Time Series – Applications to Finance with R and S–Plus 2e

Name: Time Series – Applications to Finance with R and S–Plus 2e
Author: NH Chan

Applications to Finance with R and S–Plus

Gebonden Engels 2010 2e druk 9780470583623

167,12

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Samenvatting

This book is designed to help readers grasp the conceptual underpinnings of time series modeling in order to gain a deeper understanding of the ever–changing dynamics of the financial world. It covers theory and application equally for readers from both financial and mathematical backgrounds. The book offers succinct coverage of standard topics in statistical time series such as forecasting and spectral analysis in a manner that is both technical and conceptual. An author website provides instructor notations and additional software subroutines, as well as complete solutions to the exercises in the text.

Specificaties

ISBN13:9780470583623

Taal:Engels

Bindwijze:gebonden

Aantal pagina's:336

Uitgever:John Wiley & Sons

Druk:2

Hoofdrubriek:Financieel management, Financieel management

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Inhoudsopgave

List 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 and .
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.