  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 and 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 in-vestment 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
