The quadratic form of the covariance-co-skewness model by Kraus and Litzenberger and arbitrage pricing theory are used for an empirical investigation of market equilibrium with skewed seecurity returns. Empirical tests similar to the ones in Black-Jensen-Scholes and Gibbons are discussed. The empirical estimates give some support to the Kraus-Litzenberger hypothesis on skewness preference. However, there is some evidence that the tested arbitrage equilibrium is not a complete description of security pricing.

The American put is one of the oldest problems in mathematical finance. We review the development of the relevant literature over the last 40years. Today the mainstream computational problems have been solved satisfactorily and the target of research is shifting towards the development of further insights into the value of timing investment decisions.

[We propose a new method for pricing options based on GARCH models with filtered historical innovations. In an incomplete market framework, we allow for different distributions of historical and pricing return dynamics, which enhances the model's flexibility to fit market option prices. An extensive empirical analysis based on S&P 500 index options shows that our model outperforms other competing GARCH pricing models and ad hoc Black-Scholes models. We show that the flexible change of measure, the asymmetric GARCH volatility, and the nonparametric innovation distribution induce the accurate pricing performance of our model. Using a nonparametric approach, we obtain decreasing state-price densities per unit probability as suggested by economic theory and corroborating our GARCH pricing model. Implied volatility smiles appear to be explained by asymmetric volatility and negative skewness of filtered historical innovations.]

The estimation and forecast of the volatility matrix are two of the main tasks of financial econometrics since they are essential ingredients in many practical applications. Unfortunately the use of classical multivariate methods in large dimensions is difficult because of the curse of dimensionality. We present a general semiparametric technique, based on functional gradient descent (FGD) and able to overcome most problems associated with a multivariate GARCH-type estimation. By testing the accuracy of the volatility estimates for the measurement of market risk on real data we provide empirical evidence of the strong predictive potential of the FGD approach, also in comparison to other standard methods.

This study focuses on the ex-dividend stock price decline implicit within the valuation of American call options on dividend-paying stocks. The Roll (1977) American call option pricing formula and the observed structure of CBOE call option transaction prices are used to infer the expected ex-dividend stock price decline as a proportion of the amount of the dividend. The relative decline is shown to be not meaningfully different from one, confirming some recent evidence from studies which examined stock prices in the days surrounding ex-dividend.

This paper provides simple, analytic approximations for pricing exchange-traded American call and put options written on commodities and commodity futures contracts. These approximations are accurate and considerably more computationally efficient than finite-difference, binomial, or compound-option pricing methods.

This paper provides simple, analytic approximations for pricing exchange‐traded American call and put options written on commodities and commodity futures contracts. These approximations are accurate and considerably more computationally efficient than finite‐difference, binomial, or compound‐option pricing methods.

Seha M. Tinic, Giovanni Barone-Adesi, Richard R. West, Seasonality in Canadian Stock Prices: A Test of the "Tax-Loss-Selling" Hypothesis, The Journal of Financial and Quantitative Analysis, Vol. 22, No. 1 (Mar., 1987), pp. 51-63