Empirical density estimation and back-testing of Value at Risk (VaR) from parametric volatility models

dc.contributor.author	Kimundi, Gillian
dc.date.accessioned	2021-05-13T08:16:46Z
dc.date.available	2021-05-13T08:16:46Z
dc.date.issued	2017
dc.description	Paper presented at the 4th Strathmore International Mathematics Conference (SIMC 2017), 19 - 23 June 2017, Strathmore University, Nairobi, Kenya.	en_US
dc.description.abstract	This paper forecasts one-day-ahead foreign exchange volatility using parametric models and compares their empirical forecasting performance of Value at Risk of five spot exchange rates; namely, the Kenyan Shilling versus the Euro, U.S. Dollar, Japanese Yen, Great British Pound and the South Africa Rand. Univariate GARCH family models (GARCH, E-GARCH, GARCH-M and FI-GARCH) are compared against the Discrete-time Stochastic Volatility Model. The daily mean exchange rates from January 2007 to December 2016 are used. Comparison analysis is divided into in-sample and out-of-sample forecasting performance which is evaluated using exceedance-based back-testing methods of conditional coverage, independence and unconditional coverage.	en_US
dc.identifier.uri	http://hdl.handle.net/11071/11873
dc.language.iso	en	en_US
dc.publisher	Strathmore University	en_US
dc.subject	Empirical density estimation	en_US
dc.subject	Back-testing	en_US
dc.subject	Value at Risk (VaR)	en_US
dc.subject	Parametric volatility models	en_US
dc.title	Empirical density estimation and back-testing of Value at Risk (VaR) from parametric volatility models	en_US
dc.type	Article	en_US

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