Press

Published: 2017-09-01

Total Pages: 455

ISBN-13: 1351643622

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The composition of portfolios is one of the most fundamental and important methods in financial engineering, used to control the risk of investments. This book provides a comprehensive overview of statistical inference for portfolios and their various applications. A variety of asset processes are introduced, including non-Gaussian stationary processes, nonlinear processes, non-stationary processes, and the book provides a framework for statistical inference using local asymptotic normality (LAN). The approach is generalized for portfolio estimation, so that many important problems can be covered. This book can primarily be used as a reference by researchers from statistics, mathematics, finance, econometrics, and genomics. It can also be used as a textbook by senior undergraduate and graduate students in these fields.

Statistical Estimation
Statistical Estimation

Author: I.A. Ibragimov

Publisher: Springer Science & Business Media

Published: 2013-11-11

Total Pages: 410

ISBN-13: 1489900276

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when certain parameters in the problem tend to limiting values (for example, when the sample size increases indefinitely, the intensity of the noise ap proaches zero, etc.) To address the problem of asymptotically optimal estimators consider the following important case. Let X 1, X 2, ... , X n be independent observations with the joint probability density !(x,O) (with respect to the Lebesgue measure on the real line) which depends on the unknown patameter o e 9 c R1. It is required to derive the best (asymptotically) estimator 0:( X b ... , X n) of the parameter O. The first question which arises in connection with this problem is how to compare different estimators or, equivalently, how to assess their quality, in terms of the mean square deviation from the parameter or perhaps in some other way. The presently accepted approach to this problem, resulting from A. Wald's contributions, is as follows: introduce a nonnegative function w(0l> ( ), Ob Oe 9 (the loss function) and given two estimators Of and O! n 2 2 the estimator for which the expected loss (risk) Eown(Oj, 0), j = 1 or 2, is smallest is called the better with respect to Wn at point 0 (here EoO is the expectation evaluated under the assumption that the true value of the parameter is 0). Obviously, such a method of comparison is not without its defects.

Portfolio Risk Analysis
Portfolio Risk Analysis

Author: Gregory Connor

Publisher: Princeton University Press

Published: 2010-03-15

Total Pages: 400

ISBN-13: 1400835291

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Portfolio risk forecasting has been and continues to be an active research field for both academics and practitioners. Almost all institutional investment management firms use quantitative models for their portfolio forecasting, and researchers have explored models' econometric foundations, relative performance, and implications for capital market behavior and asset pricing equilibrium. Portfolio Risk Analysis provides an insightful and thorough overview of financial risk modeling, with an emphasis on practical applications, empirical reality, and historical perspective. Beginning with mean-variance analysis and the capital asset pricing model, the authors give a comprehensive and detailed account of factor models, which are the key to successful risk analysis in every economic climate. Topics range from the relative merits of fundamental, statistical, and macroeconomic models, to GARCH and other time series models, to the properties of the VIX volatility index. The book covers both mainstream and alternative asset classes, and includes in-depth treatments of model integration and evaluation. Credit and liquidity risk and the uncertainty of extreme events are examined in an intuitive and rigorous way. An extensive literature review accompanies each topic. The authors complement basic modeling techniques with references to applications, empirical studies, and advanced mathematical texts. This book is essential for financial practitioners, researchers, scholars, and students who want to understand the nature of financial markets or work toward improving them.

Elliptically Contoured Models in Statistics
Elliptically Contoured Models in Statistics

Author: Arjun K. Gupta

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 336

ISBN-13: 9401116466

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In multivariate statistical analysis, elliptical distributions have recently provided an alternative to the normal model. Most of the work, however, is spread out in journals throughout the world and is not easily accessible to the investigators. Fang, Kotz, and Ng presented a systematic study of multivariate elliptical distributions, however, they did not discuss the matrix variate case. Recently Fang and Zhang have summarized the results of generalized multivariate analysis which include vector as well as the matrix variate distributions. On the other hand, Fang and Anderson collected research papers on matrix variate elliptical distributions, many of them published for the first time in English. They published very rich material on the topic, but the results are given in paper form which does not provide a unified treatment of the theory. Therefore, it seemed appropriate to collect the most important results on the theory of matrix variate elliptically contoured distributions available in the literature and organize them in a unified manner that can serve as an introduction to the subject. The book will be useful for researchers, teachers, and graduate students in statistics and related fields whose interests involve multivariate statistical analysis. Parts of this book were presented by Arjun K Gupta as a one semester course at Bowling Green State University. Some new results have also been included which generalize the results in Fang and Zhang. Knowledge of matrix algebra and statistics at the level of Anderson is assumed. However, Chapter 1 summarizes some results of matrix algebra.

Quantitative Portfolio Management
Quantitative Portfolio Management

Author: Michael Isichenko

Publisher: John Wiley & Sons

Published: 2021-09-10

Total Pages: 306

ISBN-13: 1119821215

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Discover foundational and advanced techniques in quantitative equity trading from a veteran insider In Quantitative Portfolio Management: The Art and Science of Statistical Arbitrage, distinguished physicist-turned-quant Dr. Michael Isichenko delivers a systematic review of the quantitative trading of equities, or statistical arbitrage. The book teaches you how to source financial data, learn patterns of asset returns from historical data, generate and combine multiple forecasts, manage risk, build a stock portfolio optimized for risk and trading costs, and execute trades. In this important book, you’ll discover: Machine learning methods of forecasting stock returns in efficient financial markets How to combine multiple forecasts into a single model by using secondary machine learning, dimensionality reduction, and other methods Ways of avoiding the pitfalls of overfitting and the curse of dimensionality, including topics of active research such as “benign overfitting” in machine learning The theoretical and practical aspects of portfolio construction, including multi-factor risk models, multi-period trading costs, and optimal leverage Perfect for investment professionals, like quantitative traders and portfolio managers, Quantitative Portfolio Management will also earn a place in the libraries of data scientists and students in a variety of statistical and quantitative disciplines. It is an indispensable guide for anyone who hopes to improve their understanding of how to apply data science, machine learning, and optimization to the stock market.

The Role of Statistics in Business and Industry
The Role of Statistics in Business and Industry

Author: Gerald J. Hahn

Publisher: John Wiley & Sons

Published: 2011-09-20

Total Pages: 302

ISBN-13: 1118211464

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An insightful guide to the use of statistics for solving key problems in modern-day business and industry This book has been awarded the Technometrics Ziegel Prize for the best book reviewed by the journal in 2010. Technometrics is a journal of statistics for the physical, chemical and engineering sciences, published jointly by the American Society for Quality and the American Statistical Association. Criteria for the award include that the book brings together in one volume a body of material previously only available in scattered research articles and having the potential to significantly improve practice in engineering and science. Highlighting the relevance of statistical methods in everyday applications, The Role of Statistics in Business and Industry bridges the gap between the tools of statistics and their use in today's business world. This one-of-a-kind resource encourages the proactive use of statistics in three well-organized and succinct parts: Setting the Stage provides an introduction to statistics, with a general overview of its uses in business and industry Manufactured Product Applications explains how statistical techniques assist in designing, building, improving, and ensuring the reliability of a wide variety of manufactured products such as appliances, plastic materials, aircraft engines, and locomotives Other Applications describe the role of statistics in pharmaceuticals, finance, and business services, as well as more specialized areas including the food, semiconductor, and communications industries This book is truly unique in that it first describes case studies and key business problems, and then shows how statistics is used to address them, while most literature on the topic does the reverse. This approach provides a comprehensive understanding of common issues and the most effective methods for their treatment. Each chapter concludes with general questions that allow the reader to test their understanding of the presented statistical concepts as well as technical questions that raise more complex issues. An extensive FTP site provides additional material, including solutions to some of the applications. With its accessible style and real-world examples, The Role of Statistics in Business and Industry is a valuable supplement for courses on applied statistics and statistical consulting at the upper-undergraduate and graduate levels. It is also an ideal resource for early-career statisticians and practitioners who would like to learn the value of applying statistics to their everyday work.

New Developments in Statistical Information Theory Based on Entropy and Divergence Measures
New Developments in Statistical Information Theory Based on Entropy and Divergence Measures

Author: Leandro Pardo

Publisher: MDPI

Published: 2019-05-20

Total Pages: 344

ISBN-13: 3038979368

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This book presents new and original research in Statistical Information Theory, based on minimum divergence estimators and test statistics, from a theoretical and applied point of view, for different statistical problems with special emphasis on efficiency and robustness. Divergence statistics, based on maximum likelihood estimators, as well as Wald’s statistics, likelihood ratio statistics and Rao’s score statistics, share several optimum asymptotic properties, but are highly non-robust in cases of model misspecification under the presence of outlying observations. It is well-known that a small deviation from the underlying assumptions on the model can have drastic effect on the performance of these classical tests. Specifically, this book presents a robust version of the classical Wald statistical test, for testing simple and composite null hypotheses for general parametric models, based on minimum divergence estimators.

Introduction to Statistical Methods for Financial Models
Introduction to Statistical Methods for Financial Models

Author: Thomas A Severini

Publisher: CRC Press

Published: 2017-07-06

Total Pages: 370

ISBN-13: 1351981919

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This book provides an introduction to the use of statistical concepts and methods to model and analyze financial data. The ten chapters of the book fall naturally into three sections. Chapters 1 to 3 cover some basic concepts of finance, focusing on the properties of returns on an asset. Chapters 4 through 6 cover aspects of portfolio theory and the methods of estimation needed to implement that theory. The remainder of the book, Chapters 7 through 10, discusses several models for financial data, along with the implications of those models for portfolio theory and for understanding the properties of return data. The audience for the book is students majoring in Statistics and Economics as well as in quantitative fields such as Mathematics and Engineering. Readers are assumed to have some background in statistical methods along with courses in multivariate calculus and linear algebra.

Institutional Investment Management
Institutional Investment Management

Author: Frank J. Fabozzi

Publisher: John Wiley & Sons

Published: 2009-08-25

Total Pages: 884

ISBN-13: 0470538902

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The most comprehensive coverage of institutional investment management issues This comprehensive handbook of investment management theories, concepts, and applications opens with an overview of the financial markets and investments, as well as a look at institutional investors and their objectives. From here, respected investment expert Frank Fabozzi moves on to cover a wide array of issues in this evolving field. From valuation and fixed income analysis to alternative investments and asset allocation, Fabozzi provides the best in cutting-edge information for new and seasoned practitioners, as well as professors and students of finance. Contains practical, real-world applications of investment management theories and concepts Uses unique illustrations of factor models to highlight how to build a portfolio Includes insights on execution and measurement of transaction costs Covers fixed income (particularly structured products) and derivatives Institutional Investment Management is an essential read for anyone who needs to hone their skills in this discipline.