We study a two-stage purchase contract with a demand forecast update. The purchase contract provides the buyer an opportunity to adjust an initial commitment based on an updated demand forecast obtained at a later stage. An adjustment, if any, incurs a fixed as well as a variable cost. Using a...

This paper addresses the long-standing question of whether asset prices are predictable. The common view holds that daily prices fully incorporate all available information, and therefore price changes are unforecastable. This conclusion does not necessarily hold when the vast bulk of market...

This paper address the long-standing question of whether asset prices are predictable. The common view holds that daily prices fully incorporate all available information, and therefore price changes are unforecastable. This conclusion does not necessarily hold when the vast bulk of market...

You're probably familiar, at least in passing, with the 'convexity' of long-term bonds - i.e. that yields dropping 1% produce a bigger price move than yields rising 1%. A significant amount of brainpower has gone into understanding all the ramifications of this convexity in the fixed income...

We develop an adaptive learning game to rethink efficient markets. We use the stochastically stable state of this game, which is a mixed Nash equilibrium, to form an adaptive expectation model that provides an estimate of the confidence interval for prices on the next day. The estimate is most...

Classic artificial intelligence (Q-learning) algorithms have been capable of consistently learning supra-competitive pricing strategies in infinitely repeated Nash-Bertrand pricing games without human communication. Such algorithms have been able to converge due to the temporal correlation of...

Game-theoretic models of learning are hard to study even in the laboratory setting due to econometric and practical concerns (like the limited length of an experimental session).In particular, as the simulations by (Salmon, 2001) show, in a cross-model (or "blind'') testing of several models,...

Consider a finite-state stochastic process governed by an unknown objective probability distribution. Observing the system, a forecaster assigns subjective probabilities to future states. The resulting subjective forecast merges to the objective distribution if, with time, the forecasted...