![]() ![]() ![]() Linear regression does try to predict trends and future values. In simple words, y is the output when m, x, and c are used as inputs. Where y is the estimated dependent variable, m is the regression coefficient, or what is commonly called the slope, x is the independent variable and c is a constant. The simplest form of the regression equation with one dependent and one independent variable is defined by the formula Let’s recap the concept of linear regression, choose an arbitrary time frame, take the past data, apply the method, identify the past trend, and check the results. With this in mind, let’s try and figure out the future stock prices of Infosys (NSE Symbol: INFY). If the existing trend carries on into the future then you could have a potential winner.Ī caveat needs to be added: Nothing can determine with any assurance that the future will turn out to be exactly like the past and so this method like other forecasting methods despite being fundamentally useful has its limitations. IntroductionĮven though there are myriad complex methods and systems aimed at trying to forecast future stock prices, the simple method of linear regression does help to understand the past trend and is used by professionals as well as beginners to try and extrapolate the existing or past trend into the future. This article was published as a part of the Data Science Blogathon. ![]()
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