Download or read book Statistical Models of Asset Returns written by Andrew W. Lo and published by Edward Elgar Publishing. This book was released on 2007 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This major collection presents a careful selection of the most important published articles in the field of financial econometrics. Starting with a review of the philosophical background, the collection covers such topics as the random walk hypothesis, long-memory processes, asset pricing, arbitrage pricing theory, variance bounds tests, term structure models, market microstructure, Bayesian methods and other statistical tools. Andrew Lo - one of the world's leading financial economists - has written an authoritative introduction, which offers a comprehensive overview of the subject and complements his selection.
Download or read book Statistical Models and Methods for Financial Markets written by Tze Leung Lai and published by Springer Science & Business Media. This book was released on 2008-09-08 with total page 363 pages. Available in PDF, EPUB and Kindle. Book excerpt: The idea of writing this bookarosein 2000when the ?rst author wasassigned to teach the required course STATS 240 (Statistical Methods in Finance) in the new M. S. program in ?nancial mathematics at Stanford, which is an interdisciplinary program that aims to provide a master’s-level education in applied mathematics, statistics, computing, ?nance, and economics. Students in the programhad di?erent backgroundsin statistics. Some had only taken a basic course in statistical inference, while others had taken a broad spectrum of M. S. - and Ph. D. -level statistics courses. On the other hand, all of them had already taken required core courses in investment theory and derivative pricing, and STATS 240 was supposed to link the theory and pricing formulas to real-world data and pricing or investment strategies. Besides students in theprogram,thecoursealso attractedmanystudentsfromother departments in the university, further increasing the heterogeneity of students, as many of them had a strong background in mathematical and statistical modeling from the mathematical, physical, and engineering sciences but no previous experience in ?nance. To address the diversity in background but common strong interest in the subject and in a potential career as a “quant” in the ?nancialindustry,thecoursematerialwascarefullychosennotonlytopresent basic statistical methods of importance to quantitative ?nance but also to summarize domain knowledge in ?nance and show how it can be combined with statistical modeling in ?nancial analysis and decision making. The course material evolved over the years, especially after the second author helped as the head TA during the years 2004 and 2005.
Download or read book Statistical Models and Methods for Financial Markets written by Tze Leung Lai and published by Springer Science & Business Media. This book was released on 2008-07-25 with total page 363 pages. Available in PDF, EPUB and Kindle. Book excerpt: The idea of writing this bookarosein 2000when the ?rst author wasassigned to teach the required course STATS 240 (Statistical Methods in Finance) in the new M. S. program in ?nancial mathematics at Stanford, which is an interdisciplinary program that aims to provide a master’s-level education in applied mathematics, statistics, computing, ?nance, and economics. Students in the programhad di?erent backgroundsin statistics. Some had only taken a basic course in statistical inference, while others had taken a broad spectrum of M. S. - and Ph. D. -level statistics courses. On the other hand, all of them had already taken required core courses in investment theory and derivative pricing, and STATS 240 was supposed to link the theory and pricing formulas to real-world data and pricing or investment strategies. Besides students in theprogram,thecoursealso attractedmanystudentsfromother departments in the university, further increasing the heterogeneity of students, as many of them had a strong background in mathematical and statistical modeling from the mathematical, physical, and engineering sciences but no previous experience in ?nance. To address the diversity in background but common strong interest in the subject and in a potential career as a “quant” in the ?nancialindustry,thecoursematerialwascarefullychosennotonlytopresent basic statistical methods of importance to quantitative ?nance but also to summarize domain knowledge in ?nance and show how it can be combined with statistical modeling in ?nancial analysis and decision making. The course material evolved over the years, especially after the second author helped as the head TA during the years 2004 and 2005.
Download or read book Fat Tailed and Skewed Asset Return Distributions written by Svetlozar T. Rachev and published by John Wiley & Sons. This book was released on 2005-09-15 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: While mainstream financial theories and applications assume that asset returns are normally distributed, overwhelming empirical evidence shows otherwise. Yet many professionals don’t appreciate the highly statistical models that take this empirical evidence into consideration. Fat-Tailed and Skewed Asset Return Distributions examines this dilemma and offers readers a less technical look at how portfolio selection, risk management, and option pricing modeling should and can be undertaken when the assumption of a non-normal distribution for asset returns is violated. Topics covered in this comprehensive book include an extensive discussion of probability distributions, estimating probability distributions, portfolio selection, alternative risk measures, and much more. Fat-Tailed and Skewed Asset Return Distributions provides a bridge between the highly technical theory of statistical distributional analysis, stochastic processes, and econometrics of financial returns and real-world risk management and investments.
Download or read book The International Library of Financial Econometrics Statistical models of asset returns written by Andrew Wen-Chuan Lo and published by . This book was released on 2007 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Empirical Asset Pricing written by Wayne Ferson and published by MIT Press. This book was released on 2019-03-12 with total page 497 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to the theory and methods of empirical asset pricing, integrating classical foundations with recent developments. This book offers a comprehensive advanced introduction to asset pricing, the study of models for the prices and returns of various securities. The focus is empirical, emphasizing how the models relate to the data. The book offers a uniquely integrated treatment, combining classical foundations with more recent developments in the literature and relating some of the material to applications in investment management. It covers the theory of empirical asset pricing, the main empirical methods, and a range of applied topics. The book introduces the theory of empirical asset pricing through three main paradigms: mean variance analysis, stochastic discount factors, and beta pricing models. It describes empirical methods, beginning with the generalized method of moments (GMM) and viewing other methods as special cases of GMM; offers a comprehensive review of fund performance evaluation; and presents selected applied topics, including a substantial chapter on predictability in asset markets that covers predicting the level of returns, volatility and higher moments, and predicting cross-sectional differences in returns. Other chapters cover production-based asset pricing, long-run risk models, the Campbell-Shiller approximation, the debate on covariance versus characteristics, and the relation of volatility to the cross-section of stock returns. An extensive reference section captures the current state of the field. The book is intended for use by graduate students in finance and economics; it can also serve as a reference for professionals.
Download or read book Introduction to Statistical Methods for Financial Models written by Thomas A Severini and published by CRC Press. This book was released on 2017-07-06 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book The Econometric Analysis of Time Series written by Andrew C. Harvey and published by . This book was released on 1990 with total page 387 pages. Available in PDF, EPUB and Kindle. Book excerpt: Coverage has been extended to include recent topics. The book again presents a unified treatment of economic theory, with the method of maximum likelihood playing a key role in both estimation and testing. Exercises are included and the book is suitable as a general text for final-year undergraduate and postgraduate students.
Download or read book Empirical Asset Pricing Models written by Jau-Lian Jeng and published by Springer. This book was released on 2018-03-19 with total page 277 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book analyzes the verification of empirical asset pricing models when returns of securities are projected onto a set of presumed (or observed) factors. Particular emphasis is placed on the verification of essential factors and features for asset returns through model search approaches, in which non-diversifiability and statistical inferences are considered. The discussion reemphasizes the necessity of maintaining a dichotomy between the nondiversifiable pricing kernels and the individual components of stock returns when empirical asset pricing models are of interest. In particular, the model search approach (with this dichotomy emphasized) for empirical model selection of asset pricing is applied to discover the pricing kernels of asset returns.
Download or read book Statistical Properties of Asset Returns written by Jüri Uustalu and published by . This book was released on 1994 with total page 106 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Empirical Asset Pricing written by Turan G. Bali and published by John Wiley & Sons. This book was released on 2016-02-26 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt: “Bali, Engle, and Murray have produced a highly accessible introduction to the techniques and evidence of modern empirical asset pricing. This book should be read and absorbed by every serious student of the field, academic and professional.” Eugene Fama, Robert R. McCormick Distinguished Service Professor of Finance, University of Chicago and 2013 Nobel Laureate in Economic Sciences “The empirical analysis of the cross-section of stock returns is a monumental achievement of half a century of finance research. Both the established facts and the methods used to discover them have subtle complexities that can mislead casual observers and novice researchers. Bali, Engle, and Murray’s clear and careful guide to these issues provides a firm foundation for future discoveries.” John Campbell, Morton L. and Carole S. Olshan Professor of Economics, Harvard University “Bali, Engle, and Murray provide clear and accessible descriptions of many of the most important empirical techniques and results in asset pricing.” Kenneth R. French, Roth Family Distinguished Professor of Finance, Tuck School of Business, Dartmouth College “This exciting new book presents a thorough review of what we know about the cross-section of stock returns. Given its comprehensive nature, systematic approach, and easy-to-understand language, the book is a valuable resource for any introductory PhD class in empirical asset pricing.” Lubos Pastor, Charles P. McQuaid Professor of Finance, University of Chicago Empirical Asset Pricing: The Cross Section of Stock Returns is a comprehensive overview of the most important findings of empirical asset pricing research. The book begins with thorough expositions of the most prevalent econometric techniques with in-depth discussions of the implementation and interpretation of results illustrated through detailed examples. The second half of the book applies these techniques to demonstrate the most salient patterns observed in stock returns. The phenomena documented form the basis for a range of investment strategies as well as the foundations of contemporary empirical asset pricing research. Empirical Asset Pricing: The Cross Section of Stock Returns also includes: Discussions on the driving forces behind the patterns observed in the stock market An extensive set of results that serve as a reference for practitioners and academics alike Numerous references to both contemporary and foundational research articles Empirical Asset Pricing: The Cross Section of Stock Returns is an ideal textbook for graduate-level courses in asset pricing and portfolio management. The book is also an indispensable reference for researchers and practitioners in finance and economics. Turan G. Bali, PhD, is the Robert Parker Chair Professor of Finance in the McDonough School of Business at Georgetown University. The recipient of the 2014 Jack Treynor prize, he is the coauthor of Mathematical Methods for Finance: Tools for Asset and Risk Management, also published by Wiley. Robert F. Engle, PhD, is the Michael Armellino Professor of Finance in the Stern School of Business at New York University. He is the 2003 Nobel Laureate in Economic Sciences, Director of the New York University Stern Volatility Institute, and co-founding President of the Society for Financial Econometrics. Scott Murray, PhD, is an Assistant Professor in the Department of Finance in the J. Mack Robinson College of Business at Georgia State University. He is the recipient of the 2014 Jack Treynor prize.
Download or read book Portfolio Diversification written by Francois-Serge Lhabitant and published by Elsevier. This book was released on 2017-09-26 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: Portfolio Diversification provides an update on the practice of combining several risky investments in a portfolio with the goal of reducing the portfolio's overall risk. In this book, readers will find a comprehensive introduction and analysis of various dimensions of portfolio diversification (assets, maturities, industries, countries, etc.), along with time diversification strategies (long term vs. short term diversification) and diversification using other risk measures than variance. Several tools to quantify and implement optimal diversification are discussed and illustrated. Focuses on portfolio diversification across all its dimensions Includes recent empirical material that was created and developed specifically for this book Provides several tools to quantify and implement optimal diversification
Download or read book Essays on Fitting Factor Models for Asset Returns written by Sangeetha Srinivasan and published by . This book was released on 2018 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: Factor models are used to describe the fundamental drivers of financial asset returns. There are 3 types: time-series factor, statistical factor and fundamental factor models. While factor models have existed for almost 60 years, industry-wide adoption with factor-based investing has surged in the last decade. This dissertation is centered on factorAnalytics, an open source R package co-developed with other UW students and faculty members, that demystifies the industry black-box models, making model fitting tools readily available for any interested academic or practitioner. Chapter 1 compares the characteristics of the three types of models in terms of model specification, estimation, interpretation and various in-sample and out-of-sample performance metrics using S&P 500 stock returns. Like Connor (1995), we find that the fundamental factor model outperforms the time-series and statistical factor models since it makes use of additional information on asset-specific characteristics. Moreover, we find that adding statistical factor(s) extracted from the residuals of time-series or fundamental factor models, or, fitting fundamental factors to the residuals of a time-series factor model, to create hybrid models, further improves performance. Investment management firms need to understand peer positioning for a variety of reasons, including risk management. Factor models provide a framework to estimate peer exposures, especially useful when holdings-based information is lacking. Chapter 2 presents a multi-asset time-series factor model constructed from long-short portfolios of asset class index returns, applied to peer-average returns from the Morningstar U.S. fund allocation categories. We show that factors are better than asset classes for assessing unknown exposures and decomposing risk in multi-asset portfolios. Furthermore, there is an opportunity to create more efficient, better risk-diversified portfolios using factors when making allocation decisions. We use the multi-factor model to construct equal-asset-risk and equal-factor-risk portfolios and compare them to the equal-weighted and minimum-variance portfolios. We also show that a zero-investment equal-factor-risk portfolio sleeve helps bridge the gap between pure risk parity and traditional portfolios, enhancing Sharpe ratio across all risk categories. Chapters 3-5 contain vignettes for each type of factor model that describe and demonstrate model fitting, factor risk (volatility, value-at-risk and expected shortfall) decomposition, and related S3 generic methods.
Download or read book Empirical Asset Pricing written by Wayne Ferson and published by MIT Press. This book was released on 2019-03-26 with total page 497 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to the theory and methods of empirical asset pricing, integrating classical foundations with recent developments. This book offers a comprehensive advanced introduction to asset pricing, the study of models for the prices and returns of various securities. The focus is empirical, emphasizing how the models relate to the data. The book offers a uniquely integrated treatment, combining classical foundations with more recent developments in the literature and relating some of the material to applications in investment management. It covers the theory of empirical asset pricing, the main empirical methods, and a range of applied topics. The book introduces the theory of empirical asset pricing through three main paradigms: mean variance analysis, stochastic discount factors, and beta pricing models. It describes empirical methods, beginning with the generalized method of moments (GMM) and viewing other methods as special cases of GMM; offers a comprehensive review of fund performance evaluation; and presents selected applied topics, including a substantial chapter on predictability in asset markets that covers predicting the level of returns, volatility and higher moments, and predicting cross-sectional differences in returns. Other chapters cover production-based asset pricing, long-run risk models, the Campbell-Shiller approximation, the debate on covariance versus characteristics, and the relation of volatility to the cross-section of stock returns. An extensive reference section captures the current state of the field. The book is intended for use by graduate students in finance and economics; it can also serve as a reference for professionals.
Download or read book On the Central Limit Theorem for the Sum of a Random Number of Independent Random Variables written by J. R. Blum and published by . This book was released on 1963 with total page 10 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Statistical Models written by David A. Freedman and published by Cambridge University Press. This book was released on 2009-04-27 with total page 459 pages. Available in PDF, EPUB and Kindle. Book excerpt: This lively and engaging book explains the things you have to know in order to read empirical papers in the social and health sciences, as well as the techniques you need to build statistical models of your own. The discussion in the book is organized around published studies, as are many of the exercises. Relevant journal articles are reprinted at the back of the book. Freedman makes a thorough appraisal of the statistical methods in these papers and in a variety of other examples. He illustrates the principles of modelling, and the pitfalls. The discussion shows you how to think about the critical issues - including the connection (or lack of it) between the statistical models and the real phenomena. The book is written for advanced undergraduates and beginning graduate students in statistics, as well as students and professionals in the social and health sciences.
Download or read book Statistical Portfolio Estimation written by Masanobu Taniguchi and published by CRC Press. This book was released on 2017-09-01 with total page 389 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
