activity
20072026
collaborators

7 papers

q-fin.MF2026

Portfolio Decarbonization under Incomplete Carbon and Transition Information

Olivier Féron, Ruben Haalebos

We study dynamic portfolio decarbonization under incomplete information about firms' carbon intensities and the underlying transition state. The investor maximizes expected utility…

q-fin.MF2021

A survey of electricity spot and futures price models for risk management applications

Thomas Deschatre, Olivier Féron, Pierre Gruet

This review presents the set of electricity price models proposed in the literature since the opening of power markets. We focus on price models applied to financial pricing and ri…

q-fin.PR2020

Price formation and optimal trading in intraday electricity markets with a major player

Olivier Féron, Peter Tankov, Laura Tinsi

We study price formation in intraday electricity markets in the presence of intermittent renewable generation. We consider the setting where a major producer may interact strategic…

q-fin.PR2020

Price formation and optimal trading in intraday electricity markets

Olivier Féron, Peter Tankov, Laura Tinsi

We develop a tractable equilibrium model for price formation in intraday electricity markets in the presence of intermittent renewable generation. Using stochastic control theory,…

math.ST2018

Efficient volatility estimation in a two-factor model

Olivier Féron, Pierre Gruet, Marc Hoffmann

We statistically analyse a multivariate HJM diffusion model with stochastic volatility. The volatility process of the first factor is left totally unspecified while the volatility…

stat.ME2011

Estimation of covariance matrices based on hierarchical inverse-Wishart priors

Mathilde Bouriga, Olivier Féron

This paper focuses on Bayesian shrinkage for covariance matrix estimation. We examine posterior properties and frequentist risks of Bayesian estimators based on new hierarchical in…

physics.data-an2007

Bayesian segmentation of hyperspectral images

Adel Mohammadpour, Olivier Féron, Ali Mohammad-Djafari

In this paper we consider the problem of joint segmentation of hyperspectral images in the Bayesian framework. The proposed approach is based on a Hidden Markov Modeling (HMM) of t…