Support Vector Machine as an Efficient Framework for Stock Market Volatility Forecasting-Reference-Cited by-同舟云学术

Support Vector Machine as an Efficient Framework for Stock Market Volatility Forecasting

Published:2006-02-16 Issue:2 Volume:3 Page:147-160
ISSN:1619-697X
Container-title:Computational Management Science
language:en
Short-container-title:CMS

Author:

Gavrishchaka Valeriy V.,Banerjee Supriya

Publisher

Springer Science and Business Media LLC

Subject

Information Systems,Management Information Systems

Link

http://link.springer.com/content/pdf/10.1007/s10287-005-0005-5.pdf

Reference36 articles.

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3. Baillie RT, Bollerslev T, Mikkelsen HO (1996) Fractionally integrated generalized autoregressive conditional heteroskedasticity. J Econom 74:3

4. Bishop CM (1995) Neural networks for pattern recognition. Clarendon Press, Oxford

5. Bollerslev T (1986) Generalized autoregressive conditional heteroskedasticity. J Econom 31:307

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