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<article xsi:noNamespaceSchemaLocation="http://jats.nlm.nih.gov/publishing/1.1/xsd/JATS-journalpublishing1-mathml3.xsd" dtd-version="1.1" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"><front><journal-meta><journal-id journal-id-type="publisher-id">JERA</journal-id><journal-title-group><journal-title>Journal of Electronic Research and Application</journal-title></journal-title-group><issn>2208-3502</issn><eissn>2208-3510</eissn><publisher><publisher-name>Bio-Byword Scientific Publishing Pty. Ltd.</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.26689/jera.v8i5.7676</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title>Using Python to Analyze Financial Big Data</title><url>https://artdesignp.com/journal/JERA/8/5/10.26689/jera.v8i5.7676</url><author>ZhuXuanrui</author><pub-date pub-type="publication-year"><year>2024</year></pub-date><volume>8</volume><issue>5</issue><history><date date-type="pub"><published-time>2024-08-26</published-time></date></history><abstract>As technology and the internet develop, more data are generated every day. These data are in large sizes, high dimensions, and complex structures. The combination of these three features is the “Big Data” [1]. Big data is revolutionizing all industries, bringing colossal impacts to them [2]. Many researchers have pointed out the huge impact that big data can have on our daily lives [3]. We can utilize the information we obtain and help us make decisions. Also, the conclusions we drew from the big data we analyzed can be used as a prediction for the future, helping us to make more accurate and benign decisions earlier than others. If we apply these technics in finance, for example, in stock, we can get detailed information for stocks. Moreover, we can use the analyzed data to predict certain stocks. This can help people decide whether to buy a stock or not by providing predicted data for people at a certain convincing level, helping to protect them from potential losses.</abstract><keywords/></article-meta></front><body/><back><ref-list><ref id="B1" content-type="article"><label>1</label><element-citation publication-type="journal"><p>Shui Y, Song G, 2016, Big Data Concepts, Theories, and Applications. Springer International Publishing. https://doi.org/10.1007/978-3-319-27763-9</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B2" content-type="article"><label>2</label><element-citation publication-type="journal"><p>Wolfert S, Ge L, Verdouw C, et al., 2017, Big Data in Smart Farming—A Review. Agricultural Systems, 153: 69–80. https://doi.org/10.1016/j.agsy.2017.01.023</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B3" content-type="article"><label>3</label><element-citation publication-type="journal"><p>Dash S, Shakyawar SK, Sharma M, et al., 2019, Big Data in Healthcare: Management, Analysis and Future Prospects. Journal of Big Data, 6: 54.</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B4" content-type="article"><label>4</label><element-citation publication-type="journal"><p>Goldstein I, Spatt CS, Mao Y, 2021, Big Data in France. The Review of Financial Studies, 34(7): 3213–3225.</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B5" content-type="article"><label>5</label><element-citation publication-type="journal"><p>Goldfarb D, 2022, Mplfinance Styles. https://github.com/matplotlib/mplfinance/blob/master/examples/styles.ipynb</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B6" content-type="article"><label>6</label><element-citation publication-type="journal"><p>Goldfarb D, 2022, Mplfinance Plot Customizations. https://github.com/matplotlib/mplfinance/blob/master/examples/plot_customizations.ipynb</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B7" content-type="article"><label>7</label><element-citation publication-type="journal"><p>Goldfarb D, 2023, Financial Markets Data Visualization using Matpolib. https://github.com/matplotlib/mplfinance?tab=readme-ov-file#usage</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B8" content-type="article"><label>8</label><element-citation publication-type="journal"><p>Hasan MM, Popp J, Olah J, 2020, Current Landscape and Influence of Big Data on Finance. Journal of Big Data, 7: 21.</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B9" content-type="article"><label>9</label><element-citation publication-type="journal"><p>Mahesh B, 2020, Machine Learning Algorithms—A Review. International Journal of Science and Research (IJSR), 9(1): 381–386.</p><pub-id pub-id-type="doi"/></element-citation></ref></ref-list></back></article>
