In the world, every country depending on the economy. Economy depending upon the population activities. One of the most vital activities in these activities is selling, buying, and Investing money. So, Investment of the money on different aspects of the economy. So, Investment of the money common man to a rich person thinking about it. Above all the things are call share market. So many people are daily investing the daily money basis and long term basis also. Every significant business factor is risk analysis and trends of the share prices. In the share market, a massive amount of data generated day by day. So In this paper objective is to predict the low price and high price situations. This situation to predict using machine learning regression techniques is Linear, Lasso, Bayesian ridge, ridge, and Embaded Stack Regression algorithms. And predict the classes of high and low prices in time sequences and find out the performance attributes of the regression and compare them with the new embed stacking algorithm.