In todays’ world everyone starting from a child to an adult is studying stocks and is finding ways to earn more by studying the patterns of the market. Stock market is a compound interrelated system of various investors. It fluctuates frequently and hence is hard to predict what is yet to come. All the companies worldwide rely on these forecasts and speculations so that they can increase their profits. Everyday news on the economic front plays a vital role in defining the jump or drop in the prices of stocks. The market news helps the investor excessively in determining his bidding as it is immensely rich in information. In this study, we extract useful information from news headlines of a particular company to investigate the immediate impact of it on the company’s stock growth. Having the text based dataset we use NLP and compare two approaches using two different algorithms which both collectively determine the sentiment of the news headline (whether it is positive/negative/neutral) in lieu with the company stocks.

Differential evolution algorithm (DE) requires diversified population to solve multi- modalproblems. DE supports non-distributed population. DE versions include differential evolution algorithm with best selection method and species evolution (DESBS) and differential evolution algorithm with hierarchical fair competition modal (HFCDE). This article analyzed the efficiency of HFCDE and DESBS to solve the multi-modal s’ problems. HFCDE and DESBS support non-distributed population structured. HFCDE starts with set of feasible solution then it distributed them in the different hierarchy. HFCDE provides the fair competition. DESBS is another semi distributed, differential evolution algorithm.It starts with set of feasible solutions (population). Later it identifies the niches and create the sub-groups within population. Both HFCDE and DESBS have outperformed the other variant of state-of-art variants of DE. Here, the performance of DESBS and the HFCDE are rigorously tested on the multimodal problems. The success of DESBS over HFCDE in multi-modal difficulties managed to overcome the phenomena of elitism to resolve the complex problems, it has been observed that DESBS performs better than HFCDE in complex multi-modal scenarios.