It will be convenient to consider in detail one specific form of security option: common stock purchase warrants. The model to be constructed can be extended mutatis mutanidis to any convertible security; Section 4 explicitly relates the model of warrant price to convertible bond price. A common stock purchase warrant is a security which the holder may exchange, at his option, for equity capital. The exchange may be effected by surrendering the warrant and a prespecified sum of money before a prespecified date to the corporation issuing the common stock. The act of conversion is usually called the exercise of the warrant, and the accompanying money the exercise price. Let X be the price of a unit of common, let Y be the price of a warrant, and let A be the exercise price of Y. For the remainder of this study, we shall measure X and Y in units of A so that Y/A = y is the price of 1/A warrants and X/A = x is the price of 1/A common shares. In this way, y plus $1 can be converted into shares

A mixed model of regression with error components is proposed as one of possible interest for combining cross section and time series data. For known variances, it is shown that Aitken estimators and covariance estimators are in one sense asymptotically equivalent, even though the Aitken estimators are more efficient in small samples. Turning to unknown variance components, Zellner-type iterative estimators are compared with covariance estimators. Here, few small sample properties are obtained. However, it is shown that covariance and Zellner-type estimators have equivalent asymptotic distributions and equivalent limits of sequences of first and second order moments for weakly nonstochastic regressors. For the model analyzed, the theoretical results obtained, as well as ease of computation, tend to support traditional covariance estimators of the regression parameters. An additional interesting result presented in an appendix is that ordinary least squares estimates of the fl's (ignoring the error components) have unbounded asymptotic variances. On efficiency grounds, this argues rather strongly for some care in combining data from alternative sources in regression analysis.