金融新闻重贴标签的深层语言分类及其在股价预测中的应用Deep Language Classification for Relabeling of Financial News and its application in Stock Price Forecasting |
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课程网址: | http://videolectures.net/sikdd2019_torkar_stock_price_forecasting... |
主讲教师: | Miha Torkar |
开课单位: | Jožef Stefan研究所人工智能实验室 |
开课时间: | 2019-11-14 |
课程语种: | 英语 |
中文简介: | 本文旨在评估转移学习任务的绩效,该任务由74家上市公司的高频金融新闻数据的分类员培训集组成,带有特定领域的标签。该数据来源由Jozef Stefan Institute提供,仅用于本研究目的。然后使用经过培训的分类程序将标签归为未标记的高频聚合新闻源,即事件注册表。其目的是将重新标记的数据用于生成外生特征,以用于公司价格的时间序列预测。研究发现,使用微调的BERT[1]模型可以产生语义上最连贯的标签,而从新标记的数据生成的特征证明可以对保留的价格数据进行最高精度的预测。 |
课程简介: | This paper aims at assessing the performance of the transfer learning task consisting of training set of classiffiers on high frequency financial news data for 74 publicly traded companies, with domain speciffic labels. This source of data is provided by the Jozef Stefan Institute and is used exclusively for the purposes of this research. The trained classiffiers are then used to attribute labels to an unlabelled source of high frequency aggregated news, Event-Registry. The aim is for the relabelled data to be used in the generation of exogenous features for use in time series forecasting of the companies' prices. It is found that using a fine-tuned BERT [1] model yields the most semantically coherent labels, and the features generated from the newly labelled data prove to yield the highest accuracy forecasts on held out price data. |
关 键 词: | 金融新闻重贴标签; 深层语言分类; 在股价预测中的应用 |
课程来源: | 视频讲座网 |
数据采集: | 2022-09-14:cyh |
最后编审: | 2022-09-19:cyh |
阅读次数: | 41 |