84 citations · 141 across the 10 of their papers we have counts for
13 papers
Hawkes processes for credit indices time series analysis: How random are trades arrival times?
Achraf Bahamou, Maud Doumergue, Philippe Donnat
Targeting a better understanding of credit market dynamics, the authors have studied a stochastic model named the Hawkes process. Describing trades arrival times, this kind of mode…
Putting Self-Supervised Token Embedding on the Tables
Marc Szafraniec, Gautier Marti, Philippe Donnat
Information distribution by electronic messages is a privileged means of transmission for many businesses and individuals, often under the form of plain-text tables. As their numbe…
Autoregressive Convolutional Neural Networks for Asynchronous Time Series
Mikołaj Bińkowski, Gautier Marti, Philippe Donnat
We propose Significance-Offset Convolutional Neural Network, a deep convolutional network architecture for regression of multivariate asynchronous time series. The model is inspire…
A review of two decades of correlations, hierarchies, networks and clustering in financial markets
Gautier Marti, Frank Nielsen, Mikołaj Bińkowski +1
We review the state of the art of clustering financial time series and the study of their correlations alongside other interaction networks. The aim of this review is to gather in…
Exploring and measuring non-linear correlations: Copulas, Lightspeed Transportation and Clustering
Gautier Marti, Sebastien Andler, Frank Nielsen +1
We propose a methodology to explore and measure the pairwise correlations that exist between variables in a dataset. The methodology leverages copulas for encoding dependence betwe…
Clustering Financial Time Series: How Long is Enough?
Gautier Marti, Sébastien Andler, Frank Nielsen +1
Researchers have used from 30 days to several years of daily returns as source data for clustering financial time series based on their correlations. This paper sets up a statistic…