Forecasting in Economics and Finance

Abstract

Practices used to address economic forecasting problems have undergone substantial changes over recent years. We review how such changes have influenced the ways in which a range of forecasting questions are being addressed. We also discuss the promises and challenges arising from access to big data. Finally, we review empirical evidence and experience accumulated from the use of forecasting methods to a range of economic and financial variables.

Some Aspects of Forecasting as Part of Macroeconomic Analysis.

“…Crisis of 1929-1933. Abroad was a powerful impetus in the development of forecasting and planning [2] . Planning at the macro level abroad arises for the first time in the 1930s.…”

Balanced Growth Approach to Tracking Recessions

“…24 We investigated a number of alternative time windows and arrived at similar qualitative results. 25 Depending upon an eventual decision context, alternative metrics could be used (see Elliott and Timmermann 2016). 26 It is important to note that the MAE and RMSE have inherent shortcomings because they measure a single variable's forecast properties at a single horizon (see Clements and Hendry 1993).…”

Calm Before the Storm: An Early Warning Approach Before and During the COVID-19 Crisis

“…In principal, moving averages filtering reduces white noise optimally by focusing out the sharpest edge points. This guideline follows the relevant network and finance literature (Joseph et al, 2017;Zhong and Enke, 2017;Elliott and Timmermann, 2016;Chen et al, 2016;Ferreira and Santa-Clara, 2011;Vaisla and Bhatt, 2010;Atsalakis and Valavanis, 2009;Cont, 2001;Granger, 1992;Balvers et al, 1990;Fama, 1976).…”

“…Research into systemic risk and predictive modelling widely uses asset return indicators, and applies both non-parametric self-learning techniques and parametric statistical methods (Joseph et al, 2017;Zhong and Enke, 2017;Joseph et al, 2016;Elliott and Timmermann, 2016;Chen et al, 2016;Ferreira and Santa-Clara, 2011;Vaisla and Bhatt, 2010;Atsalakis and Valavanis, 2009;Cont, 2001;Granger, 1992;Balvers et al, 1990). We complement Joseph et al (2017Joseph et al ( , 2016; Atsalakis and Valavanis (2009) and Zhong and Enke (2017) by pre-processing our data with an appropriate window choice with the aim to avoid aberrations caused by discontinuations in returns data.…”