论文标题
新闻对商品市场的影响：数据集和结果
Impact of News on the Commodity Market: Dataset and Results
论文作者
论文摘要
在过去的几年中，基于机器学习的方法已应用于从金融领域的新闻流中提取信息。但是，这些信息主要是新闻头条中包含的财务情感的形式，主要是出于股价。在我们目前的工作中，我们建议可以从新闻头条中提取各种其他信息，这对投资者，政策制定者和其他从业人员感兴趣。我们提出了一个框架，该框架提取了诸如新闻所指的诸如过去运动，资产比较和其他一般信息的预期方向性之类的信息。我们将此框架应用于商品“黄金”，并使用11,412个人类通知的新闻头条（与本研究一起发布）的数据集训练机器学习模型，该数据集从2000- 2019年期间收集。我们试验以验证新闻流对黄金价格的因果影响，并观察到我们框架产生的信息显着影响未来的黄金价格。
Over the last few years, machine learning based methods have been applied to extract information from news flow in the financial domain. However, this information has mostly been in the form of the financial sentiments contained in the news headlines, primarily for the stock prices. In our current work, we propose that various other dimensions of information can be extracted from news headlines, which will be of interest to investors, policy-makers and other practitioners. We propose a framework that extracts information such as past movements and expected directionality in prices, asset comparison and other general information that the news is referring to. We apply this framework to the commodity "Gold" and train the machine learning models using a dataset of 11,412 human-annotated news headlines (released with this study), collected from the period 2000-2019. We experiment to validate the causal effect of news flow on gold prices and observe that the information produced from our framework significantly impacts the future gold price.
