Description

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, the daily systemic

risk measure FRM (Financial Risk Meter) is proposed for Emerging markets (FRM@

EM). The FRM@ EM is applied to capture systemic risk behavior embedded in the

returns of the 25 largest EMs’ Financial Institutions (FIs), covering the BRIMST

(Brazil, Russia, India, Mexico, South Africa, and Turkey), and thereby reflects the

financial linkages between these economies. The results indicated that the FRM of

EMs’ FIs reached its maximum during the US financial crisis following the 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 choose

the tail-event optimized portfolios and the suitable market for investment. 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 named uplifted Hierarchical Risk

Parity (upHRP) and compare it to more classical approaches. Results indicate that

the upHRP approach provides better diversification. Moreover, the upHRP portfolio

overweight low-central FIs and underweight high-central ones.