论文标题
一个实际数据驱动的分析模型，以预测信息技术领域指数的标准普尔500
A Real Data-Driven Analytical Model to Predict Information Technology Sector Index Price of S&P 500
论文作者
论文摘要
标准普尔500指数是世界上最受欢迎的股票指数之一。特别是，在市值，年收入和与之相关的公司数量（75）方面，标准普尔500指数的信息技术领域是标准普尔500标准普尔500指数的第一业务部门，并且由于多年来投资年度率高，这是许多投资者最吸引人的领域之一。建立了一个非线性实际数据驱动的分析模型，以预测S＆P 500信息技术部门指数的每周收盘价（WCP），使用六个财务，四个经济指标及其两道互动作为驱动股票收益的属性实体。我们根据标准普尔500的信息技术部门指数的$ WCP $的贡献百分比对统计学意义的指标及其相互作用进行排名，该指标为提议的预测模型的受益人提供了重要信息。该模型的预测精度为99.4％，本文提出了一些有趣的发现和模型的实用性。
S&P 500 Index is one of the most sought after stock indices in the world. In particular, Information Technology Sector of S&P 500 is the number one business segment of the S&P 500 in terms of market capital, annual revenue and the number of companies (75) associated with it, and is one of the most attracting areas for many investors due to high percentage annual returns on investment over the years. A non-linear real data-driven analytical model is built to predict the Weekly Closing Price (WCP) of the Information Technology Sector Index of S&P 500 using six financial, four economic indicators and their two way interactions as the attributable entities that drive the stock returns. We rank the statistically significant indicators and their interactions based on the percentage of contribution to the $WCP$ of the Information Technology Sector Index of the S&P 500 that provides significant information for the beneficiary of the proposed predictive model. The model has the predictive accuracy of 99.4%, and the paper presents some intriguing findings and the model's usefulness.
