Devdiscourse

Time series AI models can mislead policymakers through structural bias

Time series forecasting requires simplifying complex environments into quantifiable variables. These simplifications, while ...
Nature

Time Series and Spatial Modelling

Time series and spatial modelling encompass a wide array of statistical and computational techniques aimed at deciphering complex temporal trends and spatial dependencies within diverse natural and ...
JSTOR Daily

A semiparametric approach for modelling multivariate nonlinear time series

The Canadian Journal of Statistics / La Revue Canadienne de Statistique, Vol. 47, No. 4 (December/décembre 2019), pp. 668-687 (20 pages) In this article, a semiparametric time-varying nonlinear vector ...
Agence France-Presse

Ant International Open Sources Time-Series Transformer AI Model to Enable More Businesses to Benefit from AI-Powered Forecasting

Deployed internally at Ant International to manage cashflow and FX exposure on an hourly, daily and weekly basis, Falcon TST has achieved accuracy rates of over 90%, and cut the company’s FX costs by ...
International Monetary Fund

GDP Nowcasting Performance of Traditional Econometric Models vs Machine-Learning Algorithms: Simulation and Case Studies

Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in ...