Direction-of-Change Forecasting using a Volatility- Based Recurrent Neural Network
This paper investigates the profitability of a trading strategy, based on recurrent neural networks, that attempts to predict the direction-of-change of the market in the case of the NASDAQ composite index. The sample extends over the period 2/8/1971 \u2013 4/7/1998, while the sub-period 4/8/1998 - 2/5/2002 has been reserved for out-of-sample testing purposes. We demonstrate that the incorporation in the trading rule of estimates of the conditional volatility changes strongly enhances its profitability during `bear' market periods. This improvement is being measured with respect to a nested model that does not include the volatility variable as well as to a buy & hold strategy. We suggest that our findings can be justified by invoking either the `volatility feedback' theory or the existence of portfolio insurance schemes in the equity markets. Our results are also consistent with the view that volatility dependence produces sign dependence.
|Date of creation:||2006|
|Date of revision:|
|Contact details of provider:|| Postal: Dept. of Economics and Econometrics, Universiteit van Amsterdam, Roetersstraat 11, NL - 1018 WB Amsterdam, The Netherlands|
Phone: + 31 20 525 52 58
Fax: + 31 20 525 52 83
Web page: http://www.fee.uva.nl/cendef/
More information through EDIRC
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Lawrence R. Glosten & Ravi Jagannathan & David E. Runkle, 1993.
"On the relation between the expected value and the volatility of the nominal excess return on stocks,"
157, Federal Reserve Bank of Minneapolis.
- Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. " On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
- Geert Bekaert & Guojun Wu, 1997.
"Asymmetric Volatility and Risk in Equity Markets,"
NBER Working Papers
6022, National Bureau of Economic Research, Inc.
- Peter F. Christoffersen & Francis X.Diebold, 2003.
"Financial Asset Returns, Direction-of-Change Forecasting, and Volatility Dynamics,"
PIER Working Paper Archive
04-009, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
- Peter F. Christoffersen & Francis X. Diebold, 2006. "Financial Asset Returns, Direction-of-Change Forecasting, and Volatility Dynamics," Management Science, INFORMS, vol. 52(8), pages 1273-1287, August.
- Christoffersen, Peter F. & Diebold, Francis X., 2003. "Financial asset returns, direction-of-change forecasting, and volatility dynamics," CFS Working Paper Series 2004/08, Center for Financial Studies (CFS).
- Peter F. Christoffersen & Francis X. Diebold, 2003. "Financial Asset Returns, Direction-of-Change Forecasting, and Volatility Dynamics," NBER Working Papers 10009, National Bureau of Economic Research, Inc.
- Abhyankar, A & Copeland, L S & Wong, W, 1997. "Uncovering Nonlinear Structure in Real-Time Stock-Market Indexes: The S&P 500, the DAX, the Nikkei 225, and the FTSE-100," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(1), pages 1-14, January.
- Henriksson, Roy D & Merton, Robert C, 1981. "On Market Timing and Investment Performance. II. Statistical Procedures for Evaluating Forecasting Skills," The Journal of Business, University of Chicago Press, vol. 54(4), pages 513-33, October.
- G. William Schwert, 2001.
"Stock Volatility in the New Millennium: How Wacky Is Nasdaq?,"
NBER Working Papers
8436, National Bureau of Economic Research, Inc.
- William Schwert, G., 2002. "Stock volatility in the new millennium: how wacky is Nasdaq?," Journal of Monetary Economics, Elsevier, vol. 49(1), pages 3-26, January.
- Fernando Fernández-Rodríguez & Christian González-Martel* & Simón Sosvilla-Rivero, .
"On the profitability of technical trading rules based on arifitial neural networks : evidence from the Madrid stock market,"
- Fernandez-Rodriguez, Fernando & Gonzalez-Martel, Christian & Sosvilla-Rivero, Simon, 2000. "On the profitability of technical trading rules based on artificial neural networks:: Evidence from the Madrid stock market," Economics Letters, Elsevier, vol. 69(1), pages 89-94, October.
- Gencay, Ramazan, 1998. "The predictability of security returns with simple technical trading rules," Journal of Empirical Finance, Elsevier, vol. 5(4), pages 347-359, October.
- Pesaran, M Hashem & Timmermann, Allan, 1995. " Predictability of Stock Returns: Robustness and Economic Significance," Journal of Finance, American Finance Association, vol. 50(4), pages 1201-28, September.
- Paul R. Krugman, 1987. "Trigger Strategies and Price Dynamics in Equity and Foreign Exchange Markets," NBER Working Papers 2459, National Bureau of Economic Research, Inc.
When requesting a correction, please mention this item's handle: RePEc:ams:ndfwpp:06-16. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Cees C.G. Diks)
If references are entirely missing, you can add them using this form.