activity
20072022
most citedM/M/ queues in semi-Markovian random environment

54 citations · 114 across the 18 of their papers we have counts for

collaborators

19 papers

math.PR2022★ 1 cited

Optimal stopping of Gauss-Markov bridges

Abel Azze, Bernardo D'Auria, Eduardo García-Portugués

We solve the non-discounted, finite-horizon optimal stopping problem of a Gauss-Markov bridge by using a time-space transformation approach. The associated optimal stopping boundar…

math.PR2022★ 2 cited

Optimal exercise of American options under time-dependent Ornstein-Uhlenbeck processes

Abel Azze, Bernardo D'Auria, Eduardo García-Portugués

We study the barrier that gives the optimal time to exercise an American option written on a time-dependent Ornstein--Uhlenbeck process, a diffusion often adopted by practitioners…

q-fin.PM2022

Before and after default: information and optimal portfolio via anticipating calculus

José A. Salmerón, Giulia Di Nunno, Bernardo D'Auria

Default risk calculus plays a crucial role in portfolio optimization when the risky asset is under threat of bankruptcy. However, traditional stochastic control techniques are not…

math.OC2022

An Anticipative Markov Modulated Market

Bernardo D'Auria, José A. Salmerón

A Markovian modulation captures the trend in the market and influences the market coefficients accordingly. The different scenarios presented by the market are modeled as the disti…

math.PR2021

Anticipative information in a Brownian-Poissonmarket: the binary information

Bernardo D'Auria, José A. Salmerón

The binary information collects all those events that may or may not occur. With this kind of variables, a large amount of information can be captured, in particular, about financi…

math.PR2021★ 1 cited

Optimal stopping of an Ornstein-Uhlenbeck bridge

Abel Azze, Bernardo D'Auria, Eduardo García-Portugués

We make a rigorous analysis of the existence and characterization of the free boundary related to the optimal stopping problem that maximizes the mean of an Ornstein--Uhlenbeck bri…