Die Vorträge im Wintersemester 17/18 finden in der Regel mittwochs von 18:00 - 20:00 im Raum S06 S00 A21 (Wegbeschreibung) auf dem Campus Essen statt.
Termine und Vortragende:
29.11.2017: Prof. Dr. Ralf Korn, TU Kaiserslautern
Save for the Bad Times or Consume as Long as You Have? - Worst-Case Portfolio Optimization and Applications
Rare events and their consequences are hard - if not impossible - to estimate. The worst-case approach deals with this problem via distuinguishing between randomness and uncertainty. As a consequence, portfolio optimization problems are split into optimization and indifference tasks. Thus, we obtain a completely new portfolio optimization approach
In this talk, we give a survey on the worst-case approach, highlight a surprising application in optimal life-time consumption and present new aspects of the method.
20.12.2017: Prof. Stefan Trück, Macquarie University, Sydney
Convenience Yield Risk Premiums
The convenience yield is an important risk factor for commodity derivatives, but very little is known about how convenience yield risk is priced. In this paper, we construct portfolios of commodity futures that track the convenience yield risk premium. Our empirical results for a variety of different commodities show that premiums are consistently positive, as suggested by an argument based on hedging demand. However, the magnitude of the premium varies strongly between groups of commodities. Such differences can be explained by different market structures. Our study has implications for the risk management of commodity positions and demonstrates the value of convenience yield risk premiums for investors. For grains, a risk-averse investor realizes monetary utility gains over a risk-free investment of up to 11% per year from a trading strategy that tracks the premium.
24.01.2018: Prof. Peter Tankov, ENSAE ParisTech, Palaiseau
Optimal management of a wind power plant with storage capacity
We consider the problem of a wind producer who has access to the spot and intraday electricity markets and has the possibility of partially storing the produced energy using a battery storage facility. The aim of the producer is to maximise the expected gain of selling in the market the energy produced during a 24-hour period. We propose and calibrate statistical models for the power production and the intraday electricity price, and compute the optimal strategy of the producer via dynamic programming.