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This study contributes to the valuation of employee stock options (ESO) in two ways: First, a new pricing model is presented, admitting a major part of calculations to be solved in closed form. Designed with a focus on good replication of empirics, the model fits with publicly observable exercise characteristics better than earlier models. In particular, it is able to account for the correlation of the time of exercise and the stock price at exercise, suspected of being crucial for the option value. The impact of correlation is weak, however, whereas cancellations play a central role. The second contribution of this paper is an examination to what extent the ESO pricing method of SFAS 123 is subject to discretion of the accountant. Given my model were true, the SFAS price would be a good proxy. Yet, outside shareholders usually cannot observe one of the SFAS input parameters. On behalf of an example I show that there is wide latitude left to the accountant.
This study contributes to the valuation of employee stock options (ESO) in two ways: First, a new pricing model is presented, admitting a major part of calculations to be solved in closed form. Designed with a focus on good replication of empirics, the model fits with publicly observable exercise characteristics better than earlier models. In particular, it is able to account for the correlation of the time of exercise and the stock price at exercise, suspected of being crucial for the option value. The impact of correlation is weak, however, whereas cancellations play a central role. The second contribution of this paper is an examination to what extent the ESO pricing method of SFAS 123 is subject to discretion of the accountant. Given my model were true, the SFAS price would be a good proxy. Yet, outside shareholders usually cannot observe one of the SFAS input parameters. On behalf of an example I show that there is wide latitude left to the accountant.
This paper determines the cost of employee stock options (ESOs) to shareholders. I present a pricing method that seeks to replicate the empirics of exercise and cancellation as good as possible. In a first step, an intensity-based pricing model of El Karoui and Martellini is adapted to the needs of ESOs. In a second step, I calibrate the model with a regression analysis of exercise rates from the empirical work of Heath, Huddart and Lang. The pricing model thus takes account for all effects captured in the regression. Separate regressions enable me to compare options for top executives with those for subordinates. I find no price differences. The model is also applied to test the precision of the fair value accounting method for ESOs, SFAS 123. Using my model as a reference, the SFAS method results in surprisingly accurate prices.
JEL classification: G13; J33; M41; M52