Abstract:
The financial sector is vital to the economy as it encourages economic growth.
Therefore, modelling the extremes and risk management of financial stock returns
and losses is vital to economic survival. However, with limited amount
of information it can be difficult to estimate the parameters of the distributions
due to the enormous variance and heavy tails of the financial stock returns.
The problem of limited amount of information has inspired the present
study to examine and model the extreme value behaviour of the Johannesburg
Stock Exchange (JSE) financial market data using the extreme value theory
(EVT). The study employed secondary data acquired from the JSE in South
Africa, which comprises the daily total return index of the All-Share Index
(ALSI) as well as the daily USD/ZAR exchange rates. The generalised extreme
value distribution (GEVD), r-largest order statistics GEVD (rGEVD), generalised
Pareto distribution (GPD), and the Poisson point process along with the
newly proposed alternative for GEVD called blended GEVD (bGEVD) models
were applied to the five-year daily JSE financial market data. The parent distribution
of the maximum daily JSE financial market data was investigated
and the Gamma distribution was found to be the optimal parent distribution.
The block maxima method was employed in the study to fit the EVT models.
The GEVD models for the USD/ZAR exchange rate and the All Share Total
Return Index (ALSTRI) were developed using the weekly and monthly block
maxima method. Both results of weekly and monthly maxima GEVD and the
monthly rGEVD models for the ALSTRI and the USD/ZAR exchange rate can
be modelled by the Weibull and/or Gumbel family. The 100-year return levels of the monthly GEVD, bGEVD, and rGEVD models are almost equal to the
maximum observations of the financial markets, revealing that the ALSTRI
and USD/ZAR exchange rates will exceed 10802 and R18.89 respectively, at
least once in 100 years. The Poisson point process return level estimates are
quite comparable with the GPD estimates, indicating that the ALSTRI and
USD/ZAR exchange rates will surpass 17501.63 and R23.72 respectively, at
least once in 100 years. This implies that the investors will experience higher
gains in the total returns of the ALSI. The USD/ZAR exchange rate return levels
suggest that the Rand will become more unstable in the long run. Instead
of focusing merely on the traditional methods of block maxima, the use of advanced
extreme value methods that accommodate even small datasets such
as GPD, r-largest order statistics, bGEVD, and Poisson point process are encouraged.
The researcher discovered that there are no studies conducted on
bGEVD in the field of finance or financial markets. In the future, more studies
on bGEVD, vine copulas, and r-largest order bGEVD can be conducted on the
financial markets and/or finance sector. Therefore, the present study will add
value to the literature and knowledge of statistics and econometrics.