Matthieu Garcin | DeepAI

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Featured Co-authors

Xavier Brouty
2 publications
Samuel Stéphan
1 publication
Ayoub Ammy-Driss
1 publication
Jules Klein
1 publication
Sana Laaribi
1 publication
Maxime L. D. Nicolas
1 publication

∙ 06/23/2023

Fractal properties, information theory, and market efficiency

Considering that both the entropy-based market information and the Hurst...

0 Xavier Brouty, et al. ∙

∙ 05/22/2023

Complexity measure, kernel density estimation, bandwidth selection, and the efficient market hypothesis

We are interested in the nonparametric estimation of the probability den...

0 Matthieu Garcin, et al. ∙

∙ 08/25/2022

A statistical test of market efficiency based on information theory

We determine the amount of information contained in a time series of pri...

0 Xavier Brouty, et al. ∙

∙ 11/22/2021

Nonparametric estimator of the tail dependence coefficient: balancing bias and variance

A theoretical expression is derived for the mean squared error of a nonp...

0 Matthieu Garcin, et al. ∙

∙ 07/15/2021

Credit scoring using neural networks and SURE posterior probability calibration

In this article we compare the performances of a logistic regression and...

0 Matthieu Garcin, et al. ∙

∙ 07/21/2020

Efficiency of the financial markets during the COVID-19 crisis: time-varying parameters of fractional stable dynamics

This paper investigates the impact of COVID-19 on financial markets. It ...

0 Ayoub Ammy-Driss, et al. ∙

∙ 07/17/2020

Estimation of time-varying kernel densities and chronology of the impact of COVID-19 on financial markets

The time-varying kernel density estimation relies on two free parameters...

0 Matthieu Garcin, et al. ∙

∙ 03/05/2020

A comparison of maximum likelihood and absolute moments for the estimation of Hurst exponents in a stationary framework

The absolute-moment method is widespread for estimating the Hurst expone...

0 Matthieu Garcin, et al. ∙

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