Volatility Forecast in Crises and Expansions

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 a...

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Bibliographic Details
Main Author: Sergii Pypko
Format: Article
Language:English
Published: MDPI AG 2015-08-01
Series:Journal of Risk and Financial Management
Subjects:
Online Access:http://www.mdpi.com/1911-8074/8/3/311
Description
Summary: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.
ISSN:1911-8074