Volatility forecast in crises and expansions
Sergii Pypko (Department of Economics, University of Western Ontario)
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.
Year of publication: |
September 2015
|
---|---|
Authors: | Pypko, Sergii |
Published in: |
Journal of risk and financial management : JRFM. - Basel : MDPI, ISSN 1911-8074, ZDB-ID 2739117-6. - Vol. 8.2015, 3, p. 311-336
|
Subject: | volatility forecast | non-linear time series models | Theorie | Theory | Volatilität | Volatility | Prognoseverfahren | Forecasting model | Zeitreihenanalyse | Time series analysis | ARCH-Modell | ARCH model |
Saved in:
freely available
Type of publication: | Article |
---|---|
Type of publication (narrower categories): | Aufsatz in Zeitschrift ; Article in journal |
Language: | English |
Other identifiers: | 10.3390/jrfm8030311 [DOI] hdl:10419/178564 [Handle] |
Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10011545111
Saved in favorites
Similar items by subject
-
Forecasting volatility in commodity markets with long-memory models
Alfeus, Mesias, (2022)
-
A novel cluster HAR-type model for forecasting realized volatility
Yao, Xingzhi, (2019)
-
Qu, Hui, (2022)
- More ...
Similar items by person
-
Volatility forecast in crises and expansions
Pypko, Sergii, (2015)
- More ...