Sjur Westgaard holds an MSc and PhD in Industrial Economics from Norwegian University of Science and Technology and an MSc in Finance from Norwegian School of Business and Economics. He has worked as an investment portfolio manager for an insurance company, a project manager for a consultant company, and a credit analyst for an international bank. He is now a Professor at the Norwegian University of Science and Technology and has also an adjunct position at the Norwegian University of Life Sciences. His teaching involves economics and finance, and economic and financial forecasting. His main research interests cover risk management and forecasting for financial institutions and industry corporations. He has been a project manager for several research projects involving power companies and the Norwegian Research Council. He is one of the founders and editors of Journal of Commodity Markets. He is also an associate editor of The Journal of Energy Markets and a former associate editor of Journal of Banking and Finance.
The authors put forward an explainable machine learning model predicting credit default using a real-world data set provided by a Norwegian bank.
Measuring the effect of corrective short-term updates for wind energy forecasts on intraday electricity prices
This paper investigates the impact of wind energy updates on intraday prices and proposes the use of merit-order-based models to counter price uncertainties stemming from updates.
In this paper the authors propose a semi-parametric, parsimonious value-at-risk forecasting model based on quantile regression and readily available market prices of option contracts from the over-the-counter foreign exchange interbank market.
The authors investigate the performance of various value-at-risk (VaR) models in the context of the highly volatile Nordic power futures market, examining whether simple averages of models provide better results than the individual models themselves.
Value-at-risk in the European energy market: a comparison of parametric, historical simulation and quantile regression value-at-risk
This paper examines a set of value-at-risk (VaR) models and their ability to appropriately describe and capture price-change risk in the European energy market.
This paper proposes and investigates a valuation model for the income of selling tradeable green certificates in the Swedish–Norwegian market, formulated as a singular stochastic control problem.
This paper looks at the time-varying relation between electricity futures prices and fundamentals.