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Stawarz, Marcin, 2025, "Determining Multi-Class Trading Signals for Bitcoin: A Comparative Study of XGBoost, LightGBM, and Random Forest", https://doi.org/10.18150/FXSBZP, RepOD, V1
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The file provides daily trading data for Bitcoin (BTC) in USD, covering the period from January 1, 2015, to June 30, 2024. The dataset includes key indicators such as Open Price, High Price, Low Price, Close Price, Adjusted Close Price, and Volume.
This data originates from Yahoo Finance and serves as a foundation for time series analysis, forecasting, and machine learning models, focusing on identifying price patterns, volatility trends, and trading behaviors within the cryptocurrency market.
Raw data (CSV file). Source: Yahoo Finance.
Bitcoin, machine learning, classification, financial markets, trading signals
Stawarz M., Determining Multi-Class Trading Signals for Bitcoin: A Comparative Study of XGBoost, LightGBM, and Random Forest, Economics Letters :
CC0 Creative Commons Zero 1.0
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