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Author: | Bekiros S.D. Georgoutsos, D.A. |
Title: | Non-linear dynamics in financial asset returns: the predictive power of the CBOE volatility index |
Journal: | European Journal of Finance
2008 : JUL-SEP, VOL. 14:5-6, p. 397-408 |
Index terms: | financial models trading volatility assets return on investment neural networks |
Freeterms: | technical trading rules implied volatility Chicago Board Options Exchange(CBOE) recurrent neural network(RNN) Non-linear dynamics predictive power |
Language: | eng |
Abstract: | The author attempts to predicts the direction of change of the S&P500 index over the period 8 April 1998 to 5 February 2002 by means of a recurrent neural network (RNN).Based on the incorporation in the trading rule of the Chicago Board Options Exchange (CBOE) volatility index changes strongly enhances its profitability during 'bear' market periods. The paper argues improvement is measured in comparison with a RNN including changes of estimated conditional volatility measures, a linear autoregressive model as well as to a buy-and-hold strategy. The results indicates a number of theories that are consistent. |
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