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Abstract Disease modelling has had considerable policy impact during the ongoing COVID-19 pandemic, and it is increasingly acknowledged that combining multiple models can improve the reliability of outputs. Here we report insights from ten weeks of collaborative short-term forecasting of COVID-19 in Germany and Poland (12 October–19 December 2020). The study period covers the onset of the second wave in both countries, with tightening non-pharmaceutical interventions (NPIs) and subsequently a decay (Poland) or plateau and renewed increase (Germany) in reported cases. Thirteen independent teams provided probabilistic real-time forecasts of COVID-19 cases and deaths. These were reported for lead times of one to four weeks, with evaluation focused on one- and two-week horizons, which are less affected by changing NPIs. Heterogeneity between forecasts was considerable both in terms of point predictions and forecast spread. Ensemble forecasts showed good relative performance, in particular in terms of coverage, but did not clearly dominate single-model predictions. The study was preregistered and will be followed up in future phases of the pandemic.
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Stock market bubbles and the forecastability of gold returns and volatility
Abstract In this article, multi‐scale LPPLS confidence indicator approach is used to detect both positive and negative bubbles at short‐, medium‐, and long‐term horizons for the stock markets of the G7 and the BRICS countries. This enables detecting major crashes and rallies in the 12 stock markets over the period of the 1st week of January, 1973 to the 2nd week of September, 2020. Similar timing of strong (positive and negative) LPPLS indicator values across both G7 and BRICS countries was also observed, suggesting interconnectedness of the extreme movements in these stock markets. Next, these indicators were utilized to forecast gold returns and its volatility, using a method involving block means of residuals obtained from the popular LASSO routine, given that the number of covariates ranged between 42 and 72, and gold returns demonstrated a heavy upper tail. The finding was, these bubbles indicators, particularly when both positive and negative bubbles are considered simultaneously, can accurately forecast gold returns at short‐ to medium‐term, and also time‐varying estimates of gold returns volatility to a lesser extent. The results of this paper have important implications for the portfolio decisions of investors who seek a safe haven during boom‐bust cycles of major global stock markets.
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- Award ID(s):
- 2124222
- PAR ID:
- 10563178
- Publisher / Repository:
- Wiley
- Date Published:
- Journal Name:
- Applied Stochastic Models in Business and Industry
- ISSN:
- 1524-1904
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1002/asmb.2887
