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Is Volatility the Best Predictor of Market Crashes?

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Abstract

The objective of this paper is to determine the best predictor of equity market crashes by focusing particularly on volatility and market liquidity. In finance, volatility has traditionally been regarded as the best measure of market risk. However, this paper shows that the forecast value of market liquidity, in particular our modified calculated market depth, predicts equity market crashes much more accurately than does the forecast values of EGARCH or Implied Volatility.

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References

  • Admati, A. and Pfleiderer, P. (1988) A theory of intraday patterns: Volume and price variability, Review of Financial Studies 1, 3–40.

    Article  Google Scholar 

  • Amemiya, T. (1981) Qualitative response models: A survey, Journal of Economic Literature 19, 481–536.

    Google Scholar 

  • Amihud, Y. and Mendelson, H. (1986) Asset pricing and the bid-ask spread, Journal of Financial Economics 17, 223–249.

    Article  Google Scholar 

  • Beckers, S. (1981) Standard deviations in option prices as predictors of future stock price variability, Journal of Banking and Finance 5, 363–382.

    Article  Google Scholar 

  • Bekaert, G. and Wu, G. (2000) Asymmetric volatility and risk in equity markets, Review of Financial Studies 13, 1–42.

    Article  Google Scholar 

  • Black, F. (1976) Studies of stock price volatility changes, Proceedings of the 1976 Meetings of the Business and Economics Statistics Section, American Statistical Association, 177–181.

  • Blume, L. E., Easley, D. and O’Hara, M. (1994) Market statistics and technical analysis: The role of volume, Journal of Finance 49, 153–182.

    Google Scholar 

  • Bollerslev, T. (1986) Generalized autoregressive conditional heteroskedasticity, Journal of Econometrics 31, 307–327.

    Article  Google Scholar 

  • Box, G. E. P. and Jenkins, G. M. (1976) Time Series Analysis: Forecasting and Control, 2nd edn, Holden-Day, San Francisco.

    Google Scholar 

  • Campbell, J. Y. and Hentschel, L. (1992) No news is good news: An asymmetric model of changing volatility in stock returns, Journal of Financial Economics 31, 281–318.

    Article  Google Scholar 

  • Chiras, D. P. and Manaster, S. (1978) The information content of option prices and a test of market efficiency, Journal of Financial Economics 6, 213–234.

    Article  Google Scholar 

  • Chordia, T., Roll, R. W. and Subrahmanyam, A. (2000) Commonality in liquidity, Journal of Financial Economics 56, 3–28.

    Article  Google Scholar 

  • Chordia, T., Roll, R. W. and Subrahmanyam, A. (2001) Market liquidity and trading activity, Journal of Finance 56, 501–530.

    Article  Google Scholar 

  • Christie, A. A. (1982) The stochastic behavior of common stock variance: Value, leverage and interest rate effects, Journal of Financial Economics 10, 407–432.

    Article  Google Scholar 

  • Day, T and Lewis, C. M. (1992) Stock market volatility and the information content of stock index options, Journal of Econometrics 52, 267–287.

    Article  Google Scholar 

  • Duffie, D. and Pan, J. (1997) An overview of value at risk, Journal of Derivatives 4, 7–49.

    Google Scholar 

  • Engle, R. F. (1982) Autoregressive conditional heteroskedasticity with estimates of the variance of United Kingdom inflation, Econometrica 50, 987–1007.

    Google Scholar 

  • Engle, R. F. and Bollerslev, T. (1986) Modeling the persistence of conditional variances, Econometric Reviews 5, 1–50.

    MathSciNet  Google Scholar 

  • French, K. R., Schwert, G .W. and Stambaugh, R. F. (1987) Expected stock returns and volatility, Journal of Financial Economics 19, 3–29.

    Article  Google Scholar 

  • Glosten, L., Jagannathan, R. and Runkle, D. E. (1993) On the relation between the expected value and the volatility of the nominal excess return on stocks, Journal of Finance 48, 1779–1801.

    Google Scholar 

  • Godfrey, M. D., Granger, C. W. J. and Morgenstern, O. (1964) The random walk hypothesis of stock market behavior, Kyklos 17, 1–30.

    Google Scholar 

  • Goldfeld, S., Quandt, R. and Trotter, H. (1966) Maximization by Quadratic Hill Climbing, Econometrica 34, 541–551.

    Google Scholar 

  • Granger, C. W. J. and Morgenstern, O. (1963) Spectral analysis of New York stock market prices, Kyklos 16, 1–27.

    Google Scholar 

  • Greene, W. H. (2003) Econometric Analysis, Prentice Hall, New Jersey.

    Google Scholar 

  • Hasbrouck, J. and Seppi, D. J. (2001), Common factors in prices, order flows and liquidity, Journal of Financial Economics 59, 383–411.

    Article  Google Scholar 

  • Huberman, G. and Halka, D. (1999) Systematic liquidity. Working paper, Columbia Business School.

  • Hull, J. C. and White, A. (1998) Value at risk when daily changes in market variables are not normally distributed, Journal of Derivatives 5, 9–19.

    Google Scholar 

  • Jacoby, G., Fowler, D. J. and Gottesman, A. A. (2000) The capital asset pricing model and the liquidity effect: A theoretical approach, Journal of Financial Markets 3, 61–81.

    Article  Google Scholar 

  • James, C. M. and Edmister, R. O. (1983) The relation between common stock returns trading activity and market value, Journal of Finance 38, 1075–1086.

    Google Scholar 

  • Jorion, P. (1995) Predicting volatility in the foreign exchange market, Journal of Finance 50, 507–528.

    Google Scholar 

  • Jorion, P. (1997) Value at Risk: The New Benchmark for Controlling Market Risk, McGraw-Hill, Chicago.

    Google Scholar 

  • Kyle, A. S. (1985) Continuous auctions and insider trading, Econometrica 53, 1315–1335.

    Google Scholar 

  • Lamoureux, C. G. and Lastrapes, W. D. (1990) Heteroskedasticity in stock returns data: Volume versus GARCH effects, Journal of Finance 45, 221–229.

    Google Scholar 

  • Lamoureux, C. G. and Lastrapes, W. D. (1993) Forecasting stock-return variance: Towards an understanding of stochastic implied volatilities, Review of Financial Studies 6, 293–326.

    Article  Google Scholar 

  • Latane, H. A. and Rendleman, R. J. Jr. (1976) Standard deviation of stock price ratios implied by option premia, Journal of Finance 31, 369–382.

    Google Scholar 

  • Maddala, G. S. (2001) Introduction to Econometrics, John Wiley and Sons, Inc., New York.

    Google Scholar 

  • Nelson, D. B. (1991) Conditional heteroskedasticity in asset returns: New approach, Econometrica 59, 347–370.

    MathSciNet  Google Scholar 

  • O’Hara, M. (1995) Market Microstructure Theory, Blackwell Publishers Ltd., Oxford, U.K.

    Google Scholar 

  • Pindyck, R. S. (1984) Risk: Inflation, and the stock market, American Economic Review 74, 334–351.

    Google Scholar 

  • Stoll, H. R. (2000) Friction, Journal of Finance 55, 1479–1513.

    Article  Google Scholar 

  • Schwert, G. W. (1989) Why does stock market volatility change over time? Journal of Finance 44, 1115–1153.

    Google Scholar 

  • Subrahmanyam, A. (1991) Risk aversion, market liquidity, and price efficiency, Review of Financial Studies 4, 417–441.

    Article  Google Scholar 

  • Tsuji, C. (2002) Long-term memory and applying the multi-factor ARFIMA models in financial markets, Asia-Pacific Financial Markets 9, 283–304.

    Article  Google Scholar 

  • Turner, C. M., Startz, R. and Nelson, C. R. (1989) A markov model of heteroskedasticity, risk and learning in the stock market, Journal of Financial Economics 25, 3–22.

    Article  Google Scholar 

  • Wang, J. (1994) A model of competitive stock trading volume, Journal of Political Economy 102, 127–168.

    Article  Google Scholar 

  • Wood, R. L., McInish, T. H. and Ord, J. K. (1985) An investigation of transactions data for NYSE stocks, Journal of Finance 40, 723–739.

    Google Scholar 

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Correspondence to Chikashi Tsuji.

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Tsuji, C. Is Volatility the Best Predictor of Market Crashes?. Asia-Pacific Finan Markets 10, 163–185 (2003). https://doi.org/10.1007/s10690-005-6009-x

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