Option Valuation with Conditional Heteroskedasticity and Non-Normality

We provide results for the valuation of European style contingent claims for a large class of specifications of the underlying asset returns. Our valuation results obtain in a discrete time, infinite state-space setup using the no-arbitrage principle and an equivalent martingale measure. Our approach allows for general forms of heteroskedasticity in returns, and valuation results for homoskedastic processes can be obtained as a special case. It also allows for conditional non-normal return innovations, which is critically important because heteroskedasticity alone does not suffice to capture the option smirk. We analyze a class of equivalent martingale measures for which the resulting risk-neutral return dynamics are from the same family of distributions as the physical return dynamics. In this case, our framework nests the valuation results obtained by Duan (1995) and Heston and Nandi (2000) by allowing for a time-varying price of risk and non-normal innovations. We provide extensions of these results to more general equivalent martingale measures and to discrete time stochastic volatility models, and we analyze the relation between our results and those obtained for continuous time models. Nous présentons les résultats d’une étude portant sur l’évaluation de créances éventuelles de style européen pour une grande variété de caractéristiques liées au rendement des actifs sous-jacents. Les résultats de notre évaluation proposent en temps discret une formule état-espace infinie, à partir du principe de non-arbitrage et d’une mesure de martingale équivalente. Notre approche permet de tenir compte de formes générales d’hétéroscédasticité dans les rendements et d’obtenir, dans des cas spéciaux, des résultats d’évaluation liés aux processus homoscédastiques. Elle permet aussi de considérer les innovations conditionnellement non normales en matière de rendement, ce qui représente un facteur critique, compte tenu du fait que l’hétéroscédasticité ne permet pas, à elle seule, de saisir pleinement le caractère ironique de l’option. Nous analysons une catégorie de mesures de martingale équivalentes dont la dynamique du rendement risque-neutre obtenu est de la même famille de distribution que la dynamique du rendement physique. Dans ce cas, notre cadre d’étude soutient les résultats d’évaluation obtenus par Duan (1995) et par Heston et Nandi (2000) et tient compte du coût du risque variant dans le temps et des innovations non normales. Nous étendons ces résultats aux mesures de martingale équivalentes plus générales et aux modèles de volatilité stochastique en temps discret et analysons aussi la relation entre nos résultats et ceux obtenus dans le cas des modèles en temps continu.GARCH, risk-neutral valuation, no-arbitrage, non-normal innovations, GARCH (hétéroscédasticité conditionnelle autorégressive généralisée), évaluation du risque neutre, absence d’arbitrage, innovations non normales

Structural The Equity Premium and the Volatility Spread: The Role of Risk-Neutral Skewness

We introduce the Homoscedastic Gamma [HG] model where the distribution of returns is characterized by its mean, variance and an independent skewness parameter under both measures. The model predicts that the spread between historical and risk-neutral volatilities is a function of the risk premium and of skewness. In fact, the equity premium is twice the ratio of the volatility spread to skewness. We measure skewness from option prices and test these predictions. We find that conditioning on skewness increases the predictive power of the volatility spread and that coefficient estimates accord with theory. In short, the data do not reject the model's implications for the equity premium. We also check the model's implications for option pricing and show that the information content of skewness leads to improved in-sample and out-of-sample pricing performances as well as improved hedging performances. Our results imply that expanding around the Gaussian density is restrictive and does not offer sufficient flexibility to match the skewness and kurtosis implicit in option data. Finally, we document the term structure of option-implied volatility, skewness and kurtosis and find that time-dependence in returns has a greater impact on skewness.Financial markets

Affine and generalized affine models : Theory and applications

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Risk premium, variance premium and the maturity structure of uncertainty

Theoretical risk factors underlying time-variations of risk premium across asset classes are typically unobservable or hard to measure by construction. Important examples include risk factors in Long Run Risk [LRR] structural models (Bansal and Yaron 2004) as well as stochastic volatility or jump intensities in reduced-form affine representations of stock returns (Duffie, Pan, and Singleton 2000). Still, we show that both classes of models predict that the term structure of risk-neutral variance should reveal these risk factors. Empirically, we use model-free measures and construct the ex-ante variance term structure from option prices. This reveals (spans) two risk factors that predict the bond premium and the equity premium, jointly. Moreover, we find that the same risk factors also predict the variance premium. This important contribution is consistent with theory and confirms that a small number of factors underlies common time-variations in the bond premium, the equity premium and the variance premium. Theory predicts that the term structure of higher-order risks can reveal the same factors. This is confirmed in the data. Strikingly, combining the information from the variance, skewness and kurtosis term structure can be summarized by two risk factors and yields similar level of predictability (i.e., R2s). This bodes well for our ability to bridge the gap between the macro-finance literature, which uses very few state variables, and valuations in option markets