The stochastic conditional duration model: a latent variable model for the analysis of financial durations

By Luc Bauwens, David Veredas. 2004

255 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/59761100b7d95a1dd030a0a87ad75dbc295e98de

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Citations in the corpus

Properties of Realized Variance Under Alternative Sampling Schemes (2006, background): “For instance, a simple two-factor intensity process with one slowly mean reverting factor and one quickly mean reverting factor can generate serial dependence in both return volatility at low frequency and trade durations at high frequency similar to that of an SV model (Taylor, 1986) and SCD model ”
Maximization by Parts in Likelihood Inference (2005, background): “A stochastic conditional duration model proposed by Bauwens and Veredas (2004) takes the form of a state-space model, ln(di) = µ + ψi + ηi, ψi = βψi−1 + ξi, where ηi and ξi are independent errors; ηi follows a heavytailed distribution p(·|α), such as log-gamma; and ξi is Gaussian φ(·|σ).”
Autoregressive Conditional Duration Models in Finance: A Survey of the Theoretical and Empirical Literature (2008, methodology): “…ACD models for trade durations: positive autocorrelations, overdispersion, a right-skewed shape, and strong intraday seasonality (see Engle and Russell, 1998; Bauwens and Giot, 2000; Bauwens and Veredas, 2004; Bauwens et al., 2004, Fernandes and Grammig, 2006; Fernandes et al., 2006, among others).”
Predicting Time-Varying Parameters with Parameter-Driven and Observation-Driven Models (2016, background): “…normal, Student’s-t, and copula densities in table 1 with equation (2) directly leads to the stochastic conditional duration, stochastic volatility, and stochastic copula models as in Tauchen and Pitts (1983), Bauwens and Veredas (2004), Bauwens and Hautsch (2006), and Hafner and Manner (2012).”
Stochastic Conditional Intensity Processes (2006, methodology): “Following the literature on latent factor models [Taylor (1982, 1986), Bauwens and Veredas (2004) ], we assume � *i to be conditionally i.i.d.”