金融市场预测
Financial Market Prediction
Yale University（耶鲁大学）
摘要：
鉴于雅虎和伦敦交易所等热门网站的财务数据，本文试图建模和预测可被视为“良好投资”的股票。股票有125个特征，从国内生产总值到EDIBTA，并以股票和市场价格回报之间的差异为标志。一个人工神经网络（自组织映射）适合对超过100万个数据点进行训练，以预测2013年及之后的测试股票的“良好投资”。
英文摘要：
Given financial data from popular sites like Yahoo and the London Exchange, the presented paper attempts to model and predict stocks that can be considered "good investments". Stocks are characterized by 125 features ranging from gross domestic product to EDIBTA, and are labeled by discrepancies between stock and market price returns. An artificial neural network (Self-Organizing Map) is fitted to train on more than a million data points to predict "good investments" given testing stocks from 2013 and after.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
