Classification: Financial Mathematics
Umeå University is one of Sweden’s largest institutions of higher education with over 35,000 students and 4,200 faculty and staff. We are characterised by world-leading research in several scientific fields and a multitude of educations ranked highly in international comparison. Umeå University is also the site of the pioneering discovery of the CRISPR-Cas9 genetic scissors - a revolution in genetic engineering that has been awarded the Nobel Prize in Chemistry. At Umeå University, everything is nearby. Our cohesive campus environment makes it easy to meet, collaborate and exchange knowledge, which promotes a dynamic and open culture where we rejoice in each other's successes. Are you interested in knowing more about Umeå University as a workplace read more at:Work with us. The Department of Mathematics and Mathematical Statistics conducts research in computational mathematics, discrete mathematics, mathematical modelling and analysis, and mathematical statistics. Our teaching is conducted at all levels and includes mathematics, mathematical statistics and computational science. Among our partners are international research groups, academic institutions, public organizations and companies. The Department of Mathematics and Mathematical Statistics at Umeå University is opening a postdoctoral position in Financial Mathematics focusing on the pricing of commodity futures and options contracts in the context of seasonality. Last day to apply: August 15, 2022. The appointment is for two years at the Department of Mathematics and Mathematical Statistics. The successful candidate is expected to take on the research question with enthusiasm and high ambitions, actively engage with collaborators, and to participate in the daily activities of the research environment. Starting date can be at Janury 1, 2023 with some flexibility (earlier or later is possible). Project description and working tasks Our investigation will build up on benchmark multi-factor models from the commodities futures pricing literature, but clearly distinguishing the different channels that can create seasonality, spot price and preferences. We will link the preference channel to utility-based determination of risk premia, using the well-known utility indifference pricing approach. There are two key elements that can (and need) to be implemented within this approach: time varying instantaneous risk-aversion non-wealth factors that affect investors utility (e.g. sentiments) The pricing kernels obtained from this approach will be assessed against the pricing kernels of known multi-factor models. By doing so, some indication on which seasonal patterns may present market anomalies and arbitrages may be obtained. In the context of time varying instantaneous risk aversion there is scope here for deeper mathematical considerations involving the Malliavin calculus and time consistency issues. In a further step, we investigate the possibility of market anomalies and arbitrages more directly. This will involve the concept of statistical arbitrage. Here there is scope for application of machine learning techniques. The project offers opportunities for interdisciplinary collaborations with partners in the UK, Germany, Norway and the USA as well as links to the financial industry. The successful applicant will be given an opportunity to develop a teaching portfolio contributing up to 20% of the total working time, but this is not a requirement.
Last updated: 27 June 2022