no code implementations • 4 Jul 2023 • Giuseppe Cavaliere, Thomas Mikosch, Anders Rahbek, Frederik Vilandt
Engle and Russell (1998, Econometrica, 66:1127--1162) apply results from the GARCH literature to prove consistency and asymptotic normality of the (exponential) QMLE for the generalized autoregressive conditional duration (ACD) model, the so-called ACD(1, 1), under the assumption of strict stationarity and ergodicity.
no code implementations • 6 Feb 2023 • Heino Bohn Nielsen, Anders Rahbek
We extend the theory from Fan and Li (2001) on penalized likelihood-based estimation and model-selection to statistical and econometric models which allow for non-negativity constraints on some or all of the parameters, as well as time-series dependence.
no code implementations • 3 Aug 2022 • Giuseppe Cavaliere, Thomas Mikosch, Anders Rahbek, Frederik Vilandt
We establish new results for estimation and inference in financial durations models, where events are observed over a given time span, such as a trading day, or a week.
no code implementations • 13 Jul 2021 • Giuseppe Cavaliere, Zeng-Hua Lu, Anders Rahbek, Yuhong Yang
We show that our tests perform better than/or perform as good as existing score tests in terms of joint testing, and has furthermore the added benefit of allowing for simultaneously testing individual elements of parameter of interest.
no code implementations • 28 May 2021 • Giuseppe Cavaliere, Indeewara Perera, Anders Rahbek
The test statistics considered are of Kolmogorov-Smirnov and Cram\'{e}r-von Mises type, and are based on a certain empirical process marked by centered squared residuals.
no code implementations • 7 Apr 2021 • Giuseppe Cavaliere, Ye Lu, Anders Rahbek, Jacob Stærk-Østergaard
Inference and testing in general point process models such as the Hawkes model is predominantly based on asymptotic approximations for likelihood-based estimators and tests.
no code implementations • 10 Jan 2021 • H. Peter Boswijk, Giuseppe Cavaliere, Anders Rahbek, Iliyan Georgiev
Instead, we use the concept of `weak convergence in distribution' to develop and establish novel conditions for validity of the wild bootstrap, conditional on the volatility process.