The impact of transaction duration, volume and direction on price dynamics and volatility

DOI10.1080/14697680903405742zbMath1210.91152OpenAlexW1967892033MaRDI QIDQ3169221

Anthony S. Tay, Mitch Warachka, Christopher Ting, Yiu Kuen Tse

Publication date: 28 April 2011

Published in: Quantitative Finance (Search for Journal in Brave)

Full work available at URL: https://ink.library.smu.edu.sg/soe_research/1381

zbMATH Keywords

applied econometricsforecasting abilityeconometric theoryeconometrics of financial markets

Mathematics Subject Classification ID

Applications of statistics to actuarial sciences and financial mathematics (62P05) Statistical methods; risk measures (91G70) Economic time series analysis (91B84)

Related Items (3)

Extension and verification of the asymmetric autoregressive conditional duration models ⋮ Intraday value-at-risk: an asymmetric autoregressive conditional duration approach ⋮ Review of statistical approaches for modeling high-frequency trading data

Cites Work

• Nonparametric specification tests for conditional duration models
• The stochastic conditional duration model: a latent variable model for the analysis of financial durations
• Stochastic volatility duration models
• Capturing common components in high-frequency financial time series: a multivariate stochastic multiplicative error model
• Autoregressive Conditional Duration: A New Model for Irregularly Spaced Transaction Data
• Non‐monotonic hazard functions and the autoregressive conditional duration model
• The Econometrics of Ultra-high-frequency Data
• A nonlinear autoregressive conditional duration model with applications to financial transaction data

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