Feb. 13, 2024, 5:43 a.m. | Bryan Kelly Boris Kuznetsov Semyon Malamud Teng Andrea Xu

cs.LG updates on arXiv.org arxiv.org

We open up the black box behind Deep Learning for portfolio optimization and prove that a sufficiently wide and arbitrarily deep neural network (DNN) trained to maximize the Sharpe ratio of the Stochastic Discount Factor (SDF) is equivalent to a large factor model (LFM): A linear factor pricing model that uses many non-linear characteristics. The nature of these characteristics depends on the architecture of the DNN in an explicit, tractable fashion. This makes it possible to derive end-to-end trained DNN-based …

black box box cs.ce cs.lg deep learning deep neural network dnn linear network neural network non-linear optimization portfolio pricing prove q-fin.st stochastic

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