Value at risk (VaR) backtesting 'Evidence from a South African market portfolio'
| dc.contributor.author | Katsenga, Gerald Z | |
| dc.date.accessioned | 2014-03-18T09:07:08Z | |
| dc.date.available | 2014-03-18T09:07:08Z | |
| dc.date.issued | 2014-03-18 | |
| dc.description.abstract | Value at Risk (VaR) has emerged as one of the most prominent risk measurement techniques in finance. It is a measure that quantifies the worst expected loss over a given confidence level and target horizon, under normal market conditions. In this thesis, the concept of VaR as an invaluable tool for financial risk management is explained, and a theoretical but detailed description of some of the methods of VaR computation are presented, with a key emphasis on the assumptions and shortcomings of these models. A discussion that is preceded by a presentation on the calculation of portfolio returns and the choice of VaR parameters as key determinants in the choice of an appropriate VaR model. In light of the shortcomings to VaR measures, a number of backtesting techniques that examine the accuracy of VaR estimates are presented and reviewed. The review of these VaR validation methods is both from a theory and practice perspective. The unconditional coverage, independence property and the conditional coverage property are defined and their relation to backtesting methods discussed. The backtesting techniques presented are classified by whether they test for the unconditional coverage property, independence property or the conditional coverage (joint) property of a VaR measure. The backtesting methods presented and discussed in this work are then utilized in empirically validating the accuracy of one of the most widely used VaR method in South Africa, the historical simulation. The examination of VaR estimates from this model is applied on an ‘actual’ interest rate portfolio. The outcome of the statistical backtests show positive results of accurate performance of the model at lower confidence levels, and an underestimation of risk at higher VaR confidence levels. However, when hedge positions are excluded from the portfolio the model’s performance in accurately estimating VaR is questionable. | en_ZA |
| dc.identifier.uri | http://hdl.handle.net10539/14200 | |
| dc.language.iso | en | en_ZA |
| dc.title | Value at risk (VaR) backtesting 'Evidence from a South African market portfolio' | en_ZA |
| dc.type | Thesis | en_ZA |