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Time series : applications to finance / Ngai Hang Chan.

By: Material type: TextTextSeries: Wiley series in probability and statisticsPublisher: New York : Wiley-Interscience, [2002]Copyright date: ©2002Description: xiii, 203 pages : illustrations ; 24 cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 0471411175
  • 9780471411178
Subject(s): DDC classification:
  • 332.015195 21
LOC classification:
  • HA30.3 .C47 2002
Online resources:
Contents:
1. Introduction -- 2. Probability Models -- 3. Autoregressive Moving Average Models -- 4. Estimation in the Time Domain -- 5. Examples in SPLUS -- 6. Forecasting -- 7. Spectral Analysis -- 8. Nonstationarity -- 9. Heteroskedasticity -- 10. Multivariate Time Series -- 11. State Space Models -- 12. Multivariate GARCH -- 13. Cointegrations and Common Trends.
Review: "Time Series 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. Recent developments in nonstandard time series techniques are discussed and illustrated in detail with real financial examples. These techniques include nonstationarity, heteroskedasticity; multivariate time series; state space modeling and stochastic volatility; multivariate GARCH; and cointegrations and common trends." "All examples are systematically illustrated with S-Plus and highlight the relevance of time series in financial applications. Detailed analyses and explanations for the S-Plus commands, as well as challenging end-of-chapter exercises, are also provided."--BOOK JACKET.
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Holdings
Item type Current library Call number Copy number Status Date due Barcode
Book City Campus City Campus Main Collection 332.015195 CHA (Browse shelf(Opens below)) 1 Available A263242B

Includes bibliographical references (pages 195-199) and index.

1. Introduction -- 2. Probability Models -- 3. Autoregressive Moving Average Models -- 4. Estimation in the Time Domain -- 5. Examples in SPLUS -- 6. Forecasting -- 7. Spectral Analysis -- 8. Nonstationarity -- 9. Heteroskedasticity -- 10. Multivariate Time Series -- 11. State Space Models -- 12. Multivariate GARCH -- 13. Cointegrations and Common Trends.

"Time Series 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. Recent developments in nonstandard time series techniques are discussed and illustrated in detail with real financial examples. These techniques include nonstationarity, heteroskedasticity; multivariate time series; state space modeling and stochastic volatility; multivariate GARCH; and cointegrations and common trends." "All examples are systematically illustrated with S-Plus and highlight the relevance of time series in financial applications. Detailed analyses and explanations for the S-Plus commands, as well as challenging end-of-chapter exercises, are also provided."--BOOK JACKET.

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