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Found 7 papers, 0 papers with code
Asymptotics for the Generalized Autoregressive Conditional Duration Model
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.
Penalized Quasi-likelihood Estimation and Model Selection in Time Series Models with Parameters on the Boundary
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.
The Econometrics of Financial Duration Modeling
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.
MinP Score Tests with an Inequality Constrained Parameter Space
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.
Specification tests for GARCH processes
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.
Bootstrap Inference for Hawkes and General Point Processes
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.
Bootstrapping Non-Stationary Stochastic Volatility
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.
