Does the fear gauge predict downside risk more accurately than econometric models? Evidence from the US stock market

References

• Alexander, C., & Lazar, E. (2006). Normal mixture GARCH(1,1): Applications to exchange rate modelling. Journal of Applied Econometrics, 21, 307–336.10.1002/(ISSN)1099-1255
   Web of Science ®Google Scholar
• Alexander, C., Lazar, E., & Stanescu, S. (2013). Forecasting VaR using analytic higher moments for GARCH processes. International Review of Financial Analysis, 30, 36–45.10.1016/j.irfa.2013.05.006
   Web of Science ®Google Scholar
• Bates, D. S. (2006). Maximum likelihood estimation of latent affine processes. Review of Financial Studies, 19, 909–965.10.1093/rfs/hhj022
   Web of Science ®Google Scholar
• Bates, D. S. (2012). US stock market crash risk, 1926–2010. Journal of Financial Economics, 105, 229–259.10.1016/j.jfineco.2012.03.004
   Web of Science ®Google Scholar
• Bekaert, G., Engstrom, E., & Ermolov, A. (2015). Bad environments, good environments: A non-Gaussian asymmetric volatility model. Journal of Econometrics, 186, 258–275.10.1016/j.jeconom.2014.06.021
   Web of Science ®Google Scholar
• Bekaert, G., & Hoerova, M. (2014). The VIX, the variance premium and stock market volatility. Journal of Econometrics, 183, 181–192.10.1016/j.jeconom.2014.05.008
   Web of Science ®Google Scholar
• Bekaert, G., & Wu, G. (2000). Asymmetric volatility and risk in equity markets. Review of Financial Studies, 13, 1–42.10.1093/rfs/13.1.1
   Web of Science ®Google Scholar
• Berger, D., & Pukthuanthong, K. (2012). Market fragility and international market crashes. Journal of Financial Economics, 105, 565–580.10.1016/j.jfineco.2012.03.009
   Web of Science ®Google Scholar
• Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 31, 307–327.10.1016/0304-4076(86)90063-1
   Web of Science ®Google Scholar
• Bollerslev, T., Engle, R. F., & Wooldridge, J. M. (1988). A capital asset pricing model with time-varying covariances. Journal of Political Economy, 96, 116–131.10.1086/261527
   Web of Science ®Google Scholar
• Cappiello, L., Engle, R. F., & Sheppard, K. (2006). Asymmetric dynamics in the correlations of global equity and bond returns. Journal of Financial Econometrics, 4, 537–572.10.1093/jjfinec/nbl005
   Google Scholar
• Charles, A., & Darné, O. (2005). Outliers and GARCH models in financial data. Economics Letters, 86, 347–352.10.1016/j.econlet.2004.07.019
   Web of Science ®Google Scholar
• Charles, A., & Darné, O. (2014). Large shocks in the volatility of the Dow Jones Industrial Average index: 1928–2013. Journal of Banking and Finance, 43, 188–199.10.1016/j.jbankfin.2014.03.022
   Web of Science ®Google Scholar
• Chesney, M., Reshetar, G., & Karaman, M. (2011). The impact of terrorism on financial markets: An empirical study. Journal of Banking and Finance, 35, 253–267.10.1016/j.jbankfin.2010.07.026
   Web of Science ®Google Scholar
• Chung, S. L., Tsai, W. C., Wang, Y. H., & Weng, P. S. (2011). The information content of the S&P 500 index and VIX options on the dynamics of the S&P 500 index. Journal of Futures Markets, 31, 1170–1201.10.1002/fut.v31.12
   Web of Science ®Google Scholar
• Coudert, V., & Gex, M. (2008). Does risk aversion drive financial crises? Testing the predictive power of empirical indicators. Journal of Empirical Finance, 15, 167–184.10.1016/j.jempfin.2007.06.001
   Web of Science ®Google Scholar
• Ding, Z., Granger, C. W. J., & Engle, R. F. (1993). A long memory property of stock market returns and a new model. Journal of Empirical Finance, 1, 83–106.10.1016/0927-5398(93)90006-D
   Google Scholar
• Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50, 987–1007.10.2307/1912773
   Web of Science ®Google Scholar
• Engle, R. F. (2002). Dynamic conditional correlation: A simple class of multivariate generalized autoregressive conditional heteroskedasticity models. Journal of Business and Economic Statistics, 20, 339–350.10.1198/073500102288618487
   Web of Science ®Google Scholar
• Engle, R. F., & Kroner, K. F. (1995). Multivariate simultaneous generalized ARCH. Econometric Theory, 11, 122–150.10.1017/S0266466600009063
   Web of Science ®Google Scholar
• Engle, R. F., Lilien, D. M., & Robins, R. P. (1987). Estimating time varying risk premia in the term structure: The arch-M model. Econometrica, 55, 391–407.10.2307/1913242
   Web of Science ®Google Scholar
• Engle, R. F., & Ng, V. K. (1993). Measuring and testing the impact of news on volatility. The Journal of Finance, 48, 1749–1778.10.1111/j.1540-6261.1993.tb05127.x
   Web of Science ®Google Scholar
• Franses, P. H., & Ghijsels, H. (1999). Additive outliers, GARCH and forecasting volatility. International Journal of Forecasting, 15, 1–9.10.1016/S0169-2070(98)00053-3
   Web of Science ®Google Scholar
• Fung, J. K. W. (2007). The information content of option implied volatility surrounding the 1997 Hong Kong stock market crash. Journal of Futures Markets, 27, 555–574.10.1002/(ISSN)1096-9934
   Web of Science ®Google Scholar
• Giot, P. (2005). Relationships between implied volatility indexes and stock index returns. The Journal of Portfolio Management, 31, 92–100.10.3905/jpm.2005.500363
   Web of Science ®Google Scholar
• Glosten, L. R., Jagannathan, R., & Runkle, D. E. (1993). On the relation between the expected value and the volatility of the nominal excess return on stocks. The Journal of Finance, 48, 1779–1801.10.1111/j.1540-6261.1993.tb05128.x
   Web of Science ®Google Scholar
• Huang, W., Liu, Q., Ghon Rhee, S., & Wu, F. (2012). Extreme downside risk and expected stock returns. Journal of Banking and Finance, 36, 1492–1502.10.1016/j.jbankfin.2011.12.014
   Web of Science ®Google Scholar
• Li, W. X., Chen, C. C. S., & French, J. J. (2015). Toward an early warning system of financial crises: What can index futures and options tell us? The Quarterly Review of Economics and Finance, 55, 87–99.10.1016/j.qref.2014.07.004
   Web of Science ®Google Scholar
• Lundblad, C. (2007). The risk return tradeoff in the long run: 1836–2003. Journal of Financial Economics, 85, 123–150.10.1016/j.jfineco.2006.06.003
   Web of Science ®Google Scholar
• Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59, 347–370.10.2307/2938260
   Web of Science ®Google Scholar
• Pukthuanthong, K., & Roll, R. (2009). Global market integration: An alternative measure and its application. Journal of Financial Economics, 94, 214–232.10.1016/j.jfineco.2008.12.004
   Web of Science ®Google Scholar
• Sakata, S., & White, H. (1998). High breakdown point conditional dispersion estimation with application to S&P 500 daily returns volatility. Econometrica, 66, 529–567.10.2307/2998574
   Web of Science ®Google Scholar
• Schwert, G. W. (1990). Stock volatility and the crash of ’87. Review of Financial Studies, 3, 77–102.10.1093/rfs/3.1.77
   Web of Science ®Google Scholar
• Tolikas, K. (2014). Unexpected tails in risk measurement: Some international evidence. Journal of Banking and Finance, 40, 476–493.10.1016/j.jbankfin.2013.07.022
   Web of Science ®Google Scholar
• Wong, W. K. (2010). Backtesting value-at-risk based on tail losses. Journal of Empirical Finance, 17, 526–538.10.1016/j.jempfin.2009.11.004
   Web of Science ®Google Scholar
• Zakoian, J. M. (1994). Threshold heteroskedastic models. Journal of Economic Dynamics and Control, 18, 931–955.10.1016/0165-1889(94)90039-6
   Web of Science ®Google Scholar
• Zhang, X., & King, M. L. (2005). Influence diagnostics in generalized autoregressive conditional heteroscedasticity processes. Journal of Business and Economic Statistics, 23, 118–129.10.1198/073500104000000217
   Web of Science ®Google Scholar