Risks in emerging markets equities: Time-varying versus spatial risk analysis
Abstract
For 12 emerging market economies (EMEs) time-varying and spatial risks are contrasted to assess systemic vulnerabilities that may affect equity returns as well as to aid portfolio diversification as a risk-minimising tool for Eurozone Crisis-Global Financial Crisis (EZC-GFC) and post-GFC periods. We use the Fissler & Ziegel (2016) loss (FZL) function for its desirable elicitability feature to rank competing models of time-varying tail risk estimates whereas nonparametric spatial autocorrelations, based on Tobler's first law of geography, are applied to the Bank for International Settlement's Global Liquidity Indicators (GLIs) to estimate time-invariant risk. In the process we have proposed the "Financial Distance" as an extension of Ghemawat's (2001) CAGE distance dimensions. The results reveal that the overall spatial autocorrelation between the 12 EMEs is smaller and negative for post-GFC as opposed to positive and bigger for Eurozone Crisis and Global Financial Crisis (EZC-GFC) periods. Among other things, this suggests EMEs may have employed prudent liquidity policies to enhance their resilience to systemic susceptibilities having learnt bitter experiences during crisis episodes. For investors, international portfolio diversification tend to yield its expected risk-minimising outcomes during this period. We find this revelation renders irrelevant the rankings of characteristic FZL estimates for both periods since time-invariant systematic debacles have no respect for time-varying tail risks estimates of specific equities.
- Publication:
-
Physica A Statistical Mechanics and its Applications
- Pub Date:
- March 2020
- DOI:
- 10.1016/j.physa.2019.123474
- Bibcode:
- 2020PhyA..54223474O
- Keywords:
-
- C10;
- C14;
- C8;
- G1