The basics of financial econometrics : tools, concepts, and asset management applications / Frank J. Fabozzi [and three others] ; with the assistance of Markus Höchstötter.

Format:

Book

Author/Creator:

Fabozzi, Frank J.

Fabozzi, Frank J., author.

Höchstötter, Markus, author of introduction, etc.

Series:

Frank J. Fabozzi series.

THEi Wiley ebooks.

Frank J. Fabozzi Series

THEi Wiley ebooks

Language:

English

Subjects (All):

Finance--Econometric models.

Finance.

Econometrics.

Physical Description:

1 online resource (450 p.)

Edition:

1st edition

Place of Publication:

Hoboken, New Jersey : John Wiley & Sons, 2014.

Language Note:

English

System Details:

Access using campus network via VPN at home (THEi Users Only).

text file

Summary:

An accessible guide to the growing field of financial econometrics As finance and financial products have become more complex, financial econometrics has emerged as a fast-growing field and necessary foundation for anyone involved in quantitative finance. The techniques of financial econometrics facilitate the development and management of new financial instruments by providing models for pricing and risk assessment. In short, financial econometrics is an indispensable component to modern finance. Financial Econometric Basics covers the commonly used techniques in the fie

Contents:

The Basics of Financial Econometrics; Contents; Preface; Acknowledgments; About the Authors; CHAPTER 1 Introduction; FINANCIAL ECONOMETRICS AT WORK; Step 1: Model Selection; Step 2: Model Estimation; Step 3: Model Testing; THE DATA GENERATING PROCESS; APPLICATIONS OF FINANCIAL ECONOMETRICS TO INVESTMENT MANAGEMENT; Asset Allocation; Portfolio Construction; Portfolio Risk Management; Key Points; CHAPTER 2 Simple Linear Regression; THE ROLE OF CORRELATION; Stock Return Example; REGRESSION MODEL: LINEAR FUNCTIONAL RELATIONSHIP BETWEEN TWO VARIABLES

DISTRIBUTIONAL ASSUMPTIONS OF THE REGRESSION MODEL ESTIMATING THE REGRESSION MODEL; Application to Stock Returns; GOODNESS-OF-FIT OF THE MODEL; Relationship between Coefficient of Determination and Correlation Coefficient; TWO APPLICATIONS IN FINANCE; Estimating the Characteristic Line of a Mutual Fund; Controlling the Risk of a Stock Portfolio; LINEAR REGRESSION OF A NONLINEAR RELATIONSHIP; Linear Regression of Exponential Data; KEY POINTS; CHAPTER 3 Multiple Linear Regression; THE MULTIPLE LINEAR REGRESSION MODEL; ASSUMPTIONS OF THE MULTIPLE LINEAR REGRESSION MODEL

ESTIMATION OF THE MODEL PARAMETERSDESIGNING THE MODEL; DIAGNOSTIC CHECK AND MODEL SIGNIFICANCE; Testing for the Significance of the Model; Testing for the Significance of the Independent Variables; The F-Test for Inclusion of Additional Variables; APPLICATIONS TO FINANCE; Estimation of Empirical Duration; Predicting the 10-Year Treasury Yield; Benchmark Selection: Sharpe Benchmarks; Return-Based Style Analysis for Hedge Funds; Rich/Cheap Analysis for the Mortgage Market; Testing for Strong-Form Pricing Efficiency; Tests of the Capital Asset Pricing Model; Evidence for Multifactor Models

KEY POINTS CHAPTER 4 Building and Testing a Multiple Linear Regression Model; THE PROBLEM OF MULTICOLLINEARITY; Procedures for Mitigating Multicollinearity; MODEL BUILDING TECHNIQUES; Stepwise Inclusion Regression Method; Stepwise Exclusion Regression Method; Standard Stepwise Regression Method; TESTING THE ASSUMPTION OF THE MULTIPLE LINEAR REGRESSION MODEL; Tests for Linearity; Assumed Statistical Properties about the Error Term; Tests for the Residuals Being Normally Distributed; Tests For Constant Variance of the Error Term (Homoscedasticity); Absence of Autocorrelation of the Residuals

KEY POINTS CHAPTER 5 Introduction to Time Series Analysis; WHAT IS A TIME SERIES?; DECOMPOSITION OF TIME SERIES; Application to S&P 500 Index Returns; REPRESENTATION OF TIME SERIES WITH DIFFERENCE EQUATIONS; APPLICATION: THE PRICE PROCESS; Random Walk; Error Correction; KEY POINTS; CHAPTER 6 Regression Models with Categorical Variables; INDEPENDENT CATEGORICAL VARIABLES; Statistical Tests; DEPENDENT CATEGORICAL VARIABLES; Linear Probability Model; Probit Regression Model; Logit Regression Model; KEY POINTS; CHAPTER7 Quantile Regressions; LIMITATIONS OF CLASSICAL REGRESSION ANALYSIS

PARAMETER ESTIMATION

Notes:

Includes index.

Includes bibliographical references and index.

Description based on print version record.

ISBN:

9781118727232

1118727231

9781118856406

1118856406

9781118727430

1118727436

OCLC:

878139550