The basics of financial econometrics tools, concepts, and asset management applications
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 fac...
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| Otros Autores: | , |
| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Hoboken, New Jersey :
John Wiley & Sons
2014.
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| Edición: | 1st edition |
| Colección: | Frank J. Fabozzi series.
THEi Wiley ebooks. |
| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009628720806719 |
Tabla de Contenidos:
- 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
