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Forecasting volatility in the financ...

Knight, John L.

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Forecasting volatility in the financial markets

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Forecasting volatility in the financial markets/ edited by John Knight, Stephen Satchell.
其他作者:	Knight, John L.
出版者:	Amsterdam ;Butterworth-Heinemann, : 2007.,
面頁冊數:	viii, 415 p. :ill. ;25 cm.
標題:	Options (Finance) - Mathematical models. -
電子資源:	http://www.sciencedirect.com/science/book/9780750669429An electronic book accessible through the World Wide Web; click for information
電子資源:	http://www.loc.gov/catdir/toc/fy0801/2007278282.html
ISBN:	075066942X

Forecasting volatility in the financial markets
Forecasting volatility in the financial markets[electronic resource] /edited by John Knight, Stephen Satchell. - 3rd ed. - Amsterdam ;Butterworth-Heinemann,2007. - viii, 415 p. :ill. ;25 cm. - Quantitative finance series.

Includes bibliographical references and index.

Volatility modelling and forecasting in finance /Linlan Xiao and Abdurrahman Aydemir --

This new edition of Forecasting Volatility in the Financial Markets assumes that the reader has a firm grounding in the key principles and methods of understanding volatility measurement and builds on that knowledge to detail cutting-edge modelling and forecasting techniques. It provides a survey of ways to measure risk and define the different models of volatility and return. Editors John Knight and Stephen Satchell have brought together an impressive array of contributors who present research from their area of specialization related to volatility forecasting. Readers with an understanding of volatility measures and risk management strategies will benefit from this collection of up-to-date chapters on the latest techniques in forecasting volatility. Chapters new to this third edition: * What good is a volatility model? Engle and Patton * Applications for portfolio variety Dan diBartolomeo * A comparison of the properties of realized variance for the FTSE 100 and FTSE 250 equity indices Rob Cornish * Volatility modeling and forecasting in finance Xiao and Aydemir * An investigation of the relative performance of GARCH models versus simple rules in forecasting volatility Thomas A. Silvey * Leading thinkers present newest research on volatility forecasting *International authors cover a broad array of subjects related to volatility forecasting *Assumes basic knowledge of volatility, financial mathematics, and modelling.

Electronic reproduction.
Amsterdam :
Elsevier Science & Technology,
2008.

Mode of access: World Wide Web.

ISBN: 075066942X

Source: 130442:130546Elsevier Science & Technologyhttp://www.sciencedirect.comSubjects--Topical Terms:

647825
Options (Finance)
--Mathematical models.Index Terms--Genre/Form:

542853
Electronic books.

LC Class. No.: HG6024.A3 / .F675 2007eb

Dewey Class. No.: 332.66/2042

Forecasting volatility in the financial markets
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505 0 0 $t Volatility modelling and forecasting in finance / $r Linlan Xiao and Abdurrahman Aydemir -- $t What good is a volatility model? / $r Robert F. Engle and Andrew J. Patton -- $t Applications of portfolio variety/ $r Dan diBartolomeo -- $t Comparison of the properties of realized variance for the FTSE 100 and FTSE 250 equity indices / $r Rob Cornish -- $t Investigation of the relative performance of GARCH models versus simple rules in forecasting volatility/ $r Thomas A. Silvey -- $t Stochastic volatility and option pricing / $r George J. Jiang -- $t Modelling slippage : an application to the bund futures contract/ $r Emmanuel Acar and Edouard Petitdidier -- $t Real trading volume and price action in the foreign exchange markets / $r Pierre Lequeux -- $t Implied risk-neutral probability density functions from option prices : a central bank perspective/ $r Bhupinder Bahra -- $t Hashing GARCH : a reassessment of volatility forecasting performance/ $r George A. Christodoulakis and Stephen E. Satchell -- $t Implied volatility forecasting : a comparison of different procedures including fractionally integrated models with applications to UK equity options/ $r Soosung Hwang and Stephen E. Satchell -- $t GARCH predictions and the predictions of option prices / $r John Knight and Stephen E. Satchell -- $t Volatility forecasting in a tick data model / $r L. C. G. Rogers -- $t Econometric model of downside risk/ $r Shaun Bond -- $t Variations in the mean and volatility of stock returns around turning points of the business cycle / $r Gabriel Perez-Quiros and Allan Timmermann -- $t Long memory in stochastic volatility/ $r Andrew C. Harvey -- $t GARCH processes-- some exact results, some difficulties and a suggested remedy / $r John L. Knight and Stephen E. Satchell -- $t Generating composite volatility forecasts with random factor betas / $r George A. Christodoulakis.
520 $a This new edition of Forecasting Volatility in the Financial Markets assumes that the reader has a firm grounding in the key principles and methods of understanding volatility measurement and builds on that knowledge to detail cutting-edge modelling and forecasting techniques. It provides a survey of ways to measure risk and define the different models of volatility and return. Editors John Knight and Stephen Satchell have brought together an impressive array of contributors who present research from their area of specialization related to volatility forecasting. Readers with an understanding of volatility measures and risk management strategies will benefit from this collection of up-to-date chapters on the latest techniques in forecasting volatility. Chapters new to this third edition: * What good is a volatility model? Engle and Patton * Applications for portfolio variety Dan diBartolomeo * A comparison of the properties of realized variance for the FTSE 100 and FTSE 250 equity indices Rob Cornish * Volatility modeling and forecasting in finance Xiao and Aydemir * An investigation of the relative performance of GARCH models versus simple rules in forecasting volatility Thomas A. Silvey * Leading thinkers present newest research on volatility forecasting *International authors cover a broad array of subjects related to volatility forecasting *Assumes basic knowledge of volatility, financial mathematics, and modelling.
533 $a Electronic reproduction. $b Amsterdam : $c Elsevier Science & Technology, $d 2008. $n Mode of access: World Wide Web. $n System requirements: Web browser. $n Title from title screen (viewed on Mar. 10, 2008). $n Access may be restricted to users at subscribing institutions.
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