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Modelling market volatilities: the neural network perspective

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  • F. Gonzalez Miranda
  • N. Burgess
Abstract
This paper investigates the use of Artificial Neural Networks (NN) to forecast volatility. In particular, we assess the dynamic behaviour of market volatility by forecasting the volatility implied in the transaction prices of the Ibex35 index options. The use of the NN technique is done within the framework of a model building strategy that tries to capitalize on the well known feature of persistence in volatility series. We demonstrate that forecasting with non-linear NNs generally produces forecasts which, on the basis of out-of-sample forecast encompassing tests and mean squared error comparisons, ordinarily dominate forecasts from traditional linear methods. Better forecasting results for the NN are due to its flexibility to account for potentially complex non-linear relationships, which are not well captured by traditional linear methods. We test and reject the hypothesis that volatility changes are unpredictable on an hourly basis.

Suggested Citation

  • F. Gonzalez Miranda & N. Burgess, 1997. "Modelling market volatilities: the neural network perspective," The European Journal of Finance, Taylor & Francis Journals, vol. 3(2), pages 137-157.
    • Handle: RePEc:taf:eurjfi:v:3:y:1997:i:2:p:137-157
    DOI: 10.1080/135184797337499
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    1. Kuldeep Shastri & Kulpatra Wethyavivorn, 1987. "The Valuation Of Currency Options For Alternate Stochastic Processes," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 10(4), pages 283-293, December.
    2. Stein, Elias M & Stein, Jeremy C, 1991. "Stock Price Distributions with Stochastic Volatility: An Analytic Approach," The Review of Financial Studies, Society for Financial Studies, vol. 4(4), pages 727-752.
    3. Yock Y. Chong & David F. Hendry, 1986. "Econometric Evaluation of Linear Macro-Economic Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 53(4), pages 671-690.
    4. repec:bla:jfinan:v:44:y:1989:i:5:p:1115-53 is not listed on IDEAS
    5. Harvey, Campbell R & Whaley, Robert E, 1991. "S&P 100 Index Option Volatility," Journal of Finance, American Finance Association, vol. 46(4), pages 1251-1261, September.
    6. Pagan, Adrian R. & Schwert, G. William, 1990. "Alternative models for conditional stock volatility," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 267-290.
    7. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    8. Schwert, G William, 1990. "Stock Volatility and the Crash of '87," The Review of Financial Studies, Society for Financial Studies, vol. 3(1), pages 77-102.
    9. Canina, Linda & Figlewski, Stephen, 1993. "The Informational Content of Implied Volatility," The Review of Financial Studies, Society for Financial Studies, vol. 6(3), pages 659-681.
    10. Day, Theodore E. & Lewis, Craig M., 1988. "The behavior of the volatility implicit in the prices of stock index options," Journal of Financial Economics, Elsevier, vol. 22(1), pages 103-122, October.
    11. Chatfield, Chris, 1993. "Neural networks: Forecasting breakthrough or passing fad?," International Journal of Forecasting, Elsevier, vol. 9(1), pages 1-3, April.
    12. L. Kavalieris, 1989. "The Estimation Of The Order Of An Autoregression Using Recursive Residuals And Cross‐Validation," Journal of Time Series Analysis, Wiley Blackwell, vol. 10(3), pages 271-281, May.
    13. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    14. Chung-Ming Kuan, 2006. "Artificial Neural Networks," IEAS Working Paper : academic research 06-A010, Institute of Economics, Academia Sinica, Taipei, Taiwan.
    15. Kandel, Shmuel & Stambaugh, Robert F, 1990. "Expectations and Volatility of Consumption and Asset Returns," The Review of Financial Studies, Society for Financial Studies, vol. 3(2), pages 207-232.
    16. Latane, Henry A & Rendleman, Richard J, Jr, 1976. "Standard Deviations of Stock Price Ratios Implied in Option Prices," Journal of Finance, American Finance Association, vol. 31(2), pages 369-381, May.
    17. Shanken, Jay, 1990. "Intertemporal asset pricing : An Empirical Investigation," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 99-120.
    18. Christie, Andrew A., 1982. "The stochastic behavior of common stock variances : Value, leverage and interest rate effects," Journal of Financial Economics, Elsevier, vol. 10(4), pages 407-432, December.
    19. 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.
    20. Black, Fischer, 1976. "The pricing of commodity contracts," Journal of Financial Economics, Elsevier, vol. 3(1-2), pages 167-179.
    21. Hull, John C & White, Alan D, 1987. "The Pricing of Options on Assets with Stochastic Volatilities," Journal of Finance, American Finance Association, vol. 42(2), pages 281-300, June.
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    2. László Vancsura & Tibor Tatay & Tibor Bareith, 2023. "Evaluating the Effectiveness of Modern Forecasting Models in Predicting Commodity Futures Prices in Volatile Economic Times," Risks, MDPI, vol. 11(2), pages 1-16, January.
    3. Rita Laura D’Ecclesia & Daniele Clementi, 2021. "Volatility in the stock market: ANN versus parametric models," Annals of Operations Research, Springer, vol. 299(1), pages 1101-1127, April.
    4. Melike Bildirici & Nilgun Guler Bayazit & Yasemen Ucan, 2020. "Analyzing Crude Oil Prices under the Impact of COVID-19 by Using LSTARGARCHLSTM," Energies, MDPI, vol. 13(11), pages 1-18, June.
    5. Psaradellis, Ioannis & Sermpinis, Georgios, 2016. "Modelling and trading the U.S. implied volatility indices. Evidence from the VIX, VXN and VXD indices," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1268-1283.

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