Stochastic volatility models for exchange rates and their estimation using quasi-maximum-likelihood methods: an application to the South African Rand |
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Authors: | M. V. Kulikova |
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Affiliation: | CEMAT, Instituto Superior Técnico , Technical University of Lisbon , Av. Rovisco Pais, 1049-001 , Lisboa , Portugal |
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Abstract: | This paper is concerned with the volatility modeling of a set of South African Rand (ZAR) exchange rates. We investigate the quasi-maximum-likelihood (QML) estimator based on the Kalman filter and explore how well a choice of stochastic volatility (SV) models fits the data. We note that a data set from a developing country is used. The main results are: (1) the SV model parameter estimates are in line with those reported from the analysis of high-frequency data for developed countries; (2) the SV models we considered, along with their corresponding QML estimators, fit the data well; (3) using the range return instead of the absolute return as a volatility proxy produces QML estimates that are both less biased and less variable; (4) although the log range of the ZAR exchange rates has a distribution that is quite far from normal, the corresponding QML estimator has a superior performance when compared with the log absolute return. |
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Keywords: | exchange rates quasi-maximum-likelihood estimation Kalman filter stochastic volatility adaptive filtering |
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