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A new investment method with AutoEncoder: Applications to crypto currencies(Forthcoming in "Expert Systems with Applications")

Masafumi Nakano and Akihiko Takahashi
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Masafumi Nakano: GCI Asset Management
Akihiko Takahashi: Graduate School of Economics and CARF, University of Tokyo

No CARF-F-489, CARF F-Series from Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo

Abstract: This paper proposes a novel approach to the portfolio management using an AutoEncoder. In particular, features learned by an AutoEncoder with ReLU are directly exploited to portfolio constructions. Since the AutoEncoder extracts characteristics of data through a non-linear activation function ReLU, its realization is generally difficult due to the non-linear transformation procedure. In the current paper, we solve this problem by taking full advantage of the similarity of ReLU and an option payoff. Especially, this paper shows that the features are successfully replicated by applying so-called dynamic delta hedging strategy. An out of sample simulation with crypto currency dataset shows the effectiveness of our proposed strategy.

Date: 2020-07
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Persistent link: https://EconPapers.repec.org/RePEc:cfi:fseres:cf489

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