This paper presents a systematic review of research papers on nowcasting economic
activity. The study summarizes the state‐of‐the‐art nowcasting approaches and methods …

Monitoring economic conditions in real time, or nowcasting, and Big Data analytics share
some challenges, sometimes called the three “Vs”. Indeed, nowcasting is characterized by …

In this paper, we develop a financial stress index (FSI) that can be used as a real-time
composite indicator for the state of financial stability. We take 17 financial variables from …

We analyze ways of incorporating low frequency information into models for the prediction of
high frequency variables. In doing so, we consider the two existing versions of the mixed …

We introduce a combined density nowcasting (CDN) approach to dynamic factor models
(DFM) that in a coherent way accounts for time-varying uncertainty of several model and …

We use a mixed-frequency vector autoregression to obtain intraquarter point and density
forecasts as new, high frequency information becomes available. This model, delineated in …

The literature on mixed-frequency models is relatively recent and has found applications
across economics and finance. The standard application in economics considers the use of …

Most macroeconomic series failed to capture the sharp fluctuations during the COVID-19
pandemic. Also, it proved difficult to extract business cycle information from alternative high …

For the purpose of forecasting key macroeconomic or financial variables from a panel of time
series variables, we adopt the dynamic factor model and propose a weighted likelihood …

Recent research finds that forecasting electricity prices is very relevant. In many
applications, it might be interesting to predict daily electricity prices by using their own lags …