“Advances in Forecasting in Macroeconomics and Financial Markets”
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A special issue of the Journal of Forecasting will publish a selection of papers on the issue “Advances in Forecasting in Macroeconomics and Financial Markets”.Guest Editors: Anindya Banerjee (University of Birmingham); Stephen G. Hall (Leicester University), Georgios P. Kouretas (Athens University of Economics and Business), George S. Tavlas (Bank of Greece and Hoover Institution).During the last ten to fifteen years, a range of forecasting techniques has been developed and existing techniques have been extended and improved. These techniques include dynamic factor models, factor augmented VARS, recursive estimation, time varying parameters, and neural networks and machine learning. In addition, recent work on forecasting has explored ways to use combinations of techniques to take uncertainties into account (for example, by assigning probabilities to each model and updating through Bayesian learning) and improve forecasts. These techniques have been applied to a variety of data, including very high frequency data and so-called big data. This special issue would consist of papers presented at the 26th International Conference on Macroeconomic Analysis and International Finance to be held at the University of Crete during May 26-28, 2022. Papers that would be included in the special issue would apply these (and other) methods to a range of macroeconomic and financial-market variables, for example, exchange rates, inflation, output, share prices, bond yields, and commodity prices. These techniques, including forecast combinations, will be compared with more traditional forecasting tools including ARIMA models and the workhorse random walk model. In line with the conference orientation, papers selected would emphasize international comparisons of forecasting performance. |