Comparative Analysis of Machine Learning Algorithms for Stock Market Prediction During COVID-19 Outbreak

In the current period of time, when there is a havoc across the world due to COVID-19 virus outbreak, it becomes very important to foresee the impact of this pandemic on the world economy. This has attracted us to analyze and predict the stock market prices of some international IT international companies which provide employment to thousands of people and create revenue for many countries namely Google, Microsoft, Apple and Amazon. In this study, we have implemented algorithms such as SVM and LSTM on stock market data to see if major IT companies see a rise or fall during the COVID-19 pandemic. We have also used ARIMA forecasting method to predict the stocks of above mentioned 4 companies. This paper provides a simple but original statistical analysis of the impact of the COVID-19 pandemic on stock market risk for 4 major IT companies of the world. Results revealed that while some businesses like personal computers from Microsoft, I phone handsets, sale of luxury and fashion goods at Amazon has declined during the pandemic, thus leading to fall of stocks. However, some prominent other segments like online shopping, cloud computing and streaming video from Amazon, oversees Office, Dynamics, Skype, LinkedIn Intelligent Cloud from Microsoft, Google’s ad sales during the crisis and issue of cheap bonds by Apple came out to be the winning corporate strategies to fight the negative economic effect of COVID-19 and to stabilize the situation of stocks in coming months. This study may help investors and companies to sustain the tide of economic fall.</p

Epoxidation studies of terpenes with urea hydrogen peroxide and phosphotungstic acid

598-602Epoxidation of isolated and allylic olefins with dodeca-phosphotungstic acid, H3[PW12O40]xH2O and urea hydrogen peroxide (UHP) adduct as an oxidant has successfully been carried out under homogenous conditions with the aid of isopropanol:water (4:1) as solvent, thereby avoiding the use of expensive phase transfer catalyst. The method has proven to be efficient in terms of percent yield, cost, reaction conditions and ease of work-up

An efficient microwave technique for <i style="">exo</i>-<i style=""> </i>to <i style="">endo-</i>double bond migration in natural products

611-614A few sesquiterpene lactones and monoterpenes when subjected to microwave irradiation on solid surface undergo facile carbon-carbon double bond migration from from exo- to endo-position