Sentiment Analysis for Trading | Quantra Courses | Learn to Trade Better

welcome to this course on Sentiment Analysis in trading. If you wish to trade using sentiments in a systematic fashion then this is the right course for you. Sentiments refer to the opinion or feeling of the people towards particular security or asset. These are expressed in the blogs, discussion forums, news article and tweets. Quantifying these text-based information by assigning a positive or negative score to it is known as sentiment analysis. Buying or selling of security using the sentiment score is known as sentiment trading. This is not a theoretical concept, we have seen how the sentiments move the market. For example, Elon Musk tweeted about Tesla on 22 Dec 2018. This tweet had a negative sentiment around it, as it hinted on Telsa failing to deliver on time. And a news article on 23 Dec 2018 said that Tesla slashed its price in China. As a result, the Tesla stock traded 6% lower on 24 Dec 2018. Another example is when an American reality television personality, Kylie Jenner on 22 Feb 2018 tweeted that she is done with Snapchat and stock fell around 6%. There are some other examples shown on the screen on how the sentiments affect the market. Although sentiment trading seems the obvious way to predict market movements, it is not easy. The human sentiments or emotions are extremely difficult for machines to interpret. That being said, we have Natural Language Processing (NLP). It is a field of study focused on the interactions between human language and computers. It enables machines to get closer to a human-level understanding of the sentiments expressed. In this course, you will learn to calculate the sentiments from the tweets and news article and create an intraday trading strategy by using the sentiments. We will discuss a detailed course flow in the upcoming video.

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