Wintersemester 16/17

Vorträge Wintersemester 16/17

Die Vorträge im Sommersemester 2016 finden in der Regel mittwochs von 18:00 - 20:00  im Raum S06 S00 A21 (<link file:30218 _blank>Wegbeschreibung) auf dem Campus Essen statt. 


Termine und Vortragende:

 26.10: Derck Koolen, ERASMUS University Rotterdam 

Forward Risk Premiums in Heterogeneous Electricity Markets under the Influence of Volatile Resources


With more renewable energy sources introduced, electricity markets experience increasing uncertainty. The question rises whether current market design is fit for enabling the transition to a low-carbon electricity system. We propose a multi-stage competitive equilibrium model for electricity wholesale markets. In analyzing risk related market behavior allowing the integration of high shares of renewable energy resources, we develop a heterogeneous agent-based approach. Results indicate evidence of a shift in risk behavior by flexible power producers in markets that reach a significant amount of renewable energy sources. Next, we simulate various conditions in an experimental market setting. This allows us to evaluate market structures under various real-world conditions and alter market design both from market and individual perspective.

 9.11: Professor Andrea Roncoroni, Finance Department ESSEC Business School, Cergy Pontoise Cedex

How Firms Should Hedge Non-Tradable Risk?

Corporate commitments often exhibit a combined financial exposure to both market prices and idiosyncratic non-tradable components (e.g., volume, load, or business turnover). We design customized contracts to optimally mitigate the risk of joint fluctuations in price and size terms. Hedges are sought out among contingent claims written on price and any quoted index that is statistically dependent on commitment size. Solutions are derived for optimal custom hedges for a variety of tradable claim universes, including price linear, price-index linear, price-index additive non-linear, and fully nonlinear derivatives, under increasingly complex dependence structures. Corresponding pay-off functions are computed either analytically or numerically by using Neumann series expansion of the associated Fredholm system solution. Empirical analysis based on data quoted on the EPEX SPOT power market and on the US gas markets show the performance or our custom hedge solutions in real contexts.

16.11: Professor Damiano Brigo, Chair in Mathematical Finance Imperial College, London

 Bitte beachten Sie, dass dieser Vortrag abweichend in Raum S06 S00 B32 stattfinden wird

The Science & Art of Valuation Adjustments: Nonlinear valuation under margins, funding costs, gap default closeout, multiple curves & capital.

The market for financial products and derivatives reached an outstanding notional size of 708 USD Trillions in 2011, amounting to ten times the planet gross domestic product. Even discounting double counting, derivatives appear to be an important part of the world economy and have played a key role in the onset of the financial crisis in 2007. We describe the changes triggered by post 2007 events on the theory of valuation. We re-discuss the valuation theory assumptions and introduce consistent valuation under counterparty credit risk, collateral posting, initial and variation margins, funding costs and capital costs. We explain model dependence induced by credit effects, hybrid features, contagion, payout uncertainty, and nonlinear effects due to replacement closeout at default and possibly asymmetric borrowing and lending rates in the margin interest and in the funding strategy for the hedge of the relevant portfolio. Nonlinearity manifests itself in the valuation equations taking the form of semi-linear PDEs or Backward SDEs. We present an invariance theorem showing that the final valuation equations do not depend on unobservable risk free rates, that become purely instrumental variables. Valuation is thus based only on real market rates and processes. We also present a high level analysis of the consequences of nonlinearities, both from the point of view of methodology and from an operational angle, including deal/entity/aggregation dependent valuation probability measures and the role of banks treasuries. We briefly discuss conditions under which adjustments can be disentangled. Finally, we hint at how one may connect these developments to interest rate theory under multiple discount curves and to valuations for CCP cleared trades, thus building a consistent valuation framework encompassing most post-2007 effects.

18.01: Stefan Küster, Dipl.-Volkswirt | Certified Financial Technician (CFTe),  EnergyCharts 

Anwendung der Technischen Analyse im Energiehandel

An den Kapitalmärkten ist die Technische Analyse eine unter Händlern, Portfolio Managern und Analysten schon seit vielen Jahren erfolgreich angewendete Methodik, um Vorhersagen über die weitere Kursentwicklung von Assets zu treffen. Die Erkenntnisse der Technischen Analyse der Finanzmärkte lassen sich jedoch auch ebenso erfolgreich auf die europäischen Energiemärkte für Strom und Gas übertragen. Die liquide gehandelten Futures an den Terminmärkten der EEX und natürlich auch OTC können charttechnisch analysiert und auf Basis der daraus gewonnenen Informationen Handelsentscheidungen getroffen werden. Der Praxisvortrag von Stefan Küster als Gründer der Technischen Analyseplattform hat es zum Ziel, den Teilnehmern die elementaren Grundlagen der Anwendung der Technischen Analyse im Energiehandel zu vermitteln. Am Ende des Vortags wird ein Live-Charting durchgeführt und es werden ausgewählte Kontrakte der Energiemärkte für Strom, Gas, Kohle, CO2 und Öl charttechnisch analysiert.


25.01: Juri Hinz, University of Technology, Sydney

Optimal Energy Supply Shift with Battery Storages

The energy storage sector has been dominated by pumped hydro power storages in past decades. However, technical progress has recently demonstrated that the disadvantages of electrical battery storages can be overcame and that this technology is increasingly becoming a viable option in the power sector. Still, optimal operational management is crucial to economically justify battery storages installation due to the high costs involved. The key success factor is the appropriate choice of charge and discharge cycles taking into account uncertainties from energy generation, demand and price. This optimization leads to stochastic control problems which are notoriously difficult due to a high number of state and control variables. In this work, we apply a novel approach to solve discrete-time control problems arising in this context and show how a duality-based technique can be used to assess the quality of our numerical solution.