From the 1 of 7 linked papers with an AI index.
7 papers
Composite likelihood inference of fractional Gaussian processes with sequentially optimal subset selection
Mathis Fourreau, Matthieu Garcin
The paper proposes a composite likelihood framework for estimating parameters of fractional Gaussian processes, introducing a sequential subset selection scheme that maximizes Goda…
Prediction of linear fractional stable motions using codifference, with application to non-Gaussian rough volatility
Matthieu Garcin, Karl Sawaya, Thomas Valade
The linear fractional stable motion (LFSM) extends the fractional Brownian motion (fBm) by considering -stable increments. We propose a method to forecast future increments of…
Directional Dependence of Extreme Events
Matthieu Garcin, Maxime L. D. Nicolas
This paper introduces a novel measure to quantify the directional dependence of extreme events between two variables. The proposed approach is designed to capture asymmetric tail d…
Asymptotic and finite-sample distributions of one- and two-sample empirical relative entropy
Matthieu Garcin, Louis Perot
In the perspective of building statistical tests of divergence between two probability distributions, we study the distribution of empirical relative entropy and derive several typ…
Market information of the fractional stochastic regularity model
Daniele Angelini, Matthieu Garcin
The Fractional Stochastic Regularity Model (FSRM) is an extension of Black-Scholes model describing the multifractal nature of prices. It is based on a multifractional process with…
Credit scoring using neural networks and SURE posterior probability calibration
Matthieu Garcin, Samuel Stephan
In this article we compare the performances of a logistic regression and a feed forward neural network for credit scoring purposes. Our results show that the logistic regression gi…