Leveraging Explainable AI to Support Cryptocurrency Investors
In the last decade, cryptocurrency trading has attracted the attention of private and professional traders and investors. To forecast the financial markets, algorithmic trading systems based on Artificial Intelligence (AI) models are becoming more and more established. However, they suffer from the...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-08-01
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| Series: | Future Internet |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1999-5903/14/9/251 |
| _version_ | 1797488163981099008 |
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| author | Jacopo Fior Luca Cagliero Paolo Garza |
| author_facet | Jacopo Fior Luca Cagliero Paolo Garza |
| author_sort | Jacopo Fior |
| collection | DOAJ |
| description | In the last decade, cryptocurrency trading has attracted the attention of private and professional traders and investors. To forecast the financial markets, algorithmic trading systems based on Artificial Intelligence (AI) models are becoming more and more established. However, they suffer from the lack of transparency, thus hindering domain experts from directly monitoring the fundamentals behind market movements. This is particularly critical for cryptocurrency investors, because the study of the main factors influencing cryptocurrency prices, including the characteristics of the blockchain infrastructure, is crucial for driving experts’ decisions. This paper proposes a new visual analytics tool to support domain experts in the explanation of AI-based cryptocurrency trading systems. To describe the rationale behind AI models, it exploits an established method, namely SHapley Additive exPlanations, which allows experts to identify the most discriminating features and provides them with an interactive and easy-to-use graphical interface. The simulations carried out on 21 cryptocurrencies over a 8-year period demonstrate the usability of the proposed tool. |
| first_indexed | 2024-03-09T23:58:10Z |
| format | Article |
| id | doaj.art-2ff774277d1b47d1817f1f1296a80bc5 |
| institution | Directory Open Access Journal |
| issn | 1999-5903 |
| language | English |
| last_indexed | 2024-03-09T23:58:10Z |
| publishDate | 2022-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Future Internet |
| spelling | doaj.art-2ff774277d1b47d1817f1f1296a80bc52023-11-23T16:20:35ZengMDPI AGFuture Internet1999-59032022-08-0114925110.3390/fi14090251Leveraging Explainable AI to Support Cryptocurrency InvestorsJacopo Fior0Luca Cagliero1Paolo Garza2Dipartimento di Automatica e Informatica, Politecnico di Torino, Corso Duca Degli Abruzzi, 24, 10129 Torino, ItalyDipartimento di Automatica e Informatica, Politecnico di Torino, Corso Duca Degli Abruzzi, 24, 10129 Torino, ItalyDipartimento di Automatica e Informatica, Politecnico di Torino, Corso Duca Degli Abruzzi, 24, 10129 Torino, ItalyIn the last decade, cryptocurrency trading has attracted the attention of private and professional traders and investors. To forecast the financial markets, algorithmic trading systems based on Artificial Intelligence (AI) models are becoming more and more established. However, they suffer from the lack of transparency, thus hindering domain experts from directly monitoring the fundamentals behind market movements. This is particularly critical for cryptocurrency investors, because the study of the main factors influencing cryptocurrency prices, including the characteristics of the blockchain infrastructure, is crucial for driving experts’ decisions. This paper proposes a new visual analytics tool to support domain experts in the explanation of AI-based cryptocurrency trading systems. To describe the rationale behind AI models, it exploits an established method, namely SHapley Additive exPlanations, which allows experts to identify the most discriminating features and provides them with an interactive and easy-to-use graphical interface. The simulations carried out on 21 cryptocurrencies over a 8-year period demonstrate the usability of the proposed tool.https://www.mdpi.com/1999-5903/14/9/251quantitative tradingcryptocurrenciesblockchain |
| spellingShingle | Jacopo Fior Luca Cagliero Paolo Garza Leveraging Explainable AI to Support Cryptocurrency Investors Future Internet quantitative trading cryptocurrencies blockchain |
| title | Leveraging Explainable AI to Support Cryptocurrency Investors |
| title_full | Leveraging Explainable AI to Support Cryptocurrency Investors |
| title_fullStr | Leveraging Explainable AI to Support Cryptocurrency Investors |
| title_full_unstemmed | Leveraging Explainable AI to Support Cryptocurrency Investors |
| title_short | Leveraging Explainable AI to Support Cryptocurrency Investors |
| title_sort | leveraging explainable ai to support cryptocurrency investors |
| topic | quantitative trading cryptocurrencies blockchain |
| url | https://www.mdpi.com/1999-5903/14/9/251 |
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