Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/178564
Authors: 
Pypko, Sergii
Year of Publication: 
2015
Citation: 
[Journal:] Journal of Risk and Financial Management [ISSN:] 1911-8074 [Volume:] 8 [Year:] 2015 [Issue:] 3 [Pages:] 311-336
Abstract: 
We build a discrete-time non-linear model for volatility forecasting purposes. This model belongs to the class of threshold-autoregressive models, where changes in regimes are governed by past returns. The ability to capture changes in volatility regimes and using more accurate volatility measures allow outperforming other benchmark models, such as linear heterogeneous autoregressive model and GARCH specifications. Finally, we show how to derive closed-form expression for multiple-step-ahead forecasting by exploiting information about the conditional distribution of returns.
Subjects: 
volatility forecast
non-linear time series models
Persistent Identifier of the first edition: 
Creative Commons License: 
https://creativecommons.org/licenses/by/4.0/
Document Type: 
Article

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