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Leverage effect for volatility with generalized Laplace error

Podgorski, Krzysztof LU and Javed, Farrukh LU (2014) In Economic Quality Control 29(2). p.157-166
Abstract
We propose a new model that accounts for the asymmetric response of volatility to positive (`good news') and negative (`bad news') shocks in economic time series – the so-called leverage effect. In the past, asymmetric powers of errors in the conditionally heteroskedastic models have been used to capture this effect. Our model is using the gamma difference representation of the generalized Laplace distributions that efficiently models the asymmetry. It has one additional natural parameter, the shape, that is used instead of power in the asymmetric power models to capture the strength of a long-lasting effect of shocks. Some fundamental properties of the model are provided including the formula for covariances and an explicit form for the... (More)
We propose a new model that accounts for the asymmetric response of volatility to positive (`good news') and negative (`bad news') shocks in economic time series – the so-called leverage effect. In the past, asymmetric powers of errors in the conditionally heteroskedastic models have been used to capture this effect. Our model is using the gamma difference representation of the generalized Laplace distributions that efficiently models the asymmetry. It has one additional natural parameter, the shape, that is used instead of power in the asymmetric power models to capture the strength of a long-lasting effect of shocks. Some fundamental properties of the model are provided including the formula for covariances and an explicit form for the conditional distribution of `bad' and `good' news processes given the past – the property that is important for statistical fitting of the model. Relevant features of volatility models are illustrated using S&P 500 historical data. (Less)
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author
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organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Heavy Tails, Volatility Clustering, Generalized Asymmetric Laplace Distribution, Leverage Effect, Conditional Heteroskedasticity, Asymmetric Power Volatility, GARCH Models
in
Economic Quality Control
volume
29
issue
2
pages
157 - 166
publisher
De Gruyter
ISSN
1869-6147
DOI
10.1515/eqc-2014-0015
language
English
LU publication?
yes
id
b75268f1-1b5b-4d3c-a6e7-2ca46aeee97e (old id 7867590)
date added to LUP
2016-04-01 13:47:15
date last changed
2018-11-21 20:19:51
@article{b75268f1-1b5b-4d3c-a6e7-2ca46aeee97e,
  abstract     = {{We propose a new model that accounts for the asymmetric response of volatility to positive (`good news') and negative (`bad news') shocks in economic time series – the so-called leverage effect. In the past, asymmetric powers of errors in the conditionally heteroskedastic models have been used to capture this effect. Our model is using the gamma difference representation of the generalized Laplace distributions that efficiently models the asymmetry. It has one additional natural parameter, the shape, that is used instead of power in the asymmetric power models to capture the strength of a long-lasting effect of shocks. Some fundamental properties of the model are provided including the formula for covariances and an explicit form for the conditional distribution of `bad' and `good' news processes given the past – the property that is important for statistical fitting of the model. Relevant features of volatility models are illustrated using S&P 500 historical data.}},
  author       = {{Podgorski, Krzysztof and Javed, Farrukh}},
  issn         = {{1869-6147}},
  keywords     = {{Heavy Tails; Volatility Clustering; Generalized Asymmetric Laplace Distribution; Leverage Effect; Conditional Heteroskedasticity; Asymmetric Power Volatility; GARCH Models}},
  language     = {{eng}},
  number       = {{2}},
  pages        = {{157--166}},
  publisher    = {{De Gruyter}},
  series       = {{Economic Quality Control}},
  title        = {{Leverage effect for volatility with generalized Laplace error}},
  url          = {{http://dx.doi.org/10.1515/eqc-2014-0015}},
  doi          = {{10.1515/eqc-2014-0015}},
  volume       = {{29}},
  year         = {{2014}},
}