Predictable Dynamics in the S&P 500 Index Options Implied Volatility Surface
By Sílvia Gonçalves, Massimo Guidolin. 2005
137 citations recorded by the source corpus.
One key stylized fact in the empirical option pricing literature is the existence of an implied volatility surface (IVS). The usual approach consists of fitting a linear model linking the implied volatility to the time to maturity and the moneyness, for each cross section of options data. However, recent empirical evidence suggests that the parameters characterizing the IVS change over time. In this paper we study whether the resulting predictability patterns in the IVS coefficients may be exploited in practice. We propose a two-stage approach to modeling and forecasting the S&P 500 index options IVS. In the first stage we model the surface along the cross-sectional moneyness and time-to-maturity dimensions, similarly to Dumas et al. (1998). In the second-stage we model the dynamics of the cross-sectional first-stage implied volatility surface coefficients by means of vector autoregression models. We find that not only the S&P 500 implied volatility surface can be successfully modeled, but also that its movements over time are highly predictable in a statistical sense. We then examine the economic significance of this statistical predictability with mixed findings. Whereas profitable delta-hedged positions can be set up that exploit the dynamics captured by the model under moderate transaction costs and when trading rules are selective in terms of expected gains from the trades, most of this profitability disappears when we increase the level of transaction costs and trade multiple contracts off wide segments of the IVS. This suggests that predictability of the time-varying S&P 500 implied volatility surface may be not inconsistent with market efficiency.
Subfields: Finance
View Paper: https://www.semanticscholar.org/paper/0670b3da9268439064d97d135eb383fb9f6c1955
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Citations in the corpus
- Can the evolution of implied volatility be forecasted? Evidence from European and US implied volatility indices (2008, methodology): “However, their results are not economically significant just as in Gonçalves and Guidolin (2006).”
- Convolutional autoregressive models for functional time series (2016, unknown): “Many empirical results show that the implied volatility curves are unit-root-nonstationary (Fengler et al., 2005; Goncalves and Guidolin, 2006; Lam et al., 2011).”