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A New Approach to Volatility Modeling : The Factorial Hidden Markov Volatility Model
Maciej Augustyniak
,
Centre interuniversitaire sur le risque, les politiques économiques et l'emploi
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Description
A new model - the factorial hidden Markov volatility (FHMV) model - is proposed for financial returns and their latent variances. It is also applicable to model directly realized variances. Volatility is modeled as a product of three components: a Markov chain driving volatility persistence, an independent discrete process capable of generating jumps in the volatility, and a predictable (data-driven) process capturing the leverage effect. An economic interpretation is attached to each one of these components. Moreover, the Markov chain and jump components allow volatility to switch abruptly between thousands of states, and the transition matrix of the model is structured in such a way as to generate a high degree of volatility persistence. In-sample results on six financial time series highlight that the FHMV process compares favorably to state-of-the-art volatility models. A forecasting experiment shows that it also outperforms its competitors when predicting volatility over time horizons ranging from one to one hundred days.
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Book Details
Title
A New Approach to Volatility Modeling
Subtitle
The Factorial Hidden Markov Volatility Model
Contributors
Maciej Augustyniak
,
Luc Bauwens
,
Arnaud Dufays
,
Centre interuniversitaire sur le risque
,
les politiques économiques et l'emploi
Publisher
Centre interuniversitaire sur le risque, les politiques économiques et l'emploi
Publication date
2017-12-01
Pages
33
Subjects
A New Approach to Volatility Modeling
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