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9780470644553

Analysis of Financial Time Series, 3rd Edition

by
  • ISBN13:

    9780470644553

  • ISBN10:

    0470644559

  • Format: eBook
  • Copyright: 2010-07-01
  • Publisher: Wiley
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Summary

This book provides a broad, mature, and systematic introduction to current financial econometric models and their applications to modeling and prediction of financial time series data. It utilizes real-world examples and real financial data throughout the book to apply the models and methods described.The author begins with basic characteristics of financial time series data before covering three main topics: Analysis and application of univariate financial time series The return series of multiple assets Bayesian inference in finance methodsKey features of the new edition include additional coverage of modern day topics such as arbitrage, pair trading, realized volatility, and credit risk modeling; a smooth transition from S-Plus to R; and expanded empirical financial data sets.The overall objective of the book is to provide some knowledge of financial time series, introduce some statistical tools useful for analyzing these series and gain experience in financial applications of various econometric methods.

Table of Contents

Financial Time Series and Their Characteristics
Asset Returns
Distributional Properties of Returns
Processes Considered
Linear time series
Stationarity
Autocorrelation
Linear time series
Simple AR models
Simple MA models
Simple ARMA Models
Unit-Root Nonstationarity
Seasonal Models
Regression with Correlated Errors
Consistent Covariance Matrix Estimation
Long-Memory Models
Volatility models
Characteristics of Volatility
Structure of a Model
Model Building
Testing for ARCH Effect
The ARCH Model
The GARCH Model
The Integrated GARCH Model
The GARCH-M Model
The Exponential GARCH Model
The Threshold GARCH Model
The CHARMA Model
Random Coefficient Autoregressive Models
The Stochastic Volatility Model
The Long-Memory Stochastic Volatility Model
Application
Alternative Approaches
Kurtosis of GARCH Models
Nonlinear Models and Their Applications
Nonlinear Models
Modeling
Forecasting
Application
High-Frequency Data Analysis and Market Microstructure
Nonsynchronous Trading
Bid-Ask Spread
Empirical Characteristics of Transactions Data
Models for Price Changes
Duration Models
Nonlinear Duration Models
Bivariate Models for Price Change and Duration
Application
Continuous-Time Models and Their Applications
Options
Some Continuous-Time Stochastic Processes
Ito's Lemma
Distributions of Price and Return
Black-Scholes Equation
Black-Scholes Pricing Formulas
An Extension of Ito's Lemma
Stochastic Integral
Jump Diffusion Models
Estimation of Continuous-Time Models
Extreme Values, Quantiles, and Value at Risk
Value at Risk
RiskMetrics
An Econometric Approach to VaR Calculation
Quantile Estimation
Extreme Value Theory
Extreme Value Approach to VaR
A New Approach to VaR
The Extremal Index
Multivariate Time Series Analysis and Its Applications
Weak Stationarity and Cross-Correlation Matrices
Vector Autoregressive Models
Vector Moving-Average Models
Vector ARMA Models
Unit-Root Nonstationarity and Cointegration
Cointegrated VAR Models
Threshold Cointegration and Arbitrage
Pairs Trading
Principal Component Analysis and Factor Models
A Factor Model
Macroeconometric Factor Models
Fundamental Factor Models
Principal Component Analysis
Statistical Factor Analysis
Asymptotic Principal Component Analysis
Multivariate Volatility Models and Their Applications
Exponentially Weighted Estimate
Some Multivariate GARCH Models
Reparameterization
GARCH Models for Bivariate Returns
Higher Dimensional Volatility Models
Factor-Volatility Models
Application
Multivariate t Distribution
State-Space Models and Kalman Filter
Local Trend Model
Linear State-Space Models
Model Transformation
Kalman Filter and Smoothing
Missing Values
Forecasting
Application
Markov Chain Monte Carlo Methods with Applications
Markov Chain Simulation
Gibbs Sampling
Bayesian Inference
Alternative Algorithm
Linear Regression With Time Series Errors
Missing Values and Outliers
Stochastic Volatility Models
A New Approach to SV Estimation
Markov Switching Models
Forecasting
Other Applications
Table of Contents provided by Publisher. All Rights Reserved.

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