We examine the pricing performance of VIX option models. Such models possess a wide-range of underlying characteristics regarding the behavior of both the S&P500 index and the underlying VIX. Our contention that “simpler is better” is supported by the empirical evidence using actual VIX option market data. Our tests employ three representative models for VIX options: Whaley (1993), Grunbichler and Longstaff (1996), and Carr and Lee (2007). We also compare our results to Lin and Chang (2009), who test four stochastic volatility models, as well as to previous simulation results of VIX option models. We find that no model has small pricing errors over the entire range of strike prices and times to expiration. In particular, out-of-the-money VIX options are difficult to price, with Grunbichler and Longstaff’s mean-reverting model producing the smallest dollar errors in this category. In general, Whaley’s Black-like option model produces the best overall results, supporting the “simpler is better” contention. However, the Whaley model does under/overprice out-of-the-money call/put VIX options, which is opposite the behavior of stock index option pricing models.

We explore the effects of fat tails on the equilibrium implications of the long run risks model of asset pricing by introducing innovations with dampened power law to consumption and dividends growth processes. We estimate the structural parameters of the proposed model by maximum likelihood. We find that the homoskedastic model with fat tails leads to significant increase in implied risk premia and volatility of price-dividend ratio over the benchmark Gaussian model, but similar volatility of market
return, expected risk free rate and its volatility.