TL;DR: This article developed a closed-form option valuation formula for a spot asset whose variance follows a GARCH(p, q) process that can be correlated with the returns of the spot asset.
Abstract: This paper develops a closed-form option valuation formula for a spot asset whose variance follows a GARCH(p, q) process that can be correlated with the returns of the spot asset. It provides the first readily computed option formula for a random volatility model that can be estimated and implemented solely on the basis of observables. The single lag version of this model contains Heston's (1993) stochastic volatility model as a continuous-time limit. Empirical analysis on S&P500 index options shows that the out-of-sample valuation errors from the single lag version of the GARCH model are substantially lower than the ad hoc Black-Scholes model of Dumas, Fleming and Whaley (1998) that uses a separate implied volatility for each option to fit to the smirk/smile in implied volatilities. The GARCH model remains superior even though the parameters of the GARCH model are held constant and volatility is filtered from the history of asset prices while the ad hoc Black-Scholes model is updated every period. The improvement is largely due to the ability of the GARCH model to simultaneously capture the correlation of volatility, with spot returns and the path dependence in volatility. Article published by Oxford University Press on behalf of the Society for Financial Studies in its journal, The Review of Financial Studies.
TL;DR: In this paper, the authors model the demand-pressure effect on prices when options cannot be perfectly hedged and show that demand pressure in one option contract increases its price by an amount proportional to the variance of the unhedgeable part of the option.
Abstract: We model the demand-pressure effect on prices when options cannot be perfectly hedged. The model shows that demand pressure in one option contract increases its price by an amount proportional to the variance of the unhedgeable part of the option. Similarly, the demand pressure increases the price of any other option by an amount proportional to the covariance of their unhedgeable parts. Empirically, we identify aggregate positions of dealers and end users using a unique dataset, and show that demand-pressure effects help explain well-known option-pricing puzzles. First, end users are net long index options, especially outof-money puts, which helps explain their apparent expensiveness and the smirk. Second, demand patterns help explain the cross section of prices and skews of single-stock options.
TL;DR: The shape of the volatility smirk has significant cross-sectional predictive power for future equity returns as mentioned in this paper, and firms with the steepest volatility smirks are those experiencing the worst earnings shocks in the following quarter.
Abstract: The shape of the volatility smirk has significant cross-sectional predictive power for future equity returns. Stocks exhibiting the steepest smirks in their traded options underperform stocks with the least pronounced volatility smirks in their options by 10.9% per year on a risk-adjusted basis. This predictability persists for at least 6 months, and firms with the steepest volatility smirks are those experiencing the worst earnings shocks in the following quarter. The results are consistent with the notion that informed traders with negative news prefer to trade out-of-the-money put options, and that the equity market is slow in incorporating the information embedded in volatility smirks.
TL;DR: In this article, the implied volatility smirk does not flatten out as maturity increases up to the observable horizon of two years, and a parsimonious model was developed to capture the observed behavior of the volatilitysmirk over the maturity horizon.
Abstract: We document a surprising pattern in S&P 500 option prices. When implied volatilities are graphed against a standard measure of moneyness, the implied volatility smirk does not flatten out as maturity increases up to the observable horizon of two years. This behavior contrasts sharply with the implications of many pricing models and with the asymptotic behavior implied by the central limit theorem (CLT). We develop a parsimonious model which deliberately violates the CLT assumptions and thus captures the observed behavior of the volatility smirk over the maturity horizon. Calibration exercises demonstrate its superior performance against several widely used alternatives.
TL;DR: In this paper, the authors model the demand-pressure effect on prices when options cannot be perfectly hedged and show that demand pressure in one option contract increases its price by an amount proportional to the variance of the unhedgeable part of the option.
Abstract: We model the demand-pressure effect on prices when options cannot be perfectly hedged. The model shows that demand pressure in one option contract increases its price by an amount proportional to the variance of the unhedgeable part of the option. Similarly, the demand pressure increases the price of any other option by an amount proportional to the covariance of their unhedgeable parts. Empirically, we identify aggregate positions of dealers and end users using a unique dataset, and show that demand-pressure effects help explain well-known option-pricing puzzles. First, end users are net long index options, especially out-of-money puts, which helps explain their apparent expensiveness and the smirk. Second, demand patterns help explain the cross section of prices and skews of single-stock options.