Multi-Task Learning for Stock Selection
نویسندگان
چکیده
Arti cial Neural Networks can be used to predict future returns of stocks in order to take nancial decisions Should one build a separate network for each stock or share the same network for all the stocks In this paper we also explore other alternatives in which some layers are shared and others are not shared When the prediction of future returns for di erent stocks are viewed as di erent tasks sharing some parameters across stocks is a form of multi task learning In a series of experiments with Canadian stocks we obtain yearly returns that are more than above
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