416 – Contributed Oral Poster Presentations: Business and Economic Statistics Section
Inference for Duration Models Using Estimating Functions
Julieta Frank
University of Manitoba
Melody Ghahramani
University of Winnipeg
Aerambamoorthy Thavaneswaran
University of Manitoba
A class of martingale estimating functions provides a more convenient framework for studying inference for nonlinear time series models relative to other widely used methods such as maximum likelihood estimation. For example, the estimating function approach does not assume any particular distribution for the innovation. Liang et al. (2011) have recently shown that quadratic estimating functions are more informative than linear estimating functions for Random Coefficient Autoregresive (RCA) models. Duration models are commonly used to model the behaviour of irregularly time-spaced financial data. The method is used to study the inference for the parameters of a new class of multiplicative Random Coefficient Autoregressive Conditional Duration (RCACD) models.
