Department of Statistics / MSc (Statistics) / The ripple e ect of a stock market crash due to extremal dependence is a global issue
with key attention and it is at the core of all modelling e orts in risk management.
Two methods of extreme value theory (EVT) were used in this study to model
equity risk and extremal dependence in the tails of stock market indices from four
African emerging markets: South Africa, Nigeria, Kenya and Egypt. The rst is the
\bivariate-threshold-excess model" and the second is the \point process approach".
With regards to the univariate analysis, the rst nding in the study shows
in descending hierarchy that volatility with persistence is highest in the South African
market, followed by Egyptian market, then Nigerian market and lastly, the Kenyan
equity market. In terms of risk hierarchy, the Egyptian EGX 30 market is the
most risk-prone, followed by the South African JSE-ALSI market, then the Nigerian
NIGALSH market and the least risky is the Kenyan NSE 20 market. It is therefore
concluded that risk is not a brainchild of volatility in these markets.
For the bivariate modelling, the extremal dependence ndings indicate that
the African continent regional equity markets present a huge investment platform for
investors and traders, and o er tremendous opportunity for portfolio diversi cation
and investment synergies between markets. These synergistic opportunities are due
to the markets being asymptotic (extremal) independent or (very) weak asymptotic
dependent and negatively dependent. This outcome is consistent with the ndings
of Alagidede (2008) who analysed these same markets using co-integration analysis.
The bivariate-threshold-excess and point process models are appropriate for modelling
the markets' risks. For modelling the extremal dependence however, given the same
marginal threshold quantile, the point process has more access to the extreme observations
due to its wider sphere of coverage than the bivariate-threshold-excess model. / NRF
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:univen/oai:univendspace.univen.ac.za:11602/1356 |
| Date | 18 May 2019 |
| Creators | Samuel, Richard Abayomi |
| Contributors | Sigauke, Caston, Bere, Aphonce |
| Source Sets | South African National ETD Portal |
| Language | English |
| Detected Language | English |
| Type | Dissertation |
| Format | 1 online resource (xvii, 156 leaves:: illustrations) |
| Rights | University of Venda |
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