The goal of a time series regression problem is best explained by a concrete example. Suppose you own an airline company and you want to predict the number of passengers you'll have next month based ...

Business forecasting is essential for the survival for companies of all sizes. The building block used by forecasters is historical data or the past performance of the business to predict future ...

This paper establishes uniform consistency results for nonparametric kernel density and regression estimators when time series regressors concerned are nonstationary null recurrent Markov chains.

Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting?

Adam Hayes, Ph.D., CFA, is a financial writer with 15+ years Wall Street experience as a derivatives trader. Besides his extensive derivative trading expertise, Adam is an expert in economics and ...

The approximate slopes of several tests of the independence of two covariance stationary time series are derived and compared. It is shown that the approximate slopes of regression tests are at least ...