The Logarithmic ACD Model: An Application to the Bid-Ask Quote Process of Three NYSE Stocks

By Luc Bauwens, P. Giot. 2000

436 citations recorded by the source corpus.

Subfields: Accounting, Management Information Systems, Strategy and Management

View Paper: https://www.semanticscholar.org/paper/3aca60ff243f1c55c095b1ce788d30f7dc6f9b0f

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Citations in the corpus

The stochastic conditional duration model: a latent factor model for the analysis of financial durations (2004, positive): “This is done by specifying a stationary AR(1) process on the logarithm of the latent factor, following the idea of the log-ACD model (Bauwens and Giot 1999).”
Market risk models for intraday data (2005, background): “The Log-ACD model (Bauwens and Giot, 2000) for the standardized price durations (i.e. the price durations of which the intraday seasonality has been removed, see Section 3) is defined by where the i are IID and follow a Weibull(1,γ) distribution and ψ i is the logarithm of the conditional…”
Nonparametric specification tests for conditional duration models (2005, methodology): “Bauwens and Giot’s (2000) logarithmic ACD model provides a more suitable framework for testing market microstructure hypotheses as it avoids some of the parameter restrictions implied by the original ACD specification.”
Capturing the Zero: A New Class of Zero-Augmented Distributions and Multiplicative Error Processes (2010, positive): “We specify μt in terms of a logarithmic specification as proposed by Bauwens and Giot (2000) for autoregressive conditional duration (ACD) models which does not require parameter constraints to ensure the positivity of μt.”
Mixture Processes for Financial Intradaily Durations (2004, methodology): “In order to avoid them, a logarithmic version, denoted as Logarithmic ACD model, was proposed by Bauwens and Giot (2000). It is characterized by an exponential formulation of the conditional expected duration, that is”
Duration, Volume and Volatility Impact of Trades (2005, neutral): “Bauwens and Giot (2000, 2003) suggest modeling the logarithm of durations.”
The stochastic conditional duration model: a latent variable model for the analysis of financial durations (2004, background): “14 The digamma function is d ln ( )=d = ′( )= ( ), and the trigamma function is d ( )=d ; see Abramovitz and Stegun (1970, Chapter 6). 15 A deeper analysis of the consequence of error misspeci$cation is provided in Fourgeaud et al. (1988). They discuss how heterogeneity aDects the estimates in terms”
Evaluating Models of Autoregressive Conditional Duration (2006, methodology): “These include the logarithmic ACD model of Bauwens and Giot (2000) and the threshold ACD model of Zhang, Russell, and Tsay (2001).”
Autoregressive Conditional Duration Models in Finance: A Survey of the Theoretical and Empirical Literature (2008, methodology): “Among the most relevant variables for investigating market microstructure effects, the lags of the following are typically used in analyses of stock markets (Engle and Russell, 1998; Bauwens and Giot, 2000; Bauwens and Giot, 2003; Bauwens and Veredas, 2004).”
A family of autoregressive conditional duration models (2006, methodology): “Bauwens and Giot (2000) work with a logarithmic version of the ACD model that avoids the nonnegativeness constraints implied by the original specification so as to facilitate the testing of market microstructure hypotheses. Bauwens and Veredas (1999) propose the stochastic conditional duration proce”