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Is volatility lognormal? Evidence from Italian futures

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  • Renò, Roberto
  • Rizza, Rosario

Abstract

We study the unconditional volatility distribution of the Italian futures market, measuring it via Fourier analysis. Our data set consists of all tick-by-tick transactions in 2000 and 2001, a period characterized by unusually high volatility levels in its final part, because of the dramatic events following 11 September 2001. Our results show that the standard assumption of lognormal unconditional volatility has to be rejected for such a turbulent sample, since it is unable to capture the tail behavior of the distribution; a much better description is provided by a Pareto tail.

Suggested Citation

  • Renò, Roberto & Rizza, Rosario, 2003. "Is volatility lognormal? Evidence from Italian futures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 322(C), pages 620-628.
    • Handle: RePEc:eee:phsmap:v:322:y:2003:i:c:p:620-628
    DOI: 10.1016/S0378-4371(02)02023-X
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    References listed on IDEAS

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    1. Yanhui Liu & Parameswaran Gopikrishnan & Pierre Cizeau & Martin Meyer & Chung-Kang Peng & H. Eugene Stanley, 1999. "The statistical properties of the volatility of price fluctuations," Papers cond-mat/9903369, arXiv.org, revised Mar 1999.
    2. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2000. "Exchange Rate Returns Standardized by Realized Volatility are (Nearly) Gaussian," Multinational Finance Journal, Multinational Finance Journal, vol. 4(3-4), pages 159-179, September.
    3. Nelson M. P. C. Areal & Stephen J. Taylor, 2002. "The realized volatility of FTSE‐100 futures prices," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 22(7), pages 627-648, July.
    4. Parameswaran Gopikrishnan & Vasiliki Plerou & Luis A. Nunes Amaral & Martin Meyer & H. Eugene Stanley, 1999. "Scaling of the distribution of fluctuations of financial market indices," Papers cond-mat/9905305, arXiv.org.
    5. Andersen, Torben G. & Bollerslev, Tim & Diebold, Francis X. & Ebens, Heiko, 2001. "The distribution of realized stock return volatility," Journal of Financial Economics, Elsevier, vol. 61(1), pages 43-76, July.
    6. Heiko Ebens, 1999. "Realized Stock Volatility," Economics Working Paper Archive 420, The Johns Hopkins University,Department of Economics, revised Jul 1999.
    7. Miccichè, Salvatore & Bonanno, Giovanni & Lillo, Fabrizio & Mantegna, Rosario N, 2002. "Volatility in financial markets: stochastic models and empirical results," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 314(1), pages 756-761.
    8. Pierre Cizeau & Yanhui Liu & Martin Meyer & C. -K. Peng & H. Eugene Stanley, 1997. "Volatility distribution in the S&P500 Stock Index," Papers cond-mat/9708143, arXiv.org.
    9. Andersen T. G & Bollerslev T. & Diebold F. X & Labys P., 2001. "The Distribution of Realized Exchange Rate Volatility," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 42-55, March.
    10. Barucci, Emilio & Reno, Roberto, 2002. "On measuring volatility and the GARCH forecasting performance," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 12(3), pages 183-200, July.
    11. Cizeau, Pierre & Liu, Yanhui & Meyer, Martin & Peng, C.-K. & Eugene Stanley, H., 1997. "Volatility distribution in the S&P500 stock index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 245(3), pages 441-445.
    12. Barucci, Emilio & Reno, Roberto, 2002. "On measuring volatility of diffusion processes with high frequency data," Economics Letters, Elsevier, vol. 74(3), pages 371-378, February.
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    Cited by:

    1. Klaus Grobys, 2024. "Science or scientism? On the momentum illusion," Annals of Finance, Springer, vol. 20(4), pages 479-519, December.
    2. Pasquale, Maria & Renò, Roberto, 2005. "Statistical properties of trading volume depending on size," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 346(3), pages 518-528.
    3. Grobys, Klaus, 2023. "Correlation versus co-fractality: Evidence from foreign-exchange-rate variances," International Review of Financial Analysis, Elsevier, vol. 86(C).
    4. Linden, Mikael, 2005. "Estimating the distribution of volatility of realized stock returns and exchange rate changes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 352(2), pages 573-583.

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