Publications

We propose using a discounted version of a convex combination of the log-likelihood with the corresponding expected log-likelihood such that when they are maximized they yield a filter, predictor and smoother for time series. This paper then focuses on...

The potential system is a nonparametric time series model for assessing the causal impact of moving an assignment at time $t$ on an outcome at future time $t+h$, accounting for the presence of features.  The potential system provides nonparametric content...

Estimating linear regression using least squares and reporting robust
standard errors is very common in financial economics, and indeed, much of
the social sciences and elsewhere.   For thick tailed predictors under
heteroskedasticity this recipe for...

Using an in-fill argument, the properties of the sample median of a sequence of events are established both for the case of a fixed period of time and for a period which shrinks as the sample size grows.  The results are used to study the properties of...

This note reviews some of the contributions Ole Eiler Barndorff-Nielsen made to financial econometrics.  He was particularly active in that area from the mid-nineties for around a dozen years.  His innovations include the NIG Lévy process, the Barndorff...

This paper develops likelihood-based methods for estimation, inference, model selection, and forecasting of continuous-time integer-valued trawl processes. The full likelihood of integer-valued trawl processes is, in general, highly intractable...

Estimation of time-varying covariances is a key input in risk management and asset allocation. ARCH-type multivariate models are used widely for this purpose. Estimation of such models is computationally costly and parameter estimates are meaningfully...

In panel experiments, we randomly expose multiple units to different interventions and measure their subsequent outcomes, sequentially repeating the procedure numerous times. Using the potential outcomes framework, we define finite population dynamic...