Econometric Theory and Applications of Duration and Event Time Models in Economics and Finance
This project defines an entirely new field of research for the econometric analysis of timing and duration of transactions in economics and finance.
In finance, trades are often observed at high frequencies over a trading day, and with “clusters” of trades over the day. Trades, or events, are irregularly spaced and, importantly, the number of events is random. This randomness has been overlooked in existing research on duration models, where classical theory for estimators is erroneously applied.
In contrast, estimators have non-standard distributions, even in large samples, which depend on the degree of clustering of events. We will develop the required new econometric theory for the rich class of duration and event time models; moreover, we will provide multivariate versions of these to correctly model durations and events, as well as their interdependence.
Our project aims at building a new, comprehensive treatment of econometric duration and event time models where the number of observations, rather being fixed as in classical econometrics, is random. Noteworthy, the project has important spillovers to different areas of research where series of durations, or event times, play a key role. These include analysis of:
- Social media, where interest is in modeling information structures of social networks;
- Macroeconomic and monetary policy, anlysing announcements effects and interventions;
- Electronic markets, measuring effects of ultra-high speed trading strategies;
- Information forensics and cyber security, understanding the evolution of threats in computer networks.
Our project team consists of leading international experts in addition to Frederik Vilandt Rasmussen, who initiated his PhD studies in the fall of 2022. Please see list of group members below.
Researchers
| Name | Title | Job responsibilities | Phone | |
|---|---|---|---|---|
| Anders Rahbek | Professor | Financial Econometrics; Econometric Time Series Analysis; Bootstrap; GARCH and Volatility Modeling; Co-integration Analysis | +4535324031 | |
| Frederik Vilandt Rasmussen | PhD Fellow | Time-series econometrics; Asymptotics for likelihood-based estimators; Duration modeling; Counting processes; Bootstrap inference | ||
| Rasmus Søndergaard Pedersen | Associate Professor | Financial Econometrics; Time Series Econometrics; Econometric Theory; Heavy-Tailed Time Series; Models for Time-Varying Volatility | +4535323074 |
Funded by:
Econometric Theory and Applications of Duration and Event Time Models in Economics and Finance has received funding for 3 years
Period: July 2023 - July 2026
Contact
PI, Professor Anders Rahbek