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ARCH Models and Financial Applications
Christian Gourieroux
€ 123.43
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Description for ARCH Models and Financial Applications
Hardback. The ARMA models have limitations when applied to the field of financial and monetary economics. Financial time series present nonlinear dynamic characteristics and ARCH models offer an adaptive framework for this problem. This book surveys the work in this area from the perspective of statistical theory, financial models, and applications. Series: Springer Series in Statistics. Num Pages: 238 pages, biography. BIC Classification: KCBM; KFF; PBWH. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 235 x 155 x 14. Weight in Grams: 520.
1.1 The DevelopmentofARCH Models Time series models have been initially introduced either for descriptive purposes like prediction and seasonal correction or for dynamic control. In the 1970s, the researchfocusedonaspecificclassoftimeseriesmodels,theso-calledautoregres- sive moving average processes (ARMA), which were very easy to implement. In thesemodels,thecurrentvalueoftheseriesofinterestiswrittenasalinearfunction ofits own laggedvalues andcurrentandpastvaluesofsomenoiseprocess, which can be interpreted as innovations to the system. However, this approach has two major drawbacks: 1) it is essentially a linear setup, which automatically restricts the type of dynamics to be approximated; 2) it is generally applied without im- posing a priori constraintson the autoregressive and moving average parameters, which is inadequatefor structural ... Read more
1.1 The DevelopmentofARCH Models Time series models have been initially introduced either for descriptive purposes like prediction and seasonal correction or for dynamic control. In the 1970s, the researchfocusedonaspecificclassoftimeseriesmodels,theso-calledautoregres- sive moving average processes (ARMA), which were very easy to implement. In thesemodels,thecurrentvalueoftheseriesofinterestiswrittenasalinearfunction ofits own laggedvalues andcurrentandpastvaluesofsomenoiseprocess, which can be interpreted as innovations to the system. However, this approach has two major drawbacks: 1) it is essentially a linear setup, which automatically restricts the type of dynamics to be approximated; 2) it is generally applied without im- posing a priori constraintson the autoregressive and moving average parameters, which is inadequatefor structural ... Read more
Product Details
Format
Hardback
Publication date
1997
Publisher
Springer-Verlag New York Inc. United States
Number of pages
238
Condition
New
Series
Springer Series in Statistics
Number of Pages
229
Place of Publication
New York, NY, United States
ISBN
9780387948768
SKU
V9780387948768
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15
Reviews for ARCH Models and Financial Applications
From the reviews: RISKBOOK.COM "Gourieroux offers a nice balance of theory and application in this book on ARCH modeling in finance…The book is well written and has extensive references. Its focus on finance will appeal to financial engineers and financial risk managers."