activity
20172021
most citedApproximation of Ruin Probabilities via Erlangized Scale Mixtures

2 citations · 2 across the 4 of their papers we have counts for

collaborators

6 papers

math.PR2021

A Markov jump process associated with the matrix-exponential distribution

Oscar Peralta

Let be the density function associated to a matrix-exponential distribution of parameters . By exponentially tilting , we find a probabilistic interpretation which…

math.PR2021

RAP-modulated Fluid Processes: First Passages and the Stationary Distribution

Nigel G. Bean, Giang T. Nguyen, Bo F. Nielsen +1

We construct a stochastic fluid process with an underlying piecewise deterministic Markov process (PDMP) akin to the one used in the construction of the rational arrival process (R…

math.PR2021

Wong--Zakai approximations with convergence rate for stochastic differential equations with regime switching

Giang T. Nguyen, Oscar Peralta

We construct Wong--Zakai approximations of time--inhomogeneous stochastic differential equations with regime switching (RSSDEs), and provide a convergence rate. %Given a family of…

math.PR2020

An explicit solution to the Skorokhod embedding problem for double exponential increments

Giang T. Nguyen, Oscar Peralta

Strong approximations of uniform transport processes to the standard Brownian motion rely on the Skorokhod embedding of random walk with centered double exponential increments. In…

math.PR2019

Rate of Strong Convergence to Markov-modulated Brownian motion

Giang T. Nguyen, Oscar Peralta

In Latouche and Nguyen (2015), the authors constructed a sequence of stochastic fluid processes and showed that it converges weakly to a Markov-modulated Brownian motion (MMBM). He…

math.PR20172 cited

Approximation of Ruin Probabilities via Erlangized Scale Mixtures

Oscar Peralta, Leonardo Rojas-Nandayapa, Wangyue Xie +1

In this paper, we extend an existing scheme for numerically calculating the probability of ruin of a classical Cramér--Lundberg reserve process having absolutely continuous but oth…