A new investment method with AutoEncoder: Applications to crypto currencies
•We propose a new investment strategy free from the estimation of expected returns.•AutoEncoder extracts the factors which enable to prevent the large drawdown.•The extracted non-linear factors are implemented by the dynamic delta hedging.•Backtesting with multiple cryptocurrencies shows the effecti...
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| Published in: | Expert systems with applications Vol. 162; p. 113730 |
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| Main Authors: | , |
| Format: | Journal Article |
| Language: | English |
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30.12.2020
Elsevier BV |
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| ISSN: | 0957-4174, 1873-6793 |
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| Abstract | •We propose a new investment strategy free from the estimation of expected returns.•AutoEncoder extracts the factors which enable to prevent the large drawdown.•The extracted non-linear factors are implemented by the dynamic delta hedging.•Backtesting with multiple cryptocurrencies shows the effectiveness of our strategy.
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. |
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| AbstractList | 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. •We propose a new investment strategy free from the estimation of expected returns.•AutoEncoder extracts the factors which enable to prevent the large drawdown.•The extracted non-linear factors are implemented by the dynamic delta hedging.•Backtesting with multiple cryptocurrencies shows the effectiveness of our strategy. 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. |
| ArticleNumber | 113730 |
| Author | Nakano, Masafumi Takahashi, Akihiko |
| Author_xml | – sequence: 1 givenname: Masafumi surname: Nakano fullname: Nakano, Masafumi organization: GCI Asset Management, 10F Chiyoda First Bldg. East, 3-8-1 Nishi-Kanda, Chiyoda-ku, Tokyo 101-0065, Japan – sequence: 2 givenname: Akihiko surname: Takahashi fullname: Takahashi, Akihiko email: akihikot@e.u-tokyo.ac.jp organization: Faculty of Economics, The University of Tokyo, 7-3-1 Hongo Bunkyo-ku, Tokyo 113-0033, Japan |
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| Snippet | •We propose a new investment strategy free from the estimation of expected returns.•AutoEncoder extracts the factors which enable to prevent the large... This paper proposes a novel approach to the portfolio management using an AutoEncoder. In particular, features learned by an AutoEncoder with ReLU are directly... |
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| SubjectTerms | Artificial neural network AutoEncoder Crypto currency Delta hedging Digital currencies Linear transformations Portfolio management |
| Title | A new investment method with AutoEncoder: Applications to crypto currencies |
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