دورية أكاديمية
Evaluating interpretable machine learning predictions for cryptocurrencies
| العنوان: | Evaluating interpretable machine learning predictions for cryptocurrencies |
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| المؤلفون: | El Majzoub, A, Rabhi, FA, Hussain, W |
| بيانات النشر: | JOHN WILEY & SONS LTD |
| سنة النشر: | 2024 |
| المجموعة: | University of Technology Sydney: OPUS - Open Publications of UTS Scholars |
| مصطلحات موضوعية: | 0801 Artificial Intelligence and Image Processing, 1702 Cognitive Sciences, 4601 Applied computing, 4602 Artificial intelligence, 4609 Information systems |
| الوصف: | This study explores various machine learning and deep learning applications on financial data modelling, analysis and prediction processes. The main focus is to test the prediction accuracy of cryptocurrency hourly returns and to explore, analyse and showcase the various interpretability features of the ML models. The study considers the six most dominant cryptocurrencies in the market: Bitcoin, Ethereum, Binance Coin, Cardano, Ripple and Litecoin. The experimental settings explore the formation of the corresponding datasets from technical, fundamental and statistical analysis. The paper compares various existing and enhanced algorithms and explains their results, features and limitations. The algorithms include decision trees, random forests and ensemble methods, SVM, neural networks, single and multiple features N-BEATS, ARIMA and Google AutoML. From experimental results, we see that predicting cryptocurrency returns is possible. However, prediction algorithms may not generalise for different assets and markets over long periods. There is no clear winner that satisfies all requirements, and the main choice of algorithm will be tied to the user needs and provided resources. |
| نوع الوثيقة: | article in journal/newspaper |
| وصف الملف: | application/pdf |
| اللغة: | English |
| تدمد: | 1550-1949 2160-0074 |
| العلاقة: | Intelligent Systems in Accounting, Finance and Management; Intelligent Systems in Accounting, Finance and Management, 2023, 30, (3), pp. 137-149; http://hdl.handle.net/10453/176256Test |
| الإتاحة: | http://hdl.handle.net/10453/176256Test |
| حقوق: | info:eu-repo/semantics/openAccess |
| رقم الانضمام: | edsbas.80021578 |
| قاعدة البيانات: | BASE |
| تدمد: | 15501949 21600074 |
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