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No one could have predicted the COVID 19 pandemic. Especially the first phase of this sudden crisis was marked by drastic drops - in turnover and share prices, among other things. Even after more than a year, this sudden, unpredictable downward movement is still a nightmare for any financial forecaster. Thus, predictions made were and are often far from reality. Therefore, the models used need adjustments to increase the forecast quality. But hardly anyone has experience with forecasts in crises of this kind, so it is unclear how best to make these adjustments.
The effects of climate change can also upset our short- and long-term revenue projections: EPFL (École Polytechnique Fédérale de Lausanne) estimates that climate change costs the Swiss state up to ten billion Swiss francs per year. In neighbouring Germany, climate change is perceived (according to COVID-19) as one of the biggest problems currently facing society.
This white paper discusses what we can learn from the pandemic for future forecasting in times of crisis. We address what stabilising strategy - looking back at the first phase of the COVID-19 pandemic - could have generated solid forecasts. The aim of this approach is to have better tools at hand in the future when shocks occur. We highlight the key problems in forecasting in uncertain times and illustrate how to address them.
- Dr Dominik Bertsche (Predictive Analytics Expert @ s-peers AG)
- Dr. Yvonne Avaro (Head of Marketing & Insights @ s-peers AG)
- You can find out more about the employees of s-peers Ag here.
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