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Is the Covid equity bubble rational? A machine learning answer

Ohana, Jean Jacques; Benhamou, Éric; Saltiel, David; Guez, Beatrice (2021), Is the Covid equity bubble rational? A machine learning answer. https://basepub.dauphine.psl.eu/handle/123456789/22202

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Covid_equity.pdf (2.744Mb)
Type
Document de travail / Working paper
Date
2021
Series title
Preprint Lamsade
Published in
Paris
Metadata
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Author(s)
Ohana, Jean Jacques
Benhamou, Éric
Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Saltiel, David
Guez, Beatrice
Abstract (EN)
Is the Covid Equity bubble rational? In 2020, stock prices ballooned with S&P 500 gaining 16%, and the tech-heavy Nasdaq soaring to 43%, while fundamentals deteriorated with decreasing GDP forecasts, shrinking sales and revenues estimates and higher government deficits. To answer this fundamental question, with little bias as possible, we explore a gradient boosting decision trees (GBDT) approach that enables us to crunch numerous variables and let the data speak. We define a crisis regime to identify specific downturns in stock markets and normal rising equity markets. We test our approach and report improved accuracy of GBDT over other ML methods. Thanks to Shapley values, we are able to identify most important features, making this current work innovative and a suitable answer to the justification of current equity level.
Subjects / Keywords
Covid Equity

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