Description
Book SynopsisA new edition of the comprehensive, hands-on guide to financial time series, now featuring S-Plus and R software
Time Series: Applications to Finance with R and S-Plus, Second Edition is designed to present an in-depth introduction to the conceptual underpinnings and modern ideas of time series analysis. Utilizing interesting, real-world applications and the latest software packages, this book successfully helps readers grasp the technical and conceptual manner of the topic in order to gain a deeper understanding of the ever-changing dynamics of the financial world.
With balanced coverage of both theory and applications, this Second Edition includes new content to accurately reflect the current state-of-the-art nature of financial time series analysis. A new chapter on Markov Chain Monte Carlo presents Bayesian methods for time series with coverage of Metropolis-Hastings algorithm, Gibbs sampling, and a case study that explores the relevance of these techniques for und
Trade Review
"Both are on topics of intense interest among academicians and financial practitioners. Their inclusoin makes the book more up-to-date and hopefully entertains a broader spectrum of readers. Upon many requests from users of the first edition, a new chapter on solutions to selected exercises has also been prepared so as to make the book more accessible to instructors and students alike." (Mathematical Reviews, 2011)
Table of ContentsList of Figures.
List of Tables.
Preface.
Preface to the First Edition.
1 Introduction.
1.1 Basic Description.
1.2 Simple Descriptive Techniques.
1.3 Transformations.
1.4 Example.
1.5 Conclusions.
1.6 Exercises.
2 Probability Models.
2.1 Introduction.
2.2 Stochastic Processes.
2.3 Examples.
2.4 Sample Correlation Function.
2.5 Exercises.
3 Autoregressive Moving Average Models.
3.1 Introduction.
3.2 Moving Average Models.
3.3 Autoregressive Models.
3.4 ARMA Models.
3.5 ARIMA Models.
3.6 Seasonal ARIMA.
3.7 Exercises.
4 Estimation in the Time Domain.
4.1 Introduction.
4.2 Moment Estimators.
4.3 Autoregressive Models.
4.4 Moving Average Models.
4.5 ARMA Models.
4.6 Maximum Likelihood Estimates.
4.7 Partial ACF.
4.8 Order Selections.
4.9 Residual Analysis.
4.10 Model Building.
4.11 Exercises.
5 Examples in SPLUS and R.
5.1 Introduction.
5.2 Example 1.
5.3 Example 2.
5.4 Exercises.
6 Forecasting.
6.1 Introduction.
6.2 Simple Forecasts.
6.3 Box and Jenkins Approach.
6.4 Treasury Bill Example.
6.5 Recursions.
6.6 Exercises.
7 Spectral Analysis.
7.1 Introduction.
7.2 Spectral Representation Theorems.
7.3 Periodogram.
7.4 Smoothing of Periodogram.
7.5 Conclusions.
7.6 Exercises.
8 Nonstationarity.
8.1 Introduction.
8.2 Nonstationarity in Variance.
8.3 Nonstationarity in Mean: Random Walk with Drift.
8.4 Unit Root Test.
8.5 Simulations.
8.6 Exercises.
9 Heteroskedasticity.
9.1 Introduction.
9.2 ARCH.
9.3 GARCH.
9.4 Estimation and Testing for ARCH.
9.5 Example of Foreign Exchange Rates.
9.6 Exercises.
10 Multivariate Time Series.
10.1 Introduction.
10.2 Estimation of μ and Γ.
10.3 Multivariate ARMA Processes.
10.4 Vector AR Models.
10.5 Example of Inferences for VAR.
10.6 Exercises.
11 State Space Models.
11.1 Introduction.
11.2 State Space Representation.
11.3 Kalman Recursions.
11.4 Stochastic Volatility Models.
11.5 Example of Kalman Filtering of Term Structure.
11.6 Exercises.
12 Multivariate GARCH.
12.1 Introduction.
12.2 General Model.
12.3 Quadratic Form.
12.4 Example of Foreign Exchange Rates.
12.5 Conclusions.
12.6 Exercises.
13 Cointegrations and Common Trends.
13.1 Introduction.
13.2 Definitions and Examples.
13.3 Error Correction Form.
13.4 Granger’s Representation Theorem.
13.5 Structure of Cointegrated Systems.
13.6 Statistical Inference for Cointegrated Systems.
13.7 Example of Spot Index and Futures.
13.8 Conclusions.
13.9 Exercises.
14 Markov Chain Monte Carlo Methods.
14.1 Introduction.
14.2 Bayesian Inference.
14.3 Markov Chain Monte Carlo.
14.4 Exercises.
15 Statistical Arbitrage.
15.1 Introduction.
15.2 Pairs Trading.
15.3 Cointegration.
15.4 Simple Pairs Trading.
15.5 Cointegrations and Pairs Trading.
15.6 Hang Seng Index Components Example.
15.7 Exercises.
16 Answers to Selected Exercises.
16.1 Chapter 1.
16.2 Chapter 2.
16.3 Chapter 3.
16.4 Chapter 4.
16.5 Chapter 5.
16.6 Chapter 6.
16.7 Chapter 7.
16.8 Chapter 8.
16.9 Chapter 9.
16.10 Chapter 10.
16.11 Chapter 11.
16.12 Chapter 12.
16.13 Chapter 13.
16.14 Chapter 14.
16.15 Chapter 15.
References.
Subject Index.
Author Index.
