Abstract
A topic of recent interest in financial risk management is the predictive accuracy of Value-at-risk (VaR) models for adequate capitalization under different market conditions (or regimes). This article assesses the forecasting performance of popular GARCH-based volatility models in the context of VaR estimation. In particular, we conduct a cross-regime analysis between time periods whereby market conditions experiences a shift. Stock returns data from the FTSE/JSE Africa All Share index were selected for the evaluation of both long and short positions of trade. Despite prior findings of the long memory models dominating in the South African financial market, we conclude that such dominance does not necessary hold when assessed under different regimes of the market. Moreover, our findings indicated a need for implementations of model switching policies, which may provide significant improvements in forecasting and minimize chances of VaR estimates falling short of actual trading losses.
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Notes
This is done in line with prior research. Alternative distributions have also been suggested in the literature, but are difficult to implement (see Huisman et al, 1998) and omitted as a result. This, however, does not influence the main results, which is to demonstrate the consistency of VaR models across different market conditions.
For the remainder of the article we will refer to log returns as just returns.
Which is of greater interest and practical significance.
By definition, the failure rates for long trading positions are the number of times where the forecasted VaR is exceeded by actual returns. Which is equivalent to percentage of negative returns less than the one-step-ahead VaR forecast. The success rates for our short positions of trade are conversely defined in a similar manner.
As part of the listed shares in the South African market are in a developed nature, whereas the others are more of an emerging.
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Acknowledgements
Timmy Elenjical and Patrick Mwangi would like to thank the University of Cape Town, where they co-authored this work in their personal capacity as students, for its continued support.
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Elenjical, T., Mwangi, P., Panulo, B. et al. A comparative cross-regime analysis on the performance of GARCH-based value-at-risk models: Evidence from the Johannesburg stock exchange. Risk Manag 18, 89–110 (2016). https://doi.org/10.1057/rm.2016.4
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DOI: https://doi.org/10.1057/rm.2016.4