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FRM Financial Risk Meter for Emerging Markets

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  • Ben Amor, Souhir
  • Althof, Michael
  • Härdle, Wolfgang Karl

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.

Suggested Citation

  • Ben Amor, Souhir & Althof, Michael & Härdle, Wolfgang Karl, 2021. "FRM Financial Risk Meter for Emerging Markets," IRTG 1792 Discussion Papers 2021-002, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    • Handle: RePEc:zbw:irtgdp:2021002
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    References listed on IDEAS

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    1. Chen, Cathy Yi-Hsuan & Härdle, Wolfgang Karl & Okhrin, Yarema, 2019. "Tail event driven networks of SIFIs," Journal of Econometrics, Elsevier, vol. 208(1), pages 282-298.
    2. Yuan, Ming, 2006. "GACV for quantile smoothing splines," Computational Statistics & Data Analysis, Elsevier, vol. 50(3), pages 813-829, February.
    3. Bunda, Irina & Hamann, A. Javier & Lall, Subir, 2009. "Correlations in emerging market bonds: The role of local and global factors," Emerging Markets Review, Elsevier, vol. 10(2), pages 67-96, June.
    4. Cai, Jian & Eidam, Frederik & Saunders, Anthony & Steffen, Sascha, 2018. "Syndication, interconnectedness, and systemic risk," Journal of Financial Stability, Elsevier, vol. 34(C), pages 105-120.
    5. Alexander Haluszczynski & Ingo Laut & Heike Modest & Christoph Rath, 2017. "Linear and nonlinear market correlations: characterizing financial crises and portfolio optimization," Papers 1712.02661, arXiv.org.
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    Cited by:

    1. Wang, Ruting & Althof, Michael & Härdle, Wolfgang, 2021. "A financial risk meter for China," IRTG 1792 Discussion Papers 2021-022, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    2. Ren, Rui & Lu, Meng-Jou & Li, Yingxing & Härdle, Wolfgang Karl, 2022. "Financial Risk Meter FRM based on Expectiles," Journal of Multivariate Analysis, Elsevier, vol. 189(C).

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    JEL classification:

    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

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