Semiparametric Modeling of Multiple Quantiles

Leopoldo Catania; Alessandra Luati

doi:10.1016/j.jeconom.2022.11.002

Semiparametric Modeling of Multiple Quantiles

^*Corresponding author for this work

Department of Economics and Business Economics

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Abstract

We develop a semiparametric model to track a large number of quantiles of a time series. The model satisfies the condition of non-crossing quantiles and the defining property of fixed quantiles. A key feature of the specification is that the updating scheme for time-varying quantiles at each probability level is based on the gradient of the check loss function. Theoretical properties of the proposed model are derived such as weak stationarity of the quantile process and consistency of the estimators of the fixed parameters. The model can be applied for filtering and prediction. We also illustrate a number of possible applications such as: i) semiparametric estimation of dynamic moments of the observables, ii) density prediction, and iii) quantile predictions.

Original language	English
Article number	105365
Journal	Journal of Econometrics
Volume	237
Issue	2
Number of pages	16
ISSN	0304-4076
DOIs	https://doi.org/10.1016/j.jeconom.2022.11.002
Publication status	Published - Dec 2023

Keywords

Dynamic quantiles
Risk management
Score driven models

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10.1016/j.jeconom.2022.11.002

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title = "Semiparametric Modeling of Multiple Quantiles",

abstract = "We develop a semiparametric model to track a large number of quantiles of a time series. The model satisfies the condition of non-crossing quantiles and the defining property of fixed quantiles. A key feature of the specification is that the updating scheme for time-varying quantiles at each probability level is based on the gradient of the check loss function. Theoretical properties of the proposed model are derived such as weak stationarity of the quantile process and consistency of the estimators of the fixed parameters. The model can be applied for filtering and prediction. We also illustrate a number of possible applications such as: i) semiparametric estimation of dynamic moments of the observables, ii) density prediction, and iii) quantile predictions.",

keywords = "Dynamic quantiles, Risk management, Score driven models",

author = "Leopoldo Catania and Alessandra Luati",

year = "2023",

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doi = "10.1016/j.jeconom.2022.11.002",

language = "English",

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T1 - Semiparametric Modeling of Multiple Quantiles

AU - Catania, Leopoldo

AU - Luati, Alessandra

PY - 2023/12

Y1 - 2023/12

N2 - We develop a semiparametric model to track a large number of quantiles of a time series. The model satisfies the condition of non-crossing quantiles and the defining property of fixed quantiles. A key feature of the specification is that the updating scheme for time-varying quantiles at each probability level is based on the gradient of the check loss function. Theoretical properties of the proposed model are derived such as weak stationarity of the quantile process and consistency of the estimators of the fixed parameters. The model can be applied for filtering and prediction. We also illustrate a number of possible applications such as: i) semiparametric estimation of dynamic moments of the observables, ii) density prediction, and iii) quantile predictions.

AB - We develop a semiparametric model to track a large number of quantiles of a time series. The model satisfies the condition of non-crossing quantiles and the defining property of fixed quantiles. A key feature of the specification is that the updating scheme for time-varying quantiles at each probability level is based on the gradient of the check loss function. Theoretical properties of the proposed model are derived such as weak stationarity of the quantile process and consistency of the estimators of the fixed parameters. The model can be applied for filtering and prediction. We also illustrate a number of possible applications such as: i) semiparametric estimation of dynamic moments of the observables, ii) density prediction, and iii) quantile predictions.

KW - Dynamic quantiles

KW - Risk management

KW - Score driven models

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U2 - 10.1016/j.jeconom.2022.11.002

DO - 10.1016/j.jeconom.2022.11.002

M3 - Journal article

SN - 0304-4076

VL - 237

JO - Journal of Econometrics

JF - Journal of Econometrics

IS - 2

M1 - 105365

ER -

Semiparametric Modeling of Multiple Quantiles

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Keywords

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