I introduce and study dynamic persuasion mechanisms. A principal privately observes the evolution of a stochastic process and sends messages over time to an agent. The agent takes actions in each period based on her beliefs about the state of the process and the principal wishes to influence the agent’s action. I characterize the optimal persuasion mechanism and apply it to some examples.

The underlying assumption for using seasonal dummies in a regression is that the seasonality of the dependent variable is deterministic. Many economic variables show a regular seasonal pattern, with peaks occuring in the same season year after year. Such a regular seasonal pattern can also be a result of an integrated stochastic process. This paper examines some consequences of deterministic mo...

We consider a model for systems perturbed by dichotomous noise, in which the hazard rate function of a random lifetime is subject to additive time-alternating perturbations described by the telegraph process. This leads us to define a real-valued continuous-time stochastic process of alternating type expressed in terms of the integrated telegraph process for which we obtain the probability dist...

We prove a law of the iterated logarithm for stable processes in a random scenery. The proof relies on the analysis of a new class of stochastic processes which exhibit long-range dependence.

When studying stochastic processes, it is often fruitful to understand several different notions of regularity. One such notion is the optimal Hölder exponent obtainable under reparametrization. In this paper, we show that chordal SLEκ in the unit disk for κ ≤ 4 can be reparametrized to be Hölder continuous of any order up to 1/(1 + κ/8). From this, we obtain that the Young integral is well def...

We prove that partial sums of linear multiparameter stochastic processes can be represented as partial sums of independent innovations plus components that are uniformly of smaller order. This representation is exploited to establish functional central limit theorems and strong approximations for random fields.

The paper considers a particular family of set–valued continuous time stochastic processes modeling birth–and–growth processes. The proposed setting allows us to infer the nucleation and the growth processes. A decomposition theorem is established to characterize the nucleation and the growth. As a logical consequence, different consistent set–valued estimators are studied for growth process. M...

multistage stochastic programming is a key technology for making decisions over time in an uncertain environment. one of the promising areas in which this technology is implementable, is medium term planning of electricity production and trading where decision makers are typically faced with uncertain parameters (such as future demands and market prices) that can be described by stochastic proc...