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Forecasting volatilities in equity, bond and money markets: A market-based approach

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  • Kent Wang

    (Wang Yanan Institute for Studies in Economics, Xiamen University and UQ Business School, The University of Queensland, k.wang@business.uq.edu.au)

Abstract

This study examines the forecasting power of the most popular volatility forecasting models in the S&P 500 index market, the Eurodollar futures market, and the 30-year US T-Bond futures market at a daily level using a market-based option-pricing error approach. Comparison has been made between two methods including and excluding implied volatility in option-pricing error approach in forecasting next-day volatilities. To remove any advantage to option-implied volatility, the analysis is performed in two steps. Spurious regression biases and biases in the measurement of volatility forecasts are controlled for.The evidence from this paper supports the use of implied volatility as a proxy for market volatility, as it works best in forecasting next-day realized volatility in all the three US markets. The appropriateness of including implied volatility in option-pricing error approach is also discussed.

Suggested Citation

  • Kent Wang, 2010. "Forecasting volatilities in equity, bond and money markets: A market-based approach," Australian Journal of Management, Australian School of Business, vol. 35(2), pages 165-180, August.
  • Handle: RePEc:sae:ausman:v:35:y:2010:i:2:p:165-180
    DOI: 10.1177/0312896210370080
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    1. Karolyi, G. Andrew, 1993. "A Bayesian Approach to Modeling Stock Return Volatility for Option Valuation," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 28(4), pages 579-594, December.
    2. Owain Ap Gwilym & Mike Buckle, 1999. "Volatility forecasting in the framework of the option expiry cycle," The European Journal of Finance, Taylor & Francis Journals, vol. 5(1), pages 73-94.
    3. Jorion, Philippe, 1995. "Predicting Volatility in the Foreign Exchange Market," Journal of Finance, American Finance Association, vol. 50(2), pages 507-528, June.
    4. Phillips, P.C.B., 1986. "Understanding spurious regressions in econometrics," Journal of Econometrics, Elsevier, vol. 33(3), pages 311-340, December.
    5. Bekaert, Geert & Wu, Guojun, 2000. "Asymmetric Volatility and Risk in Equity Markets," The Review of Financial Studies, Society for Financial Studies, vol. 13(1), pages 1-42.
    6. Granger, C. W. J. & Newbold, P., 1974. "Spurious regressions in econometrics," Journal of Econometrics, Elsevier, vol. 2(2), pages 111-120, July.
    7. Jean-Philippe Bouchaud & Andrew Matacz & Marc Potters, 2001. "The leverage effect in financial markets: retarded volatility and market panic," Science & Finance (CFM) working paper archive 0101120, Science & Finance, Capital Fund Management.
    8. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2003. "Modeling and Forecasting Realized Volatility," Econometrica, Econometric Society, vol. 71(2), pages 579-625, March.
    9. Nicolas P. B. Bollen & Tom Smith & Robert E. Whaley, 2003. "Optimal contract design: For whom?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 23(8), pages 719-750, August.
    10. Fair, Ray C & Shiller, Robert J, 1990. "Comparing Information in Forecasts from Econometric Models," American Economic Review, American Economic Association, vol. 80(3), pages 375-389, June.
    11. Ser-Huang Poon & Clive W.J. Granger, 2003. "Forecasting Volatility in Financial Markets: A Review," Journal of Economic Literature, American Economic Association, vol. 41(2), pages 478-539, June.
    12. Barone-Adesi, Giovanni & Whaley, Robert E, 1987. "Efficient Analytic Approximation of American Option Values," Journal of Finance, American Finance Association, vol. 42(2), pages 301-320, June.
    13. Brailsford, Timothy J. & Faff, Robert W., 1996. "An evaluation of volatility forecasting techniques," Journal of Banking & Finance, Elsevier, vol. 20(3), pages 419-438, April.
    14. Lamoureux, Christopher G & Lastrapes, William D, 1993. "Forecasting Stock-Return Variance: Toward an Understanding of Stochastic Implied Volatilities," The Review of Financial Studies, Society for Financial Studies, vol. 6(2), pages 293-326.
    15. Beckers, Stan, 1981. "Standard deviations implied in option prices as predictors of future stock price variability," Journal of Banking & Finance, Elsevier, vol. 5(3), pages 363-381, September.
    16. Fleming, Jeff & Kirby, Chris & Ostdiek, Barbara, 2003. "The economic value of volatility timing using "realized" volatility," Journal of Financial Economics, Elsevier, vol. 67(3), pages 473-509, March.
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    Cited by:

    1. Zheyao Pan, 2018. "A state‐price volatility index for the U.S. government bond market," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(S1), pages 573-597, November.
    2. Robert E. Marks, 2010. "Editorial: A final farewell," Australian Journal of Management, Australian School of Business, vol. 35(2), pages 115-117, August.
    3. repec:wyi:journl:002192 is not listed on IDEAS
    4. Jamie Alcock & Godfrey Smith, 2017. "Non-parametric American option valuation using Cressie–Read divergences," Australian Journal of Management, Australian School of Business, vol. 42(2), pages 252-275, May.
    5. Michael O'Neill & Gulasekaran Rajaguru, 2020. "A response surface analysis of critical values for the lead‐lag ratio with application to high frequency and non‐synchronous financial data," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 60(4), pages 3979-3990, December.
    6. Kent Wang & Yuqiang Guo, 2014. "Predictability of time-varying jump premiums: Evidence based on calibration," Australian Journal of Management, Australian School of Business, vol. 39(3), pages 369-394, August.

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