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Author: R.A. Jarrow Publisher: Elsevier ISBN: 9780444890849 Category : Business & Economics Languages : en Pages : 1204
Book Description
Hardbound. The Handbook of Finance is a primary reference work for financial economics and financial modeling students, faculty and practitioners. The expository treatments are suitable for masters and PhD students, with discussions leading from first principles to current research, with reference to important research works in the area. The Handbook is intended to be a synopsis of the current state of various aspects of the theory of financial economics and its application to important financial problems. The coverage consists of thirty-three chapters written by leading experts in the field. The contributions are in two broad categories: capital markets and corporate finance.
Author: R.A. Jarrow Publisher: Elsevier ISBN: 9780444890849 Category : Business & Economics Languages : en Pages : 1204
Book Description
Hardbound. The Handbook of Finance is a primary reference work for financial economics and financial modeling students, faculty and practitioners. The expository treatments are suitable for masters and PhD students, with discussions leading from first principles to current research, with reference to important research works in the area. The Handbook is intended to be a synopsis of the current state of various aspects of the theory of financial economics and its application to important financial problems. The coverage consists of thirty-three chapters written by leading experts in the field. The contributions are in two broad categories: capital markets and corporate finance.
Author: Jushan Bai Publisher: Now Publishers Inc ISBN: 1601981449 Category : Business & Economics Languages : en Pages : 90
Book Description
Large Dimensional Factor Analysis provides a survey of the main theoretical results for large dimensional factor models, emphasizing results that have implications for empirical work. The authors focus on the development of the static factor models and on the use of estimated factors in subsequent estimation and inference. Large Dimensional Factor Analysis discusses how to determine the number of factors, how to conduct inference when estimated factors are used in regressions, how to assess the adequacy pf observed variables as proxies for latent factors, how to exploit the estimated factors to test unit root tests and common trends, and how to estimate panel cointegration models.
Author: John Knight Publisher: Elsevier ISBN: 0080455328 Category : Business & Economics Languages : en Pages : 298
Book Description
The determination of the values of stocks, bonds, options, futures, and derivatives is done by the scientific process of asset pricing, which has developed dramatically in the last few years due to advances in financial theory and econometrics. This book covers the science of asset pricing by concentrating on the most widely used modelling technique called: Linear Factor Modelling.Linear Factor Models covers an important area for Quantitative Analysts/Investment Managers who are developing Quantitative Investment Strategies. Linear factor models (LFM) are part of modern investment processes that include asset valuation, portfolio theory and applications, linear factor models and applications, dynamic asset allocation strategies, portfolio performance measurement, risk management, international perspectives, and the use of derivatives. The book develops the building blocks for one of the most important theories of asset pricing - Linear Factor Modelling. Within this framework, we can include other asset pricing theories such as the Capital Asset Pricing Model (CAPM), arbitrage pricing theory and various pricing formulae for derivatives and option prices. As a bare minimum, the reader of this book must have a working knowledge of basic calculus, simple optimisation and elementary statistics. In particular, the reader must be comfortable with the algebraic manipulation of means, variances (and covariances) of linear combination(s) of random variables. Some topics may require a greater mathematical sophistication.* Covers the latest methods in this area.* Combines actual quantitative finance experience with analytical research rigour* Written by both quantitative analysts and academics who work in this area
Author: Andrew Ang Publisher: Oxford University Press ISBN: 0199959331 Category : Business & Economics Languages : en Pages : 717
Book Description
In Asset Management: A Systematic Approach to Factor Investing, Professor Andrew Ang presents a comprehensive, new approach to the age-old problem of where to put your money. Years of experience as a finance professor and a consultant have led him to see that what matters aren't asset class labels, but instead the bundles of overlapping risks they represent. Factor risks must be the focus of our attention if we are to weather market turmoil and receive the rewards that come with doing so. Clearly written yet full of the latest research and data, Asset Management is indispensable reading for trustees, professional money managers, smart private investors, and business students who want to understand the economics behind factor risk premiums, to harvest them efficiently in their portfolios, and to embark on the search for true alpha.
Author: M. Hashem Pesaran Publisher: Oxford University Press ISBN: 0191058475 Category : Business & Economics Languages : en Pages : 1443
Book Description
This book is concerned with recent developments in time series and panel data techniques for the analysis of macroeconomic and financial data. It provides a rigorous, nevertheless user-friendly, account of the time series techniques dealing with univariate and multivariate time series models, as well as panel data models. It is distinct from other time series texts in the sense that it also covers panel data models and attempts at a more coherent integration of time series, multivariate analysis, and panel data models. It builds on the author's extensive research in the areas of time series and panel data analysis and covers a wide variety of topics in one volume. Different parts of the book can be used as teaching material for a variety of courses in econometrics. It can also be used as reference manual. It begins with an overview of basic econometric and statistical techniques, and provides an account of stochastic processes, univariate and multivariate time series, tests for unit roots, cointegration, impulse response analysis, autoregressive conditional heteroskedasticity models, simultaneous equation models, vector autoregressions, causality, forecasting, multivariate volatility models, panel data models, aggregation and global vector autoregressive models (GVAR). The techniques are illustrated using Microfit 5 (Pesaran and Pesaran, 2009, OUP) with applications to real output, inflation, interest rates, exchange rates, and stock prices.
Author: Ali N. Akansu Publisher: John Wiley & Sons ISBN: 1118745647 Category : Technology & Engineering Languages : en Pages : 312
Book Description
The modern financial industry has been required to deal with large and diverse portfolios in a variety of asset classes often with limited market data available. Financial Signal Processing and Machine Learning unifies a number of recent advances made in signal processing and machine learning for the design and management of investment portfolios and financial engineering. This book bridges the gap between these disciplines, offering the latest information on key topics including characterizing statistical dependence and correlation in high dimensions, constructing effective and robust risk measures, and their use in portfolio optimization and rebalancing. The book focuses on signal processing approaches to model return, momentum, and mean reversion, addressing theoretical and implementation aspects. It highlights the connections between portfolio theory, sparse learning and compressed sensing, sparse eigen-portfolios, robust optimization, non-Gaussian data-driven risk measures, graphical models, causal analysis through temporal-causal modeling, and large-scale copula-based approaches. Key features: Highlights signal processing and machine learning as key approaches to quantitative finance. Offers advanced mathematical tools for high-dimensional portfolio construction, monitoring, and post-trade analysis problems. Presents portfolio theory, sparse learning and compressed sensing, sparsity methods for investment portfolios. including eigen-portfolios, model return, momentum, mean reversion and non-Gaussian data-driven risk measures with real-world applications of these techniques. Includes contributions from leading researchers and practitioners in both the signal and information processing communities, and the quantitative finance community.
Author: Gregory Connor Publisher: Princeton University Press ISBN: 1400835291 Category : Business & Economics Languages : en Pages : 400
Book Description
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.
Author: Gordon J. Alexander Publisher: Pearson Educación ISBN: 9789702603757 Category : Business & Economics Languages : en Pages : 824
Book Description
This introduction provides a clear framework for understanding and analyzing securities, and covers the major institutional features and theories of investing. While the book presents a thorough discussion of investments, the authors keep the material practical, relevant, and easy to understand. The latest developments in investments are brought to life through the use of tables, graphs, and illustrations that incorporate current market information and academic research. An international content deals directly with international securities and securities markets throughout the book--along with currency management and interest rate parity. Up-to-date "Money Matters" articles reflect the latest real-world developments and are provided throughout each chapter to give readers a sense of how practitioners deal with various investment issues and use techniques. Other coverage includes an array of investment tools--presented through discussions on stocks, bonds, and other securities such as options and futures. A guide to reviewing, forecasting, and monitoring--for individuals preparing to make investments or take the CFA exam.
Author: Jau-Lian Jeng Publisher: Springer ISBN: 3319741926 Category : Business & Economics Languages : en Pages : 277
Book Description
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.
Author: R.A. Jarrow
Author: R.A. Jarrow
Author: Jörg Breitung
Author: Jushan Bai
Author: John Knight
Author: Andrew Ang
Author: M. Hashem Pesaran
Author: Ali N. Akansu
Author: Gregory Connor
Author: Gordon J. Alexander
Author: Jau-Lian Jeng