2020

Impact of News on the Commodity Market: Dataset and Results

Sinha, Ankur, Khandait, Tanmay

Understand

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.

Built on

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