The financial crash of 2020 and the retail trader’s boon: a correlation between sentiment and technical analysis

Abstract

The American stock market passed a critical phase during 2020. The CBOE volatility index had spiked from a little over 20 to a little over 50 and returned flat to 16% year on year basis. This paper presents a novel model to measure the engagements of retailer trading through public perception and forced media messages. The markets have proved to be resilient on the expected returns in the long term however the short-term spot markets were unpredictable. Even though the Dow Jones fell from 29,100 points to 19,180 points the big investment banks made huge trading profits. Bank of America's trading revenue grew from $3.8 billion to $5.3 billion whereas the retailers went for the bankrupt companies such as Macy’s and Hertz. The paper discusses the prediction with help of neural networks and NLP models to analyze retailer’s favorite stocks and helps to predict their future expected returns of the stocks. The results of the research create a new key performance index for asset-level risk management using this correlation.