A comparative cross-regime analysis on the performance of GARCH-based value-at-risk models: Evidence from the Johannesburg stock exchange
Barry Panulo and
Chun-Sung Huang ()
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Timmy Elenjical: Department of Finance and Tax, University of Cape Town
Patrick Mwangi: Department of Finance and Tax, University of Cape Town
Barry Panulo: Bertha Centre for Social Innovation and Entrepreneurship, Graduate School of Business, University of Cape Town
Chun-Sung Huang: Department of Finance and Tax, University of Cape Town
Risk Management, 2016, vol. 18, issue 2, 89-110
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.
Keywords: risk management; Johannesburg stock exchange; conditional variance; market regimes; Kupiec test; dynamic quantile test (search for similar items in EconPapers)
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