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Forecast Improvements Using A Volatility Index

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  • LeBaron, B.

Abstract

This paper explores the possibility of improved out of sample forecasting for stock returns and foreign exchange rates using observed nonlinearities in the two series. Forecasting is done using nonparametric techniques where important information is obtained from the current level of volatility in the series. For both series forecast improvements are observed, but for stock returns the improvements are only marginal. These results indicate the usefulness and stability of some types of nonlinear modelling for financial markets. Copyright 1992 by John Wiley & Sons, Ltd.
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  • LeBaron, B., 1991. "Forecast Improvements Using A Volatility Index," Working papers 9105, Wisconsin Madison - Social Systems.
    • Handle: RePEc:att:wimass:9105
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    Cited by:

    1. Nikolaou, Kleopatra, 2008. "The behaviour of the real exchange rate: Evidence from regression quantiles," Journal of Banking & Finance, Elsevier, vol. 32(5), pages 664-679, May.
    2. Bertrand Maillet & Thierry Michel, 2000. "Further insights on the puzzle of technical analysis profitability," The European Journal of Finance, Taylor & Francis Journals, vol. 6(2), pages 196-224.
    3. Blake LeBaron, "undated". "Technical Trading Rules and Regime Shifts in Foreign Exchange," Working papers _007, University of Wisconsin - Madison.
    4. Preminger, Arie & Franck, Raphael, 2007. "Forecasting exchange rates: A robust regression approach," International Journal of Forecasting, Elsevier, vol. 23(1), pages 71-84.
    5. Meade, Nigel, 2002. "A comparison of the accuracy of short term foreign exchange forecasting methods," International Journal of Forecasting, Elsevier, vol. 18(1), pages 67-83.
    6. Gencay, Ramazan, 1999. "Linear, non-linear and essential foreign exchange rate prediction with simple technical trading rules," Journal of International Economics, Elsevier, vol. 47(1), pages 91-107, February.
    7. Lucio Sarno & Giorgio Valente, 2005. "Modelling and forecasting stock returns: exploiting the futures market, regime shifts and international spillovers," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(3), pages 345-376, March.
    8. Theodore Panagiotidis, 2010. "An Out-of-Sample Test for Nonlinearity in Financial Time Series: An Empirical Application," Computational Economics, Springer;Society for Computational Economics, vol. 36(2), pages 121-132, August.
    9. Kleopatra Nikolaou, 2007. "The behaviour of the real exchange rate: Evidence from regression quantiles," Money Macro and Finance (MMF) Research Group Conference 2006 46, Money Macro and Finance Research Group.
    10. Dhekra Azouzi & Rohit Vishal Kumar & Chaker Aloui, 2011. "Forward Rate Unbiasedness Hypothesis in the Tunisian Exchange Rate Market," International Journal of Academic Research in Business and Social Sciences, Human Resource Management Academic Research Society, International Journal of Academic Research in Business and Social Sciences, vol. 1(2), pages 17-44, July.
    11. Sarno, Lucio & Valente, Giorgio, 2005. "Empirical exchange rate models and currency risk: some evidence from density forecasts," Journal of International Money and Finance, Elsevier, vol. 24(2), pages 363-385, March.
    12. Sarantis, Nicholas, 2001. "Nonlinearities, cyclical behaviour and predictability in stock markets: international evidence," International Journal of Forecasting, Elsevier, vol. 17(3), pages 459-482.
    13. Sarno, Lucio & Valente, Giorgio, 2006. "Deviations from purchasing power parity under different exchange rate regimes: Do they revert and, if so, how?," Journal of Banking & Finance, Elsevier, vol. 30(11), pages 3147-3169, November.
    14. Lucio Sarno & Giorgio Valente & Mark E. Wohar, 2004. "Monetary Fundamentals and Exchange Rate Dynamics under Different Nominal Regimes," Economic Inquiry, Western Economic Association International, vol. 42(2), pages 179-193, April.
    15. Luke Lin & Chun I. Lee, 2016. "Central Bank Intervention, Exchange Rate Regime and the Purchasing Power Parity," The World Economy, Wiley Blackwell, vol. 39(8), pages 1256-1274, August.
    16. Jaditz Ted & Riddick Leigh A., 2000. "Time-Series Near-Neighbor Regression," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 4(1), pages 1-11, April.
    17. Clarida, Richard H. & Sarno, Lucio & Taylor, Mark P. & Valente, Giorgio, 2003. "The out-of-sample success of term structure models as exchange rate predictors: a step beyond," Journal of International Economics, Elsevier, vol. 60(1), pages 61-83, May.
    18. Lucio Sarno, 2003. "Nonlinear Exchange Rate Models: A Selective Overview," Rivista di Politica Economica, SIPI Spa, vol. 93(4), pages 3-46, July-Augu.
    19. Anatolyev, Stanislav, 2008. "A 10-year retrospective on the determinants of Russian stock returns," Research in International Business and Finance, Elsevier, vol. 22(1), pages 56-67, January.
    20. Tauchen, George & Zhang, Harold & Liu, Ming, 1996. "Volume, volatility, and leverage: A dynamic analysis," Journal of Econometrics, Elsevier, vol. 74(1), pages 177-208, September.
    21. Nam, Kiseok & Pyun, Chong Soo & Avard, Stephen L., 2001. "Asymmetric reverting behavior of short-horizon stock returns: An evidence of stock market overreaction," Journal of Banking & Finance, Elsevier, vol. 25(4), pages 807-824, April.
    22. Nikolaou, Kleopatra, 2006. "The behaviour of the real exchange rate: evidence from regression quantiles," Working Paper Series 667, European Central Bank.

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    Keywords

    time series ; economic models;

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