Question

If your manager asked you the differences between time series forecasting models and regression-based forecasting models, what would you tell him/her?

Answer 1

Time series forecasting models analysing time series data in order to extract meaning full statistics and other characteristics of data. Time series forecasting model is the use of future prediction values based on previously observed values.

Time series data have natural temporal ordering. This analysis distinct from cross sectional studies, spatial data analysis, related to geographical locations. Time series analysiscan be applied to real valued continouco data, discrete numeric data, discrete simbolic data. Time series analysis can be divided into two classes. Frequently domain method, time domain method. It is denoted by x.

Regression analysis is a set of statistical process for estimating the relationship among variables. Regression analysis used for prediction and forecasting, it use substantial overlap with the feild of machine learning.

Regression analysis estimate the conditional expectation of the dependent variable given the indipendent variable.

Methods of the regression analysis such as the linear regression and ordinary least squares regression are parametric function of defined in terms of finite number of unknown parameters that are estimated from data. Regression can help finance and investment professionals, and can help predict from sales for company GDP growth and other conditions. The capital asset pricing model is used regression model in finance for pricing asset and discovering costs of capital.