Forecasting VIX: the illusion of forecast evaluation criteria

Authors

  • Eleftheria Kafousaki Panteion University of Social and Political Sciences, Department of Economic and Regional Development, Syggrou Avenue 136, GR176721 Athens, Greece
  • Stavros Degiannakis Panteion University of Social and Political Sciences, Department of Economic and Regional Development, Greece

DOI:

https://doi.org/10.17811/ebl.12.3.2023.231-240

Keywords:

Implied volatility forecasting, realized volatility measures, objective-based evaluation criteria

Abstract

The study uses daily realized volatility measures in order to gain forecast accuracy over stocks’ market implied volatility, as proxied by VIX Index. We evaluate forecast accuracy by incorporating a traditional statistical loss function, along with an objective-based evaluation criterion, that is the cumulative returns earned from the different HAR-type volatility models, through a simple yet effective trading exercise on VIX futures. Findings, illustrate how illusive the choice between the two metrics may be, as it ends in two contradicting results.

References

Andersen, T. G., and Bollerslev, T. (1998) Answering the skeptics: yes, standard volatility models do provide accurate forecasts, International Economic Review, 39, 885–905.

Andersen, T. G., Bollerslev, T. and Meddahi, N. (2005) Correcting the errors: volatility forecast evaluation using high-frequency data and realized volatilities, Econometrica, 73 (1), 279–296.

Andersen, T. G., Fusari, N. and Todorov, V. (2015) Parametric inference and dynamic state recovery from options panels, Econometrica, 83, 1081-1145

Bakshi, G., and Madan, D. (2006) A theory of volatility spreads, Management Science, 52(12), 1945-1956.

Barndorff-Nielsen, O. E., Hansen, P.R., Lunde, A. and Shephard, N. (2008) Designing realized kernels to measure the ex-post variation of equity prices in the presence of noise, Econometrica, 76 (6), 1481–1536.

Barndorff-Nielsen, O.E., Hansen, P.R., Lunde, A. and Shephard, N. (2011) Subsampling realized kernels, Journal of Econometrics, 160 (1), 204–219.

Barndorff-Nielsen, O.E. and Shephard, N. (2002) Estimating Quadratic Variation Using Realized Variance, Journal of Applied Econometrics, 17, 457-477.

Bevilacqua, M., Morelli, D. and Tunaru, R. (2018) The Determinants of the Model-Free Positive and Negative Volatilities, Journal of International Money and Finance, 92, 1-24.

Birkelund, O., Haugom, Ε., Molnár, P., Opdal, M., and Westgaard, S. (2015) A comparison of implied and realized volatility in the Nordic power forward market, Energy Economics, 48, 288-294.

Black, K. and Szado, E. (2016)” Performance Analysis of options-based equity Mutual Funds, Closed-End Funds, and Exchange-Traded Funds”, Journal of Wealth Management, 19(1), 51-69.

Bollerslev, T., Gibson, M. and Zhou, H. (2011) Dynamic Estimation of Volatility Risk Premia and Investor Risk Aversion from Option-Implied and Realized Volatilities, CREATES Research Paper.

Bollerslev, T., Tauchen, G., and Zhou, H. (2009) Expected stock returns and variance risk premia, Review of Financial Studies, 22(11), 4463–4492.

Bollerslev, T. and Todorov, V. (2011) Tails, Fears and risk premia, Journal of Finance, 66, 2165-2211.

Busch, T., Christensen, B. J., and Nielsen, M. Ø. (2011) The role of implied volatility in forecasting future realized volatility and jumps in foreign exchange, stock, and bond markets. Journal of Econometrics, 160 (1), 48–57.

Carr, P. and Wu, L. (2008) Variance risk premiums, Review of Financial Studies, 22(3), 1311–1341.

Christensen, B. J. and Prabhala, N. R. (1998) The relation between implied and realized volatility, Journal of Financial Economics, 50, 125–150.

Corsi, F. (2009) A simple approximate long-memory model of realized volatility, Journal of Financial Econometrics, 7(2), 174–196.

Corsi, F. and Reno, R. (2012) Discrete-time volatility forecasting with persistent leverage effect and the link with continuous-time volatility modeling, Journal of Business & Economic Statistics, 30(3), 368–380.

Degiannakis, S. and Filis, G. (2017) Forecasting oil price realized volatility using information channels from other asset classes, Journal of International Money and Finance, 76, 28–49.

Degiannakis, S. and Filis, G. (2020) Oil price assumptions for macroeconomic policy, MPRA Paper 100705, University Library of Munich, Germany.

Degiannakis, S. and Filis G. (2022) Oil price volatility forecasts: What do investors need to know?, Journal of International Money and Finance, 18(5), 449–465.

Degiannakis, S., Filis, G., Klein, T. and Walther, T. (2022) Forecasting Realized Volatility of Agricultural Commodities, International Journal of Forecasting, 38(1), 74-96.

Delis, P., Degiannakis, S. and Giannopoulos, C. (2023) What should be taken into consideration when Forecasting Oil Implied Volatility Index?, Energy Journal, 44(5), forthcoming.

Hansen, P. R. and Lunde, A. (2006) Realized variance and market microstructure noise, Journal of Business and Economic Statistics, 24(2), 127–161.

Hansen, P. R., Lunde, A. and Nason, J. M. (2011) “The model confidence Set”, Econometrica, 79(2), 453-497.

He, D. X., Usu, C. J. and Rue, N. (2015) Option-Writing Strategies in a Low Volatility Framework, Journal of Investing, 24(3), 116-28.

Liu, Y. L., Patton, J. A. and Sheppard, K. (2015) Does anything beat 5-minute RV? A comparison of realized measures across multiple asset classes, Journal of Econometrics, 187, 293-311.

Moran, M. T. and Dash, S. (2007) VIX Futures and Options: Pricing and Using Volatility Products to Manage Downside Risk and Improve Efficiency in Equity Portfolios, The Journal of Trading, 2(3), 96 - 105.

Szado, E. (2018) “The Distinctive Characteristics of VIX Futures and Options,” Working Paper.

Todorov, V. (2010) Variance risk-premium dynamics: The role of Financial Studies, The Review of Financial Studies, 23, 345-383.

Downloads

Published

09-10-2023

How to Cite

Kafousaki, E., & Degiannakis, S. (2023). Forecasting VIX: the illusion of forecast evaluation criteria. Economics and Business Letters, 12(3), 231–240. https://doi.org/10.17811/ebl.12.3.2023.231-240