Intraday value-at-risk: an asymmetric autoregressive conditional duration approach
type: Item
instance of: scholarly article
title: Intraday value-at-risk: an asymmetric autoregressive conditional duration approach
zbMATH Open document ID: 1337.91148
author: Shouwei Liu
author: Yiu Kuen Tse
published in: Journal of Econometrics
publication date: 2015-10-30T00:00:00Z
full work available at URL: https://ink.library.smu.edu.sg/soe_research/1871
Mathematics Subject Classification ID: 91G70
Mathematics Subject Classification ID: 62P05
zbMATH DE Number: 6502489
zbMATH Keywords: high-frequency transaction data
zbMATH Keywords: market microstructure noise
zbMATH Keywords: asymmetric autoregressive conditional duration model
zbMATH Keywords: intraday value-at-risk
zbMATH Keywords: backtesting
describes a project that uses: CAViaR
MaRDI profile type: Publication
OpenAlex ID: W1970560850
cites work: The Econometrics of Ultra-high-frequency Data
cites work: Autoregressive Conditional Duration: A New Model for Irregularly Spaced Transaction Data
cites work: The impact of transaction duration, volume and direction on price dynamics and volatility
DOI: 10.1016/J.JECONOM.2015.03.035
description: scientific article; zbMATH DE number 6502489