Experience

 
 
 
 
 
August 2016 – Present
Stavanger

PhD Student

University of Stavanger

Research areas:

  • Bayesian inference for non-linear dynamic econometric models.
  • Hamiltonian Monte Carlo
 
 
 
 
 
August 2016 – Present
Stavanger

Research assistant

University of Stavanger

  • STA100: Probability and Statistics 1
  • STA510: Statistical modeling and simulation
 
 
 
 
 
June 2014 – July 2014
Stavanger

Summer intern

SpareBank 1 SR-Bank - Credit control

Responsibilities include:

  • Optimizing auto-generated commercial property credit risk reports
  • Coding in SQL and VBA (Excel)

R

100%

Statistics

100%

Golf

80%

Recent Posts

When writing up my PhD thesis, I learned that the University of Stavanger has no official Latex template, only a very basic Word template. I ended up making my own Latex template, based on the available Word template. The Latex template The template …

The 3rd International Conference on Econometrics and Statistics (EcoSta 2019) took place at the National Chung Hsing University (NCHU), Taichung, Taiwan 25-27 June 2019. The conference consisted of 10 parallel sessions, each having 14-17 sessions …

Continuing from my previous post, I now focus on detailed match statistics, rather than the available aggregate data. By scraping very detailed data from each match of the 2018/2019 Norwegian hockey season, my goal is to present aggregate data that …

I wanted to visualize the personal statistics for the hockey players of Stavanger Oilers, for the 2018/2019 season. The data material is scraped from both Elite Prospects and Hockey live (regular season and playoffs), using the R-package rvest, as …

This post regards my MS_VAR Github repository, which contains code used in the following paper: Osmundsen, Kjartan Kloster, Tore Selland Kleppe, and Atle Oglend. “MCMC for Markov-switching models—Gibbs sampling vs. marginalized likelihood.” …

Recent Publications

(2020). Estimating the Competitive Storage Model with Stochastic Trends in Commodity Prices. arXiv.

Preprint

(2019). Importance Sampling-based Transport Map Hamiltonian Monte Carlo for Bayesian Hierarchical Models. arXiv.

Preprint Code

(2019). MCMC for Markov-switching models - Gibbs sampling vs. marginalized likelihood. Communications in Statistics-Simulation and Computation, 1-22.

Code DOI

(2018). Using expected shortfall for credit risk regulation. Journal of International Financial Markets, Institutions and Money 57, 80-93.

DOI

Recent Talks

Contributed talk, National Chung Hsing University, Taiwan.

Poster presentation, University of Warwick.

Contributed talk, City University of Hong Kong.