讲座时间：2022年4月1日上午10点
腾讯会议：680-480-687（线上）
地点：九里校区零号楼0411室（学生）
讲座题目：Forecasting the overnight return direction of stock market index combining global market indices: a multiple-branch deep learning approach
讲座内容：Forecasting the overnight (close-to-open) return direction of a stock market index has recently attracted great attention. Owing to the strong interactions among stock markets around the globe, one stock market would be inevitably affected by others. In this study, we take global stock market indices as an informative source and propose a deep learning approach combining genetic algorithm to forecast the overnight return direction of a target stock market index. Starting from the multiple-branch input layers representing stock market indices from various regions worldwide, we use multiple convolution units to extract the features from each region. These features are then concatenated and connected with fully connected layers to forecast the daily direction of the overnight return. To optimize the deep neural network, genetic algorithm is used to determine the optimal network architecture and parameters. In the experimental study, we apply the proposed model to forecasting the overnight return directions of nine target indices from Asia, Americas and Europe markets. The experimental results indicate that compared with other competing methods, the proposed model is superior in terms of the accuracy, F-measure and Sharpe ratio.
主讲人简介：王昱，男，重庆人，2004年于中国科学技术大学获得管理学学士学位，计算机科学与技术学士学位，2009年于中国科学技术大学获得管理科学与工程博士学位，现为重庆大学经管学院教授、博士生导师，主要研究领域为数据挖掘理论方法及应用。以主要作者（第一/通讯）在Knowledge-Based Systems、Expert Systems with Applications、Applied Soft Computing、中国管理科学、管理工程学报等国际国内期刊发表论文20余篇，主持完成国家自然科学基金项目2项、国家重点研发计划项目子课题1项以及多项横向项目，同时担任10余份国际期刊的论文评审人。
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