Modeling Financial Time Series with R

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Contents

The field of financial econometrics has exploded over the last decade. This book represents an integration of theory, methods, and examples using the open source R statistical modeling language to facilitate the practice of financial econometrics. It is written for researchers and practitioners in the finance industry, academic researchers in economics and finance, and advanced MBA and graduate students in economics and finance. Readers are assumed to have a basic knowledge of R and a solid grounding in basic statistics and time series concepts. 

Overview of the Book

The chapters in the book cover univariate and multivariate models for analyzing financial time series using R.

Table of Contents

Abbreviated Table of Contents

Basics of R * Time Series Specification, Manipulation and Visualization in R * Time Series Concepts * Unit Root Tests * Modeling Extreme Values * Time Series Regression Modeling * Univariate GARCH Models * Long Memory Time Series Modeling *  Systems of Regression Equations * Vector Autoregressive Models for Multivariate Time Series * Cointegration * Multivariate GARCH Modeling * State Space Models * Factor Models for Asset Returns * Term Structure of Interest Rates * Nonlinear Models * Copulas * Continuous Time Financial Models * Generalized Method of Moments *  Index

Full Table of Contents

• MFTSR.pdf

Last updated: May 15, 2014

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