Meltem Karaatlı, Turan Kocabıyık, Damla Yalçiner Çal, M. Çolak
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引用次数: 0
Abstract
Nowadays, the advancement of technology and easier access to data has led to a large increase in the number of data mining studies. In this study, in order to create a portfolio, stocks acting together under the influence of macroeconomic variables were determined by data mining. In addition to the stocks in Borsa İstanbul 30 (BIST-30) index, macro-economic variables such as M1 money supply, gold ounce price, the ratio of exports to im-ports, industrial production index, currency basket, the capacity utilization rate of manufacturing industry, in-terest rate, producer price index, financial services confidence index, foreign direct investments, crude oil, S&P 500 index are used. Five-year data set covering the years 2014-2019 was used in the research. FP-Growth algorithm, has a high performance, was used to determine the transactions that move together and WEKA program was preferred for the application. As a result of the study, it is revealed which investment instruments can be invested or which investment instruments can be followed by making use of the changes in stock markets and macroeconomic variables. The main result obtained from this study; among the stocks included in Borsa İstanbul 30 index, the shares of the banking index mostly act together within the financial index.
如今,技术的进步和更容易获取数据导致了数据挖掘研究数量的大量增加。在本研究中,为了创建一个投资组合,在宏观经济变量的影响下,通过数据挖掘确定股票的共同作用。除Borsa İstanbul 30指数(BIST-30)股票指数外,还使用了M1货币供应量、黄金盎司价格、进出口比、工业生产指数、货币篮子、制造业产能利用率、利率、生产者价格指数、金融服务业信心指数、外国直接投资、原油、标准普尔500指数等宏观经济变量。该研究使用了2014-2019年的五年数据集。FP-Growth算法具有较高的性能,用于确定一起移动的事务,应用程序首选WEKA程序。作为研究的结果,揭示了哪些投资工具可以投资,哪些投资工具可以利用股票市场和宏观经济变量的变化。本研究得到的主要结果;在Borsa İstanbul 30指数所包含的股票中,银行指数的股票大多在金融指数内一起行动。