SHS Web Conf.
Volume 181, 20242023 International Conference on Digital Economy and Business Administration (ICDEBA 2023)
|Number of page(s)
|Financial Analysis and Stock Market Strategies
|17 January 2024
Bitcoin price prediction based on fear & greed index
Computer Science, CSE Department, The Chinese University of Hong Kong, 999077, Hong kong, China
* Corresponding author: firstname.lastname@example.org
This study investigates the Fear & Greed Index, an indicator designed to reflect market sentiment regarding Bitcoin price, intending to utilize it as a predictive parameter for future price fluctuations. Due to the substantial volatility in Bitcoin prices and its significant influence on prediction outcomes, the dataset was preprocessed through monthly filtering and normalization. To forecast Bitcoin prices, an array of machine learning algorithms, including linear regression, random forest, and XGBoost, as well as their enhanced counterparts, were employed. The optimal model was identified by comparing the Grid Search XGBoost analysis results. This research holds implications for accurately predicting Bitcoin prices and underscores the impact of market sentiment on its valuation.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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