A New Investment Method with AutoEncoder: Applications to Cryptocurrencies

Masafumi Nakano and Akihiko Takahashi
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Masafumi Nakano: Graduate School of Economics, The University of Tokyo
Akihiko Takahashi: Faculty of Economics, The University of Tokyo

No CIRJE-F-1128, CIRJE F-Series from CIRJE, Faculty of Economics, 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.

Pages: 32 pages
Date: 2019-10
New Economics Papers: this item is included in nep-cmp, nep-exp and nep-pay
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Persistent link: https://EconPapers.repec.org/RePEc:tky:fseres:2019cf1128

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