Causality between stock market and “fear gauge” indices: An empirical analysis with E-statistics
Abstract
This study investigates empirically the validity of three hypotheses that have been advanced to explain the tendency of stock market and volatility indices to move in opposite directions, using the notion of Brownian distance correlation. We consider three stock market-implied volatility index pairs, namely, the S&P 500 and the VIX, the DAX 100 and the V1XI, and the N225 and the JNIV. The empirical results support the leverage hypothesis relative to the volatility feedback hypothesis for the pairs S&P 500 and VIX, and N225 and JNIV, and the representativeness and affect heuristics hypothesis relative to the leverage hypothesis for the pairs DAX 100 and V1XI, and N225 and JNIV.
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References
Bai, J., & Perron, P. (2003). Computation and analysis of multiple structural change models. Journal of Applied Econometrics, 18, 1–22.
Black, F. (1976). Studies of Stock Market Volatility Changes. Proceedings of the American Statistical Association, Business and Economic Statistics Section, 177–181.
Bollerslev, T., Litvinova, J., & Tauchen, G. (2006). Leverage and Volatility Feedback Effects in High-Frequency Data. Journal of Financial Econometrics, 4, 353–384.
Campbell, J. Y., & Hentschel, L. (1992). No news is good news: An asymmetric model of changing volatility in stock returns. Journal of Financial Economics, 31, 281–318.
Chiang, S.-M. (2012). The Relationships between Implied Volatility Indexes and Spot Indexes. Procedia - Social and Behavioral Sciences, 57, 231–235.
Christie, A. A. (1982). The stochastic behavior of common stock variances: Value, leverage and interest rate effects. Journal of Financial Economics, 10, 407–432.
Creamer, G. G., & Creamer, B. (2016). A non-linear lead-lag dependence analysis energy futures: oil, coal and natural gas. In Florescu, I., Mariani, M., Stanley, E., and Viens, F. (Eds) "Handbook of high-frequency trading and modelling in finance". Chapter 3, pp. 61-71. John Wiley & Sons inc.
French, K. R., Schwert, G. W., & Stambaugh, R. F. (1987). Expected stock returns and volatility. Journal of Financial Economics, 19, 3–29.
Giot, P. (2005). Relationships Between Implied Volatility Indexes and Stock Index Returns. The Journal of Portfolio Management, 31, 92–100.
Hibbert, A. M., Daigler, R. T., & Dupoyet, B. (2008). A behavioral explanation for the negative asymmetric return–volatility relation. Journal of Banking & Finance, 32, 2254–2266.
Rizzo, M. L., & Szekely, G. J. (2017). energy: E-Statistics: Multivariate Inference via the Energy of Data. Retrieved from https://cran.r-project.org/package=energy
Szekely, G. J., & Rizzo, M. L. (2013). Energy statistics: A class of statistics based on distances. Journal of Statistical Planning and Inference, 143, 1249–1272.
Szekely, G. J., Rizzo, M. L., & Bakirov, N. K. (2007). Measuring and testing dependence by correlation of distances. The Annals of Statistics, 35, 2769–2794.
Whaley, R. E. (1993). Derivatives on Market Volatility: Hedging Tools Long Overdue. The Journal of Derivatives, 1, 71–84.
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