activity
20072024
most citedRobust adaptive importance sampling for normal random vectors

26 citations · 87 across the 17 of their papers we have counts for

collaborators

22 papers

q-fin.MF2024

A pure dual approach for hedging Bermudan options

Aurélien Alfonsi, Ahmed Kebaier, Jérôme Lelong

This paper develops a new dual approach to compute the hedging portfolio of a Bermudan option and its initial value. It gives a "purely dual" algorithm following the spirit of Roge…

q-fin.PM2023

Mean-variance dynamic portfolio allocation with transaction costs: a Wiener chaos expansion approach

Areski Cousin, Jérôme Lelong, Tom Picard

This paper studies the multi-period mean-variance portfolio allocation problem with transaction costs. Many methods have been proposed these last years to challenge the famous uni-…

math.ST2022

How many inner simulations to compute conditional expectations with least-square Monte Carlo?

Aurélien Alfonsi, Bernard Lapeyre, Jérôme Lelong

The problem of computing the conditional expectation E[f (Y)|X] with least-square Monte-Carlo is of general importance and has been widely studied. To solve this problem, it is usu…

q-fin.CP2022

Pricing Bermudan options using regression trees/random forests

Zineb El Filali Ech-Chafiq, Pierre Henry-Labordere, Jérôme Lelong

The value of an American option is the maximized value of the discounted cash flows from the option. At each time step, one needs to compare the immediate exercise value with the c…

math.PR2021

Rare event simulation for electronic circuit design

Xavier Jonsson, Jérôme Lelong

In this work, we propose an algorithm to simulate rare events for electronic circuit design. Our approach heavily relies on a smart use of importance sampling, which enables us to…

math.PR2021

Rating transitions forecasting: a filtering approach

Areski Cousin, Jérôme Lelong, Tom Picard

Analyzing the effect of business cycle on rating transitions has been a subject of great interest these last fifteen years, particularly due to the increasing pressure coming from…