Knowledge Management System of Institutes of Science and Development ,CAS
A novel cryptocurrency price trend forecasting model based on LightGBM | |
Sun Xiaolei![]() ![]() | |
Source Publication | FINANCE RESEARCH LETTERS
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Keyword | Cryptocurrency Trend forecasting LightGBM Forecasting performance |
Abstract | Forecasting cryptocurrency prices is crucial for investors. In this paper, we adopt a novel Gradient Boosting Decision Tree (GBDT) algorithm, Light Gradient Boosting Machine (LightGBM), to forecast the price trend (falling, or not falling) of cryptocurrency market. In order to utilize market information, we combine the daily data of 42 kinds of primary cryptocurrencies with key economic indicators. Results show that the robustness of the LightGBM model is better than the other methods, and the comprehensive strength of the cryptocurrencies impacts the forecasting performance. This can effectively guide investors in constructing an appropriate cryptocurrency portfolio and mitigate risks. |
2020 | |
Volume | 32Issue:101084Pages:1 |
DOI | 10.1016/j.frl.2018.12.032 |
Indexed By | SSCI ; SSCI |
Language | 英语 |
Citation statistics | |
Document Type | 期刊论文 |
Identifier | http://ir.casisd.cn/handle/190111/9774 |
Collection | 中国科学院科技战略咨询研究院 |
Recommended Citation GB/T 7714 | Sun Xiaolei,Liu Mingxi,Sima Zeqian. A novel cryptocurrency price trend forecasting model based on LightGBM[J]. FINANCE RESEARCH LETTERS,2020,32(101084):1. |
APA | Sun Xiaolei,Liu Mingxi,&Sima Zeqian.(2020).A novel cryptocurrency price trend forecasting model based on LightGBM.FINANCE RESEARCH LETTERS,32(101084),1. |
MLA | Sun Xiaolei,et al."A novel cryptocurrency price trend forecasting model based on LightGBM".FINANCE RESEARCH LETTERS 32.101084(2020):1. |
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A novel cryptocurren(828KB) | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | View |
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