Financial Econometrics From Basics to Advanced Modeling Techniques

ISBN-10: 0471784508

ISBN-13: 9780471784500

Edition: 2007

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Description:

Financial econometrics combines mathematical and statistical theory and techniques to understand and solve problems in financial economics. Modeling and forecasting financial time series, such as prices, returns, interest rates, financial ratios, and defaults, are important parts of this field. In Financial Econometrics, you2ll be introduced to this growing discipline and the concepts associated with it-from background material on probability theory and statistics to information regarding the properties of specific models and their estimation procedures. With this book as your guide, you2ll become familiar with: Autoregressive conditional heteroskedasticity (ARCH) and GARCH modeling Principal components analysis (PCA) and factor analysis Stable processes and ARMA and GARCH models with fat-tailed errors Robust estimation methods Vector autoregressive and cointegrated processes, including advanced estimation methods for cointegrated systems And much more The experienced author team of Svetlozar Rachev, Stefan Mittnik, Frank Fabozzi, Sergio Focardi, and Teo Jasic not only presents you with an abundant amount of information on financial econometrics, but they also walk you through a wide array of examples to solidify your understanding of the issues discussed. Filled with in-depth insights and expert advice, Financial Econometrics provides comprehensive coverage of this discipline and clear explanations of how the models associated with it fit into today2s investment management process.
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Book details

List price: $125.00
Copyright year: 2007
Publisher: John Wiley & Sons, Incorporated
Publication date: 12/15/2006
Binding: Hardcover
Pages: 576
Size: 6.00" wide x 9.00" long x 2.00" tall
Weight: 1.628

Douglas J. Lucas is Executive Director and Head of CDO Research at UBS. He is also Chairman of The Bond Market Association's CDO Research Committee and ranked top three in CDO research in the Institutional Investor's fixed income analyst survey. Lucas has been involved in the CDO market for nearly two decades, having developed Moody's rating methodology for CDOs in 1989.LAURIE S. GOODMAN, PhD, is Managing Director and co-Head of Global Fixed Income Research at UBS. She manages U.S. Securitized Products and Treasury/Agency/Derivatives Research. Goodman has worked on Wall Street for over twenty years and is well regarded by the investor community, having won more #1 slots on the Institutional Investor All-American Fixed Income Team than any other analyst.FRANK J. FABOZZI, PhD, CFA, CPA, is an Adjunct Professor of Finance and Becton Fellow at Yale University's School of Management and a Fellow of the International Center for Finance. Fabozzi is the Editor of the Journal of Portfolio Management.

FRANK J. FABOZZI, PHD, CFA, CPA, is the Frederick Frank Adjunct Professor of Finance at Yale University's School of Management and a Fellow of the International Center for Finance. Prior to joining the Yale faculty, Fabozzi was a visiting professor of finance in the Sloan School of Management at MIT. Fabozzi is the Editor of the Journal of Portfolio Management.Sergio M. Focardi is a founding partner of the Paris-based consulting firm, The Intertek Group. He consults on, trains on, and implements quantitative financial models. He is also a member of the editorial board of the Journal of Portfolio Management and author of numerous articles and books on financial modeling.Petter N. Kolm, PHD, is a doctoral student in finance at Yale University's School of Management and a financial consultant in New York City. Previously, he worked in the Quantitative Strategies group at Goldman Sachs Asset Management where he developed quantitative investment models and strategies.

Preface
Abbreviations and Acronyms
About the Authors
Financial Econometrics: Scope and Methods
The Data Generating Process
Financial Econometrics at Work
Time Horizon of Models
Applications
Appendix: Investment Management Process
Concepts Explained in this Chapter (in order of presentation)
Review of Probability and Statistics.Concepts of Probability
Principles of Estimation
Bayesian Modeling
Information Structures
Filtration
Concepts Explained in this Chapter (in order of presentation)
Regression Analysis: Theory and Estimation.The Concept of Dependence
Regressions and Linear Models
Estimation of Linear Regressions
Sampling Distributions of Regressions
Determining the Explanatory Power of a Regression
Using Regression Analysis in Finance
Stepwise Regression
Nonnormality and Autocorrelation of the Residuals
Pitfalls of Regressions
Concepts Explained in this Chapter (in order of presentation)
Selected Topics in Regression Analysis.Categorical and Dummy Variables in Regression Models
Constrained Least Squares
The Method of Moments and its Generalizations.Concepts Explained in this Chapter (in order of presentation)
Regression Applications in Finance
Applications to the Investment Management Process
A Test of Strong-Form Pricing Efficiency
Tests of the CAPM
Using the CAPM to Evaluate Manager Performance: The Jensen Measure
Evidence for Multifactor Models
Benchmark Selection: Sharpe Benchmarks.Return-Based Style Analysis for Hedge Funds
Hedge Fund Survival
Bond Portfolio Applications
Concepts Explained in this Chapter (in order of presentation)
Modeling Univariate Time Series
Difference Equations
Terminology and Definitions
Stationarity and Invertibility of ARMA Processes
Linear Processes
Identification Tools
Concepts Explained in this Chapter (in order of presentation)
Approaches to ARIMA Modeling and Forecasting.Overview of Box-Jenkins Procedure
Identification of Degree of Differencing.Identification of Lag Orders
Model Estimation
Diagnostic Checking
Forecasting
Concepts Explained in this Chapter (in order of presentation)
Autoregressive Conditional Heteroskedastic Models
ARCH Process
GARCH Process
Estimation of the GARCH Models
Stationary ARMA-GARCH Models
Lagrange Multiplier Test
Variants of the GARCH Model
GARCH Model with Student''s t-Distributed Innovations
Multivariate GARCH Formulations
Appendix: Analysis of the Properties of the GARCH(1,1) Model
Concepts Explained in this Chapter (in order of presentation)
Vector Autoregressive Models I
VAR Models Defined
Stationary Autoregressive Distributed Lag Models
Vector Autoregressive Moving Average Models
Forecasting with VAR Models
Appendix: Eigenvectors and Eigenvalues
Concepts Explained in this Chapter (in order of presentation)
Vector Autoregressive Models II
Estimation of Stable VAR Models
Estimating the Number of Lags
Autocorrelation and Distributional Properties of Residuals
VAR Illustration
Concepts Explained in this Chapter (in order of presentation)
Cointegration and State Space Models
Cointegration
Error Correction Models
Theory and Methods of Estimation of Nonstationary VAR Models
State-Space Models
Concepts Explained in this Chapter (in order of presentation)
Robust Estimation
Robust Statistics
Robust Estimators of Regressions
Illustration: Robustness of the Corporate Bond Yield Spread Model.Concepts Explained in this Chapter (in order of presentation)
Principal Components Analysis and Factor Analysis
Factor Models
Principal Components Analysis
Factor Analysis.PCA and Factor Analysis Compared.Concepts Explained in this Chapter (in order of presentation)
Heavy-Tailed and Stable Distributions in Financial Econometrics
Basic Facts and Definitions of Stable Distributions
Properties of Stable Distributions
Estimation of the Parameters of the Stable Distribution
Applications to German Stock Da
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