Recent studies indicate that systemic risk has predictive power over severe economic downturns. We propose a novel methodology that employs sparsity and targeting approaches to optimally select and combine systemic risk measures to forecast the tail of a given economic variable. Out-of-sample analysis shows that the optimal combination of systemic risk metrics may vary over time, forecasting horizons and economic proxies. Moreover, a few systemic risk measures contain all the important information for capturing the relation between systemic risk and real economy; therefore, a fixed and static combination approach may not be optimal, and the flexible parsimonious extension we introduce leads to improvement in forecasting performance.

Systemic risk and severe economic downturns: A targeted and sparse analysis

Caporin M.
Membro del Collaboration Group
;
2022

Abstract

Recent studies indicate that systemic risk has predictive power over severe economic downturns. We propose a novel methodology that employs sparsity and targeting approaches to optimally select and combine systemic risk measures to forecast the tail of a given economic variable. Out-of-sample analysis shows that the optimal combination of systemic risk metrics may vary over time, forecasting horizons and economic proxies. Moreover, a few systemic risk measures contain all the important information for capturing the relation between systemic risk and real economy; therefore, a fixed and static combination approach may not be optimal, and the flexible parsimonious extension we introduce leads to improvement in forecasting performance.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11577/3410452
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