We examine the forecast quality of Chicago Board Options Exchange (CBOE) implied volatility indexes based on the Standard and Poor's 100 and Nasdaq 100 stock indexes. We find that the forecast quality of CBOE implied volatilities for the Samp;P 100 (VIX) has significantly improved in recent...

The generalized lambda distribution is proposed as a useful model for security price distributions. Originally used to generate random variables with varied skewness and kurtosis values in Monte Carlo simulations, proposed financial applications include estimation of state price densities from...

We investigate the effectiveness of several well-known parametric and nonparametric event study test statistics with security price data from the major Asia-Pacific security markets. Extensive Monte Carlo simulation experiments with actual daily security returns data reveal that the parametric...

A hidden martingale restriction is developed for option pricing models based on Gram-Charlier expansions of the normal density function. The restriction is hidden behind a reduction in parameter space for the Gram-Charlier expansion coefficients. The resulting restriction is invisible in the...

The academic literature generally concludes that the Black-Scholes model overstates the value of employee stock options (ESOs). In particular, because ESOs cannot be traded, employee risk aversion often elicits premature exercise. As a result, the ESO is less valuable than a traded option. An...

Examination of 871 takeover rumors published in two columns of the Wall Street Journal during 1985 through 1988 reveals that the market reacts differently to reports on the same page of the Journal. Rumors in the quot;Abreast of the Marketquot; column are associated with short-term...

This paper evaluates a nonparametric sign test for abnormal security price performance in event studies. The sign test statistic examined here does not require a symmetrical distribution of security excess returns for correct specification. Sign test performance is compared to a parametric...