performing computations in these models. This paper develops, analyzes, and evaluates two simulation algorithms for intensity … Zeevi, stochastic models and simulation.</i> …Dynamic, intensity-based point process models are widely used to measure and price the correlated default risk in …

, as is common in the literature. <i>This paper was accepted by Assaf Zeevi, stochastic models and simulation.</i> …Sequential sampling problems arise in stochastic simulation and many other applications. Sampling is used to infer the …

accepted by Assaf Zeevi, stochastic models and simulation.</i> … below and above the hole, but not at the hole itself. We show that if the prior probability the product has high quality and …

We integrate a case-based model of probability judgment with prospect theory to explore asset pricing under uncertainty …. Research within the "heuristics and biases" tradition suggests that probability judgments respond primarily to case … framework's predictions, distinct patterns of miscalibration are found for buying prices, selling prices, and probability …

accepted by Gérard P. Cachon, stochastic models and simulation.</i> …

No-arbitrage models are extremely flexible modelling tools but often lack economic motivation. This paper describes an … equilibrium pricing formulas while maintaining the same flexibility of state dynamics as in no-arbitrage models. In demonstrating …

The "gambler's fallacy" is the belief that the probability of an event is lowered when that event has recently occurred …, even though the probability of the event is objectively known to be independent from one trial to the next. This paper …