A flexible inference method for an autoregressive stochastic volatility model with an application to risk management
The Autoregressive Stochastic Volatility (ARSV) model is a discrete-time stochastic volatility model that can model the financial returns time series and volatilities. This model is relevant for risk management. However, existing inference methods have various limitations on model assumptions. In th...
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| Language: | English |
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University of British Columbia
2017
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| Online Access: | http://hdl.handle.net/2429/61313 |