Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/230836 
Year of Publication: 
2021
Series/Report no.: 
IRTG 1792 Discussion Paper No. 2021-002
Publisher: 
Humboldt-Universität zu Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series", Berlin
Abstract: 
The fast-growing Emerging Market (EM) economies and their improved transparency and liquidity have attracted international investors. However, the external price shocks can result in a higher level of volatility as well as domestic policy instability. Therefore, an efficient risk measure and hedging strategies are needed to help investors protect their investments against this risk. In this paper, a daily systemic risk measure, called FRM (Financial Risk Meter) is proposed. The FRM@ EM is applied to capture systemic risk behavior embedded in the returns of the 25 largest EMs' FIs, covering the BRIMST (Brazil, Russia, India, Mexico, South Africa, and Turkey), and thereby reflects the financial linkages between these economies. Concerning the Macro factors, in addition to the Adrian & Brunnermeier (2016) Macro, we include the EM sovereign yield spread over respective US Treasuries and the above-mentioned countries' currencies. The results indicated that the FRM of EMs' FIs reached its maximum during the US financial crisis following by COVID 19 crisis and the Macro factors explain the BRIMST' FIs with various degrees of sensibility. We then study the relationship between those factors and the tail event network behavior to build our policy recommendations to help the investors to choose the suitable market for investment and tail-event optimized portfolios. For that purpose, an overlapping region between portfolio optimization strategies and FRM network centrality is developed. We propose a robust and well-diversified tail-event and cluster risk- sensitive portfolio allocation model and compare it to more classical approaches.
Subjects: 
FRM (Financial Risk Meter)
Lasso Quantile Regression
Network Dynamics
Emerging Markets
Hierarchical Risk Parity
JEL: 
C30
C58
G11
G15
G21
Document Type: 
Working Paper

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