activity
20222026
most citedStopping problems with an unknown state

1 citations · 1 across the 6 of their papers we have counts for

collaborators

7 papers

math.ST2026

Convex order and preservation of convexity for Bayesian posterior updates

Erhan Bayraktar, Yuqiong Wang

We study how the response of a Bayesian posterior statistic to future observations changes as information accumulates. For a non-decreasing function , define $Π_n^T=\E[T(Θ)\vert…

math.OC2026

Tractable bank capital structure: optimal control under Basel III constraints

Erhan Bayraktar, Etienne Chevalier, Vathana Ly Vath +1

Banks must optimize risky investments, dividend payouts, and capital structure under tight Basel III solvency and liquidity constraints, while costly equity issuance serves as a di…

math.ST2026

The relative efficiency of sequential tests

Henri Doerks, Erik Ekström, Yuqiong Wang

While many statistical procedures rely on a fixed sample size, sequential methods allow a decision-maker to adapt the sample size to achieve a given precision. In this way, sequent…

math.OC2026

Thompson Sampling Algorithm for Stochastic Games

Asaf Cohen, Ruolan He, Yuqiong Wang

We study a stochastic differential game with competitive players in a linear-quadratic framework with ergodic cost, where -dimensional diffusion processes govern the state d…

math.ST2025

On hypoellipticity of degenerate operators in testing and detection problems

Erhan Bayraktar, Yuqiong Wang

We study a class of degenerate diffusion generators arising in sequential testing and quickest detection problems with partial information. The observation process is driven by …

math.PR2024

Dynkin ghost games with asymmetry and consolation

Erik Ekström, Yuqiong Wang

We study a stopping game of preemption type between two players who both act under uncertain competition. In this framework we introduce, and study the effect of, (i) asymmetry of…

math.PR2022★ 1 cited

Stopping problems with an unknown state

Erik Ekström, Yuqiong Wang

We extend the classical setting of an optimal stopping problem under full information to include for problems with an unknown state. The framework allows the unknown state to influ…