Netflix, Inc. share price estimation, through exponential regression analysis.

Abstract

The exponential linear regression analysis is an extremely important tool in the world of finance and economics, with this analysis you can make projections and forecasts of a dependent variable explained by an independent variable that presents a curvilinear relationship. The objective of this work was to determine an equation that allowed estimating the monthly prices of the shares of Netflix, Inc., using an exponential linear regression model. The estimated beta coefficients for the model, individually, were significant for both the base coefficient and the argument coefficient, whose values ​​were 57.8122 and 0.0333, respectively. The global test of significance of the beta coefficients was also statistically significant, presenting an F value of 543.13, thus validating the proposed model.