this paper the value of the option (i.e. the supremum in (1.2)) will be found exactly, and in particular it will be shown that the maximum in (1.2) is finite if and only if r ? ¯ : (1.4) Assuming (1.4), an explicit formula is given for both the maximal expected present value and the optimal stopping rule in (2.4), which is not a fixed time rule but depends heavily on the observed values of X t and S t . We call the financial option described above a "Russian option" for two reasons. First, this name serves to (facetiously) differentiate it from American and European options, which have been extensively studied in financial economics, especially with the new interest in market economics in Russia. Second, our solution of the stopping problem (1.2) is derived by the so-called principle of smooth fit, first enunciated by the great Russian mathematician, A. N. Kolmogorov, cf. [4, 5]. The Russian option is characterized by "reduced regret" because the owner is paid the maximum stock price up to the time of exercise and hence feels less remorse at not having exercised at the maximum. For purposes of comparison and to emphasize the mathematical nature of the contribution here, we conclude the paper by analyzing an optimal stopping problem for the Russian option based on Bachelier's (1900) original linear model of stock price fluctuations, X

A firm whose net earnings are uncertain, and that is subject to the risk of bankruptcy, must choose between paying dividends and retaining earnings in a liquid reserve. Also, different operating strategies imply different combinations of expected return and variance. We model the firm's cash reserve as the difference between the cumulative net earnings and the cumulative dividends. The first is a diffusion (additive), whose drift/volatility pair is chosen dynamically from a finite set, A. The second is an arbitrary nondecreasing process, chosen by the firm. The firm's strategy must be nonclairvoyant. The firm is bankrupt at the first time, T , at which the cash reserve falls to zero (T may be infinite), and the firm's objective is to maximize the expected total discounted dividends from 0 to T , given an initial reserve, x; denote this maximum by V (x). We calculate V explicitly, as a function of the set A and the discount rate. The optimal policy has the form: (1) pay no dividends if ...

Let B = (Bt)0 t 1 be a standard Brownian motion started at zero, let 0 be given and fixed, and let G: [0; 1]2IR! IR be a measurable function. Consider the optimal stopping problem:

The Wiener disorder problem seeks to determine a stopping time which is as close as possible to the (unknown) time of ’disorder ’ when the drift of an observed Wiener process changes from one value to another. In this paper we present a solution of the Wiener disorder problem when the horizon is finite. The method of proof is based on reducing the initial problem to a parabolic free-boundary problem where the continuation region is determined by a continuous curved boundary. By means of the change-of-variable formula containing the local time of a diffusion process on curves we show that the optimal boundary can be characterized as a unique solution of the nonlinear integral equation. 1.

The free-boundary and the martingale approach are competitive methods of solving discounted optimal stopping problems for one-dimensional time-homogeneous regular diffusion processes on infinite time intervals. We provide a missing link showing the equivalence of these approaches for a problem, where the optimal stopping time is equal to the first exit time of the underlying process from a region restricted by two constant boundaries. We also consider several illustrating examples including the rational valuation of the perpetual American strangle option. 1

A large class of continuous time optimal stopping problems is shown to have solutions explicitly determined by roots of equations xH(x) = I where H involves Laplace transforms. These results motivate the specification of discrete time optimal stopping problems whose solutions are approximated by solutions to corresponding continuous time problems, making rigorous a procedure sometimes employed in the literature. A fairly self-contained treatment of continuous time optimal stopping is also included, albeit for highly structured situations.

right time to sell a stock

We present a solution of the Bayesian problem of sequential testing of two simple hypotheses about the mean value of an observed Wiener process on the time interval with finite horizon. The method of proof is based on reducing the initial optimal stopping problem to a parabolic free-boundary problem where the continuation region is determined by two continuous curved boundaries. By means of the change-of-variable formula containing the local time of a diffusion process on curves we show that the optimal boundaries can be characterized as a unique solution of the coupled system of two nonlinear integral equations. 1.

Denmark Denne afhandling er, i forbindelse med de nedenfor anførte, tidligere offentliggjorte afhandlinger, af Det naturvidenskabelige Fakultet ved Aarhus Universitet antaget til forsvar for den naturvidenskabelige doktorgrad. Forsvarshandlingen finder sted fredag den 12. april 2002 kl. 13.15 i Auditorium F p˚a Institut for Matematiske Fag, Aarhus Universitet.

We study the existence theory for parabolic variational inequalities in weighted L 2 spaces with respect to excessive measures associated with a transition semigroup. We characterize the value function of optimal stopping problems for finite and infinite dimensional diffusions as a generalized solution of such a variational inequality. The weighted L 2 setting allows us to cover some singular cases, such as optimal stopping for stochastic equations with degenerate diffusion coefficient. As an application of the theory, we consider the pricing of American-style contingent claims. Among others, we treat the cases of assets with stochastic volatility and with path-dependent payoffs.