Numerical algorithms for the efficient pricing of multidimensional discrete-time American and Bermudan options are constructed using regression methods and a new approach for computing upper bounds of the options' price. Using the sample space with payoffs at optimal stopping times, we propose...

We develop a new approach for pricing both continuous-time and discrete-time American options which is based on the fact that any American option is equivalent to a European one with a consumption process involved. This approach admits the construction of an upper bound (a lower bound) on the...

In many industries, managers face the problem of selling a given stock of items by a deadline. We investigate the problem of dynamically pricing such inventories when demand is price sensitive and stochastic and the firm’s objective is to maximize expected revenues. Examples that fit this...

The main result of the paper is a stability theorem for the Snell envelope under convergence in distribution of the underlying processes: more precisely, we prove that if a sequence $(X^n)$ of stochastic processes converges in distribution for the Skorokhod topology to a process $X$ and...

In many industries, managers face the problem of selling a given stock of items by a deadline. We investigate the problem of dynamically pricing such inventories when demand is price sensitive and stochastic and the firm’s objective is to maximize expected revenues. Examples that fit this...

This study deepens the measurement of technical inefficiency in private maize farming in Georgia, applying locally parametric (LP) reg ression method, whicb builds on the stochastic frontier production function approach. Detailed survey data for 221 mixed farms for 1997 are used in the...

This study deepens the measurement of technical inefficiency in private maize farming in Georgia, applying locally parametric (LP) reg ression method, whicb builds on the stochastic frontier production function approach. Detailed survey data for 221 mixed farms for 1997 are used in the...