Modelling and forecasting volatility in the fishing industry: a case study of Western Cape Fisheries
Date
2017
Authors
Nzombe, Jotham
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Abstract
The Western Cape Fishing industry has been a subject of discussion in numerous papers, in
which the thrust has been to seek ways of sustaining the significantly fluctuating business.
Common risk factors have been identified and strategies for managing the fishing business in
turbulent periods have been proposed over the years. A closer examination of previous
literature as well as empirical evidence indicate that the business has less to do to control or
minimize the impact of most of its external factors, which include the Government imposed
Total Allowable Catch (TAC) limit, the variability in natural marine populations,
environmental factors and fuel price oscillations. In the interest of curbing the variability
component which is borne by the internal factors, this study brings on board a quantitative
dimension to the evaluation of the four commonly cited internal factors, namely; Earnings
Per Share (EPS), Margin of Safety (MOS), Free Cash-Flow (FCF) and the Net-Worth (NW)
on volatility of the fishing business. The performance of five large JSE-listed fishing firms:
Brimstone, Oceana, Premier Fishing, Sea Harvest and Irvin & Johnson, is investigated with
the view of modelling and forecasting their volatilities. Initially, the comparison of volatility
forecasts from symmetric and asymmetric GARCH-family models is employed. The results
of competing models are tested using cross-validation of mean error measures and the
Superior Predictive Ability (SPA) and Model Confidence Set (MCS) tests. Later, a Vector
Autoregressive (VAR) model is applied to assess the impact of the four commonly cited
internal factors on volatility. The research analysis results reveal a generally high volatility of
the Western Cape fishing sector stocks. When univariate GARCH models are applied, the
asymmetric GARCH-family models (EGARCH and GJR), with fat tails, appear dominant in
the sets of competing models for all stocks, which highlights evidence of the leverage effect
in the sector. However, GARCH (1,1), outperformed its counterparts in modelling and
forecasting Irvin & Johnson (AVI) and Oceana (OCE) stocks. In the VAR modelling process,
the Granger-causality tests indicate limited causal-relationship between EPS, MOS, FCF and
the company Net-worth with the companies’ volatility measures. The variance decomposition
of the 10-year ahead forecast of volatility indicates that volatility lag, free cash flow and networth
have the largest contribution on volatility in the long-run, followed by margin of
safety. In view of the above observations, the research discusses recommendations to the
Western Cape fishing business to improve business returns and sustainability.
Description
Dissertation submitted in partial fulfillment of the requirements for the degree of Masters of Management in Finance and Investments (MMFI) in the
Graduate School of Business Administration
University of the Witwatersrand
2017.
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Citation
Nzombe, Jotham (2017) Modelling and forecasting volatility in the fishing industry: a case study of Western Cape Fisheries, University of the Witwatersrand, Johannesburg, <http://hdl.handle.net/10539/23217>