Our paper applies a deep neural network autoencoder (AE) to detect anomalous payment
flows in Canada's retail batch clearing payments system, the Automated Clearing Settlement …

El desarrollo de metodologías que permitan el diagnóstico del estado y la tendencia de la
actividad económica es de especial importancia para la toma de decisiones de política …

In this article, we present a new approach based on dynamic factor models (DFMs) to
perform accurate nowcasts for the percentage annual variation of the Mexican Global …

This paper explores the application of machine learning (ML) techniques to nowcast
themonthlyyear-over-yeargrowthrateofbothtotalandnon-primaryGDPinPeru. Using acomprehensivedatasetthatincludesover17 …

Economic decisions are made with high uncertainty about the current and recent past
economic activity, due to the limited and imperfect available information. Therefore the …

El artículo muestra cómo los medios de pago se están convirtiendo en una herramienta
fundamental para la vinculación del cliente, de la que tanto bancos como fintechs se deben …

This paper proposes comprehensive measures of the Latin American business cycle that
help to infer the expected deepness of recessions, and strength of expansions, as they …

The recent worldwide development and widespread use of digital payment systems has
provided an opportunity to explore new sources of data for the monitoring of macroeconomic …

Kondisi ketidakpastian dan volatilitas perekonomian di awal tahun 2020 diluar perkiraan
dan perhitungan pelaku ekonomi. Wabah pandemi Covid-19 merubah wajah perekonomian …

Este documento compara el filtro de regresión de Hamilton con las metodologías
tradicionales, el algoritmo Bry-Boschan y el filtro Hodrick-Prescott, utilizando la serie del …