Explainable AI Models Applied to the Multi-Agent Environment of FInancial Markets (Slides EXTRAAMAS 2021 Seminar)

EXTRAAMAS 2021, 4 May 2021, online

17 Pages Posted: 6 May 2021 Last revised: 15 Nov 2021

See all articles by Jean-Jacques Ohana

Jean-Jacques Ohana

AI For Alpha

Steve Ohana

affiliation not provided to SSRN

Eric Benhamou

Université Paris Dauphine; EB AI Advisory; AI For Alpha

David Saltiel

Université Paris Dauphine; A.I. Square Connect; AI For Alpha

Beatrice Guez

AI For Alpha

Date Written: May 4, 2021

Abstract

Financial markets are a real life multi-agent system that is well known to be hard to explain and interpret. We consider a gradient boosting decision trees (GBDT) approach to predict large S&P 500 price drops from a set of 150 technical, fundamental and macroeconomic features. We report an improved accuracy of GBDT over other machine learning (ML) methods on the S&P 500 futures prices. We show that retaining fewer and carefully selected features provides improvements across all ML approaches. Shapley values have recently been introduced from game theory to the field of ML. They allow for a robust identification of the most important variables predicting stock market crises, and of a local explanation of the crisis probability at each date, through a consistent features attribution. We apply this methodology to analyse in detail the March 2020 financial meltdown, for which the model offered a timely out of sample prediction. This analysis unveils in particular the contrarian predictive role of the tech equity sector before and after the crash.

Suggested Citation

Ohana, Jean-Jacques and Ohana, Steve and Benhamou, Eric and Saltiel, David and Guez, Beatrice, Explainable AI Models Applied to the Multi-Agent Environment of FInancial Markets (Slides EXTRAAMAS 2021 Seminar) (May 4, 2021). EXTRAAMAS 2021, 4 May 2021, online, Available at SSRN: https://ssrn.com/abstract=3839353

Jean-Jacques Ohana

AI For Alpha ( email )

35 boulevard d'Inkermann
Neuilly sur Seine, 92200
France

Steve Ohana

affiliation not provided to SSRN

Eric Benhamou (Contact Author)

Université Paris Dauphine ( email )

Place du Maréchal de Tassigny
Paris, Cedex 16 75775
France

EB AI Advisory ( email )

35 Boulevard d'Inkermann
Neuilly sur Seine, 92200
France

AI For Alpha ( email )

35 boulevard d'Inkermann
Neuilly sur Seine, 92200
France

David Saltiel

Université Paris Dauphine ( email )

Place du Maréchal de Tassigny
Paris, Cedex 16 75775
France

A.I. Square Connect ( email )

35 Boulevard d'Inkermann
Neuilly sur Seine, 92200
France

AI For Alpha ( email )

35 boulevard d'Inkermann
Neuilly sur Seine, 92200
France

Beatrice Guez

AI For Alpha ( email )

35 boulevard d'Inkermann
Neuilly sur Seine, 92200
France

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
2,269
Abstract Views
43,778
PlumX Metrics