927 citations · 2.7k across the 62 of their papers we have counts for
69 papers
Recurrent Neural Networks with more flexible memory: better predictions than rough volatility
Damien Challet, Vincent Ragel
We extend recurrent neural networks to include several flexible timescales for each dimension of their output, which mechanically improves their abilities to account for processes…
When is cross impact relevant?
Victor Le Coz, Iacopo Mastromatteo, Damien Challet +1
Trading pressure from one asset can move the price of another, a phenomenon referred to as cross impact. Using tick-by-tick data spanning 5 years for 500 assets listed in the Unite…
Price impact in equity auctions: zero, then linear
Mohammed Salek, Damien Challet, Ioane Muni Toke
Using high-quality data, we report several statistical regularities of equity auctions in the Paris stock exchange. First, the average order book density is linear around the aucti…
Statistical inference of lead-lag at various timescales between asynchronous time series from p-values of transfer entropy
Christian Bongiorno, Damien Challet
Symbolic transfer entropy is a powerful non-parametric tool to detect lead-lag between time series. Because a closed expression of the distribution of Transfer Entropy is not known…
Dissecting the explanatory power of ESG features on equity returns by sector, capitalization, and year with interpretable machine learning
Jérémi Assael, Laurent Carlier, Damien Challet
We systematically investigate the links between price returns and Environment, Social and Governance (ESG) scores in the European equity market. Using interpretable machine learnin…
Non-linear shrinkage of the price return covariance matrix is far from optimal for portfolio optimisation
Christian Bongiorno, Damien Challet
Portfolio optimization requires sophisticated covariance estimators that are able to filter out estimation noise. Non-linear shrinkage is a popular estimator based on how the Oracl…