Human Psychology, High Profile Covid-19 Cases and the Impact on Sentiment
In continuation with our write up of 10th March 2010, we have some interesting insights on how the local country by country sentiment on Coronavirus news flow has evolved and how it is linked to the performance of local stock markets. There are some clear takeaways on this;
- On a time series for the countries individually, you notice huge fluctuations in Coronavirus sentiment. In some cases (of which USA is the most prominent), the news flow sentiment has deteriorated rapidly.
- The same is the case with Canada in which the Coronavirus news flow sentiment has deteriorated sharply. But the reasons are perhaps different than US. In Canada, this could be because of a high-profile case of infection (Prime Minister’s wife).
- The huge volatility noticed in the markets such as US is linked with rapid deterioration on one side and the policy announcements on the other. If left to Corona alone, things could have been much worse.
- India is an interesting case because after the ‘V’ shape recovery in sentiment, the news flow has deteriorated but at a rate which is not rapid. This reflects in sharp recovery in markets as noticed in Friday’s trading session.
- The variance between countries on day to day basis continues (for example, Japan is the country with the most NEGATIVE sentiment on the basis of news flow for 14th March) and while things look much better for Korea, Chile and Brazil.
- All of this leads to the question: Can the sentiment analysis be used for taking a short term call on markets? And the answer is a resounding YES. As shown in the Chart 3, the portfolio incorporating Coronavirus sentiment does significantly better vs. BSE Sensex.
Chart 1: Time series for Daily Sentiment for countries on Coronavirus
Chart 2: Daily Sentiment for countries on Coronavirus
Chart 3: Market performance of Sentiment based Portfolio vs. BSE Sensex
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EMAlpha, a data analytics and investment management firm focused on making Emerging Markets (EMs) accessible to global investors and unlocking EM investing using machines. EMAlpha’s focus is on Unstructured Data as the EMs are particularly susceptible to swings in news flow driven investor sentiment. We use thoroughly researched machine learning tools to track evolving sentiment specifically towards EMs and EMAlpha pays special attention to the timely measurement of news sentiment for investors as these markets can be finicky and sentiment can be capricious.Our team members have deep expertise in research and trading in multiple Emerging Markets and EMAlpha’s collaborative approach to combining machine learning tools with a fundamental approach help us understand these markets better.
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