Extreme conditional expectile estimation in heavy-tailed heteroscedastic regression models
Extreme conditional expectile estimation in heavy-tailed heteroscedastic regression models
Page 1 The Annals of Statistics 2021, Vol. 49, No. 6, 3358–3382 https://doi.org/10.1214/21-AOS2087 …
Page 1 The Annals of Statistics 2021, Vol. 49, No. 6, 3358–3382 https://doi.org/10.1214/21-AOS2087 …
An efficient approach to quantile capital allocation and sensitivity analysis
In various fields of applications such as capital allocation, sensitivity analysis, and systemic
risk evaluation, one often needs to compute or estimate the expectation of a random …
risk evaluation, one often needs to compute or estimate the expectation of a random …
Modeling normalcy‐dominant ordinal time series: an application to air quality level
Inspired by the study of air quality level data, this article proposes a new model for the
normalcy‐dominant ordinal time series. The proposed model is based on a new zero‐one …
normalcy‐dominant ordinal time series. The proposed model is based on a new zero‐one …
Risk-parameter estimation in volatility models
C Francq, JM Zakoïan - Journal of Econometrics, 2015 - Elsevier
This paper introduces the concept of risk parameter in conditional volatility models of the
form ϵ t= σ t (θ 0) η t and develops statistical procedures to estimate this parameter. For a …
form ϵ t= σ t (θ 0) η t and develops statistical procedures to estimate this parameter. For a …
Bootstrapping the portmanteau tests in weak auto-regressive moving average models
K Zhu - Journal of the Royal Statistical Society Series B …, 2016 - academic.oup.com
The paper uses a random-weighting (RW) method to bootstrap the critical values for the
Ljung–Box or Monti portmanteau tests and weighted Ljung–Box or Monti portmanteau tests …
Ljung–Box or Monti portmanteau tests and weighted Ljung–Box or Monti portmanteau tests …
Asymptotic inference for AR models with heavy-tailed G-GARCH noises
R Zhang, S Ling - Econometric Theory, 2015 - cambridge.org
It is well known that the least squares estimator (LSE) of an AR (p) model with iid
(independent and identically distributed) noises is n1/αL (n)-consistent when the tail index α …
(independent and identically distributed) noises is n1/αL (n)-consistent when the tail index α …
Confidence intervals for conditional tail risk measures in ARMA–GARCH models
Y Hoga - Journal of Business & Economic Statistics, 2019 - Taylor & Francis
ABSTRACT ARMA–GARCH models are widely used to model the conditional mean and
conditional variance dynamics of returns on risky assets. Empirical results suggest heavy …
conditional variance dynamics of returns on risky assets. Empirical results suggest heavy …
LADE-based inference for ARMA models with unspecified and heavy-tailed heteroscedastic noises
This article develops a systematic procedure of statistical inference for the auto-regressive
moving average (ARMA) model with unspecified and heavy-tailed heteroscedastic noises …
moving average (ARMA) model with unspecified and heavy-tailed heteroscedastic noises …
Non-Gaussian quasi-likelihood estimation of SDE driven by locally stable Lévy process
H Masuda - Stochastic Processes and their Applications, 2019 - Elsevier
We address estimation of parametric coefficients of a pure-jump Lévy driven univariate
stochastic differential equation (SDE) model, which is observed at high frequency over a …
stochastic differential equation (SDE) model, which is observed at high frequency over a …