BovDB: 1995年至2020年期间机器学习B3级所有公司的股票报价数据集

Fabian Corrêa Cardoso, J. Malska, P. Ramiro, Giancarlo Lucca, E. N. Borges, V. Mattos, R. Berri
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引用次数: 0

摘要

股票市场负责全球巨额金融资源的流动。这个市场产生了大量的交易数据,经过分析后,这些数据对许多应用程序都非常有用。在本文中,我们介绍了BovDB,这是一个以巴西证券交易所(B3)为数据源构建的数据集,其中包含1995年至2020年之间的相关信息。我们通过应用累积因子来修正价格,来接近这些事件对股票的影响。结果与InfoMoney和BR Investing的公开数据进行了比较,表明我们的方法是有效的,符合市场标准。BovDB数据集可以用作不同应用程序的基准,并且对GitHub上的任何研究人员公开可用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
BovDB: A data set of stock quotes for Machine Learning on all companies from B3 between 1995 and 2020
Stock markets are responsible for the movement of huge amounts of financial resources around the world. This market generates a high volume of transaction data, which after being analyzed are very useful for many applications. In this paper we present BovDB, a data set that was built considering as source the Brazilian Stock Exchange (B3) with information related to the years between 1995 and 2020. We have approached the events’ impact on the stocks by applying a cumulative factor to correct prices. The results were compared with public data from InfoMoney and BR Investing, showing that our methods are valid and in accordance with the market standards. BovDB data set can be used as a benchmark for different applications and is publicly available for any researcher on GitHub.
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