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Found 5 papers, 1 papers with code
Dimensionality reduction techniques to support insider trading detection
Identification of market abuse is an extremely complicated activity that requires the analysis of large and complex datasets.
A machine learning approach to support decision in insider trading detection
The first one uses clustering to identify, in the vicinity of a price sensitive event such as a takeover bid, discontinuities in the trading activity of an investor with respect to his/her own past trading history and on the present trading activity of his/her peers.
How Covid mobility restrictions modified the population of investors in Italian stock markets
There are thus indications that the lockdown, and more generally the Covid pandemic, created a sort of regime change in the population of financial investors.
Information Extraction through AI techniques: The KIDs use case at CONSOB
In this paper we report on the initial activities carried out within a collaboration between Consob and Sapienza University.
A Baseline for Shapley Values in MLPs: from Missingness to Neutrality
Deep neural networks have gained momentum based on their accuracy, but their interpretability is often criticised.
