QMLE OF A STANDARD EXPONENTIAL ACD MODEL: ASYMPTOTIC DISTRIBUTION AND RESIDUAL CORRELATION

2014 ◽  
Vol 09 (02) ◽  
pp. 1440009 ◽  
Author(s):  
CHOR-YIU SIN

Since the seminal work by Engle and Russell, (1998), numerous studies have applied their standard/linear ACD(m,q) model (autoregressive conditional duration model of orders m and q) to fit the irregular spaced transaction data. Recently, Araichi et al. (2013) also applied the ACD model to claims in insurance. Many of these papers assume that the standardized error follows a standard exponential distribution. In this paper, we derive the asymptotic distribution of the quasi-maximum likelihood estimator (QMLE) when a standard exponential distribution is used. In other words, we provide robust standard errors for an ACD model. Applying this asymptotic theory, we then derive the asymptotic distribution of the corresponding residual autocorrelation.

2000 ◽  
Vol 220 (6) ◽  
Author(s):  
Reinhard Hujer ◽  
Joachim Grammig ◽  
Stefan Kokot

SummaryWe apply the Threshold Autoregressive Conditional Duration Model (TACD) as proposed by Zhang, Russell, and Tsay (1999) to model the after market trading duration process associated with the initial public offering of the Deutsche Telekom AG share in November of 1996. Special emphasis is devoted to the empirical specification of intra-day seasonality and to the detection of non-stationarity and structural breaks in the trading process.


1974 ◽  
Vol 11 (04) ◽  
pp. 762-770 ◽  
Author(s):  
H. A. David ◽  
J. Galambos

In a random sample of n pairs (X r , Y r ), r = 1, 2, …, n, drawn from a bivariate normal distribution, let Xr :n be the rth order statistic among the Xr and let Y [r:n] be the Y-variate paired with Xr :n . The Y[r:n] , which we call concomitants of the order statistics, arise most naturally in selection procedures based on the Xr :n . It is shown that asymptotically the k quantities k fixed, are independent, identically distributed variates. In addition, putting Rt,n for the number of integers j for which , the asymptotic distribution and all moments of n– 1 Rt, n are determined for t such that t/n → λ with 0 < λ < 1.


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