Page 249 - Contributed Paper Session (CPS) - Volume 6
P. 249

CPS1909 Retius C. et al.

                             Evaluating South Africa’s market risk using
                                 APARCH model under heavy-tailed
                                             distributions
                               Retius Chifurira, Knowledge Chinhamu
                School of Mathematics, Statistics and Computer Science, University of KwaZulu-Natal,
                                     Westville Campus, South Africa

            Abstract
            Estimating  Value-at-risk  (VaR)  of  stock  returns,  especially  from  emerging
            economies,  has  recently  attracted  attention  of  both  academics  and  risk
            managers. VaR and other risk management tools, such as expected shortfall
            (conditional VaR) are highly dependent on an appropriate set of underlying
            distributional assumptions. Thus, identifying a distribution that best captures
            all aspects of financial returns is of great interest to both academics and risk
            managers. This study compares the relative performance of the GARCH-type
            model  combined  with  heavy-tailed  distributions,  namely;  the  Student- t
            distribution,  Pearson  type-IV  distribution  (PIVD),  Generalized  Pareto
            distribution (GPD) and stable distribution (SD) in estimating Value-at-Risk of
            FTSE/JSE all-share price index (ALSI) returns. Model adequacy is checked by
            using the Kupiec likelihood ratio test. The advantage of the proposed models
            lies in their ability to capture volatility clustering and the leverage effect on the
            returns, through the GARCH framework  and at the same time model their
            heavy-tailed behaviour. The main findings indicate that the Asymmetric power
            ARCH (APARCH) model combined with heavy-tailed distributions performed
            well in modelling South African’s market risk. Thus, APARCH model combined
            with heavy-tailed distributions provides a good alternative for modelling stock
            returns. The outcomes of this study are expected to be of salient value to
            financial  analysts,  portfolio  managers,  risk  managers  and  financial  market
            researchers, thus giving a better understanding of the South African market.

            Keywords
            Asymmetric  volatility  models;  Value-at-Risk;  Heavy-tailed  distributions;
            FTSE/JES All share price index

            1.  Introduction
                South Africa is one of the most diverse and promising emerging markets
            globally. It is the sixth most outstanding in the emerging economies category,
            with vast opportunities within its border. It is a gateway to the rest of the
            African continent (a market of more than one billion people) and is a  key
            investment location. It is the economic powerhouse of Africa and forms part
            of BRICS group of countries which includes Brazil, Russia, India and China.
            South  African  stock  market,  Johannesburg  Stock  Exchange  (JSE)  is  Africa’s

                                                               238 | I S I   W S C   2 0 1 9
   244   245   246   247   248   249   250   251   252   253   254