Empirical Asset Pricing PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Empirical Asset Pricing PDF full book. Access full book title Empirical Asset Pricing by Wayne Ferson. Download full books in PDF and EPUB format.
Author: Wayne Ferson
Publisher: MIT Press
ISBN: 0262039370
Category : Business & Economics
Languages : en
Pages : 497
Get Book Here
Book Description
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.
Author: Wayne Ferson
Publisher: MIT Press
ISBN: 0262039370
Category : Business & Economics
Languages : en
Pages : 497
Get Book Here
Book Description
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.
Author: Ullrich Heilemann
Publisher: Duncker & Humblot
ISBN: 342852425X
Category : Business & Economics
Languages : en
Pages : 168
Get Book Here
Book Description
The analysis of cyclical macroeconomic phenomena is an important field of econometric research. In the recent past, research interests have de-emphasized quantitative forecasting exercises and have addressed the qualitative diagnosis of the relative stance of the economy regarding »upswing«, »recession«, or »boom« periods, i. e. the classification of the state of the economy into a limited number of discrete states. In this context the principal challenge is to reduce the multifaceted and sometimes abundant quantitative information about the business cycle to such qualitative statements in an efficient way. For more than six years this task was the focus of the project »Multivariate determination and analysis of business cycles« within the SFB 475 »Reduction of complexity in multivariate data structures«, funded by the German Research Foundation (DFG). The necessity for complexity reduction is, of course, not unique to business cycle analysis but is studied in many fields and in a number of ways. This broad interest in the reduction of problem dimensionality and in the appropriate combination of data and of theory caused the RWI Essen and the Statistical Department of the University of Dortmund in January 2002 to hold a workshop at the RWI Essen where the findings of this and similar projects were presented and discussed. The present publication collects revised versions of the papers presented at this workshop. Although the workshop took place some five years ago, these papers mark an importent juncture in the development of business cycle research.
Author: Victor Zarnowitz
Publisher: University of Chicago Press
ISBN: 0226978923
Category : Business & Economics
Languages : en
Pages : 613
Get Book Here
Book Description
This volume presents the most complete collection available of the work of Victor Zarnowitz, a leader in the study of business cycles, growth, inflation, and forecasting.. With characteristic insight, Zarnowitz examines theories of the business cycle, including Keynesian and monetary theories and more recent rational expectation and real business cycle theories. He also measures trends and cycles in economic activity; evaluates the performance of leading indicators and their composite measures; surveys forecasting tools and performance of business and academic economists; discusses historical changes in the nature and sources of business cycles; and analyzes how successfully forecasting firms and economists predict such key economic variables as interest rates and inflation.
Author: John Y. Campbell
Publisher:
ISBN:
Category : Stocks
Languages : en
Pages : 66
Get Book Here
Book Description
The cash flows of growth stocks are particularly sensitive to temporary movements in aggregate stock prices (driven by movements in the equity risk premium), while the cash flows of value stocks are particularly sensitive to permanent movements in aggregate stock prices (driven by market-wide shocks to cash flows.) Thus the high betas of growth stocks with the market's discount-rate shocks, and of value stocks with the market's cash-flow shocks, are determined by the cash-flow fundamentals of growth and value companies. Growth stocks are not merely "glamour stocks" whose systematic risks are purely driven by investor sentiment. More generally, accounting measures of firm-level risk have predictive power for firms' betas with market-wide cash flows, and this predictive power arises from the behavior of firms' cash flows. The systematic risks of stocks with similar accounting characteristics are primarily driven by the systematic risks of their fundamentals.
Author: Svetlozar T. Rachev
Publisher: John Wiley & Sons
ISBN: 0470937262
Category : Business & Economics
Languages : en
Pages : 316
Get Book Here
Book Description
An in-depth guide to understanding probability distributions and financial modeling for the purposes of investment management In Financial Models with Lévy Processes and Volatility Clustering, the expert author team provides a framework to model the behavior of stock returns in both a univariate and a multivariate setting, providing you with practical applications to option pricing and portfolio management. They also explain the reasons for working with non-normal distribution in financial modeling and the best methodologies for employing it. The book's framework includes the basics of probability distributions and explains the alpha-stable distribution and the tempered stable distribution. The authors also explore discrete time option pricing models, beginning with the classical normal model with volatility clustering to more recent models that consider both volatility clustering and heavy tails. Reviews the basics of probability distributions Analyzes a continuous time option pricing model (the so-called exponential Lévy model) Defines a discrete time model with volatility clustering and how to price options using Monte Carlo methods Studies two multivariate settings that are suitable to explain joint extreme events Financial Models with Lévy Processes and Volatility Clustering is a thorough guide to classical probability distribution methods and brand new methodologies for financial modeling.
Author: Carl Chiarella
Publisher: Routledge
ISBN: 1135984506
Category : Biography & Autobiography
Languages : en
Pages : 513
Get Book Here
Book Description
This important new book from a group of Keynesian, but nonetheless technically-oriented economists explores one of the dominant paradigms in financial economics: the ‘intertemporal general equilibrium approach’.
Author: Francis X. Diebold
Publisher: Oxford University Press
ISBN: 0199338329
Category : Business & Economics
Languages : en
Pages : 285
Get Book Here
Book Description
Connections among different assets, asset classes, portfolios, and the stocks of individual institutions are critical in examining financial markets. Interest in financial markets implies interest in underlying macroeconomic fundamentals. In Financial and Macroeconomic Connectedness, Frank Diebold and Kamil Yilmaz propose a simple framework for defining, measuring, and monitoring connectedness, which is central to finance and macroeconomics. These measures of connectedness are theoretically rigorous yet empirically relevant. The approach to connectedness proposed by the authors is intimately related to the familiar econometric notion of variance decomposition. The full set of variance decompositions from vector auto-regressions produces the core of the 'connectedness table.' The connectedness table makes clear how one can begin with the most disaggregated pair-wise directional connectedness measures and aggregate them in various ways to obtain total connectedness measures. The authors also show that variance decompositions define weighted, directed networks, so that these proposed connectedness measures are intimately related to key measures of connectedness used in the network literature. After describing their methods in the first part of the book, the authors proceed to characterize daily return and volatility connectedness across major asset (stock, bond, foreign exchange and commodity) markets as well as the financial institutions within the U.S. and across countries since late 1990s. These specific measures of volatility connectedness show that stock markets played a critical role in spreading the volatility shocks from the U.S. to other countries. Furthermore, while the return connectedness across stock markets increased gradually over time the volatility connectedness measures were subject to significant jumps during major crisis events. This book examines not only financial connectedness, but also real fundamental connectedness. In particular, the authors show that global business cycle connectedness is economically significant and time-varying, that the U.S. has disproportionately high connectedness to others, and that pairwise country connectedness is inversely related to bilateral trade surpluses.
Author: Shifeng Liu
Publisher: Springer Nature
ISBN: 9813343591
Category : Business & Economics
Languages : en
Pages : 1056
Get Book Here
Book Description
This book contains the proceedings of the 10th International Conference on Logistics, Informatics and Service Sciences (LISS 2020), which is co-organized by Beijing Jiaotong University, Budapest University of Technology and Economics, in July 25–28 2020. This book focuses on the “AI and data-driven technical and management innovation in logistics, informatics and services” and aims to provide new research methods, theories and applications from various areas of management and engineering. In detail the included scientific papers analyse and describe communication processes in the fields of logistics, informatics, service sciences and other related areas. The variety of papers delivers added value for both scholars and practitioners. Information and communication technologies have been providing an effective network infrastructure and development platform for logistics and service operations.
Author: CFA Institute
Publisher: John Wiley & Sons
ISBN: 1119787963
Category : Business & Economics
Languages : en
Pages : 647
Get Book Here
Book Description
Discover the latest essential resource on asset allocation for students and investment professionals. Part of the CFA Institute’s three-volume Portfolio Management in Practice series, Asset Allocation offers a deep, comprehensive treatment of the asset allocation process and the underlying theories and markets that support it. As the second volume in the series, Asset Allocation meets the needs of both graduate-level students focused on finance and industry professionals looking to become more dynamic investors. Filled with the insights and industry knowledge of the CFA Institute’s subject matter experts, Asset Allocation effectively blends theory and practice while helping the reader expand their skillsets in key areas of interest. This volume provides complete coverage on the following topics: Setting capital market expectations to support the asset allocation process Principles and processes in the asset allocation process, including handling ESG-integration and client-specific constraints Allocation beyond the traditional asset classes to include allocation to alternative investments The role of exchange-traded funds can play in implementing investment strategies An integrative case study in portfolio management involving a university endowment To further enhance your understanding of tools and techniques explored in Asset Allocation, don’t forget to pick up the Portfolio Management in Practice, Volume 2: Asset Allocation Workbook. The workbook is the perfect companion resource containing learning outcomes, summary overview sections, and challenging practice questions that align chapter-by-chapter with the main text.
Author: Stefan Nagel
Publisher: Princeton University Press
ISBN: 0691218706
Category : Business & Economics
Languages : en
Pages : 156
Get Book Here
Book Description
A groundbreaking, authoritative introduction to how machine learning can be applied to asset pricing Investors in financial markets are faced with an abundance of potentially value-relevant information from a wide variety of different sources. In such data-rich, high-dimensional environments, techniques from the rapidly advancing field of machine learning (ML) are well-suited for solving prediction problems. Accordingly, ML methods are quickly becoming part of the toolkit in asset pricing research and quantitative investing. In this book, Stefan Nagel examines the promises and challenges of ML applications in asset pricing. Asset pricing problems are substantially different from the settings for which ML tools were developed originally. To realize the potential of ML methods, they must be adapted for the specific conditions in asset pricing applications. Economic considerations, such as portfolio optimization, absence of near arbitrage, and investor learning can guide the selection and modification of ML tools. Beginning with a brief survey of basic supervised ML methods, Nagel then discusses the application of these techniques in empirical research in asset pricing and shows how they promise to advance the theoretical modeling of financial markets. Machine Learning in Asset Pricing presents the exciting possibilities of using cutting-edge methods in research on financial asset valuation.
