Prof. Dr.  Rüdiger Kiesel


Prof. Dr. Rüdiger Kiesel

R09 R00 H33
+49 201 183-4963
+49 201 183-4974
Nach Vereinbarung



My main research areas are the risk management for power utility companies, bank, and insurance companies, modeling of electricity markets, valuation and hedging of derivatives (interest-rate, credit- and energy-related), optimal portfolio allocation under frictions.


  “Big risks”: perceptions, management and neuralgic societal risks in the 21st century (with Achim Goerres and Andreas Niederberger)

 This project is about the ways in which the public deals with neuralgic societal risks such as climate change, demographic change and state deficits in the 21st century (“big risks”). It aims to answer overarching questions from the three disciplinary perspectives of practical philosophy, political sociology and financial mathematics, all based at the interdisciplinary research cluster “Transformation of Contemporary Societies” at the University Duisburg-Essen.

Practical philosophy considers the epistemic difficulties of “knowing” risks and offers normative risk assessments and reactions to them. Political sociology studies the intersection between the political and the societal spheres and is equipped to deal with the effects of social and political positions on individual perceptions. Financial mathematics offers tools for the risk management of quantifiable risks and allows designing instruments for diversification and hedging of risks.

Whereas risk is a central concept in economics and business studies, its manifestations in a broader sense are rarely studied from a rigorous multi-disciplinary angle.


Analytics and Empirics of Intraday Trading of Electricity

(with Karsten Urban and Christoph Weber)

This project studies the empirics of electricity intraday markets using data on quarter-hour products. We will discuss the development of trading strategies and the construction of optimal portfolios for different market participants. We also aim to develop real-time trading strategies for practical applications. In addition, regulatory aspects for the generation of an efficient electricity markets will be investigated.


Model Risk in Energy Markets

While model risk has been studied in some detail in the context of financial mathematics model risk in the context of energy markets has been widely neglected. The aim of the project is to raise awareness of model risk and to provide tools for its quantification in energy markets. In particular, we consider the valuation of energy spread options which represent the financial alternative to investing in a (gas – or coal-fired) power plant. The valuation of such plants is important for the German market as they are regarded as bridging technology to provide capacity until electricity generated from renewable sources can be stored efficiently. We intend to apply our approach to other pricing question within the electricity market with a focus on short-term trading.


Structural Equilibrium Pricing Models

The aim of the project is the development and use of structural models for electricity prices, which will allow quantitative analysis for pricing and hedging of various electricity derivatives. We will also use the modeling approach to study the effect of market coupling on the prices of these derivatives.


Quantitative Climate Finance

Climate Change features a variety of uncertainties. Besides the physical implications, e.g. increased frequency and severity of storms, floods, draughts and extreme weather events, there are many economically relevant uncertainties in terms of political, social and regulatory reactions.

In particular, the quantification of climate risk in a probabilistic framework carries high uncertainties for probabilities of future developments (scenarios).

As a consequence, quantitative approaches are highly controversial in the academic and in particular in the public discussion. So far a systematic approach to the various degrees of uncertainty (ambiguity) is. We will provide a systematic classification of uncertainty for the discussion of the consequences of climate change and feed it in the discussion of the wider public.

Our focus will be the analysis of the consequences of the change of the world economy in the wake of climate change to aspects of financial markets. As during the climate summit 2015 in Paris far-reaching decisions towards a limitation of the global warming to the 2 degree Celsius have been taken, we will investigate the change towards a low-carbon world economy. So, we will investigate the consequences for financial institutions, investors and the regulation of financial and insurance markets.

A quantitative investigation needs a pricing of the economic costs of the carbon emissions to extend the standard pricing and risk management approaches. If such a pricing is done in the current literature typically CO2 permit prices are used and thus the price is too low by a significant margin. The basis of our investigation is therefore the construction of a carbon (-price) index, which will include a thorough treatment of the various aspects of uncertainty related to the modelling of climate change.  In doing so we use a decision-theoretic approach motivated from the asset pricing literature. In particular, it is necessary to use a realistic modelling of risk preferences as well as an explicit inclusion of the aversion towards ambiguity. Furthermore, in our analysis we separate risk and time preferences in the spirit of the approach of (Epstein-Zinn). 

As todays climate-policy decision will have long-term consequences, the above separation allows to appreciate the importance of the appropriate discount factor for the impact of these future consequences.

Our Index can be used to investigate the implication for capital markets and financial institutions of a more rigid climate policy. We will consider the valuation of companies on the capital markets, the analysis of companies towards their creditworthiness, and the structuring of carbon-friendly portfolios in asset allocation. In addition, we can quantify a carbon risk premium for companies, which can be used in terms of the portfolio management for equity as well as bond portfolios. Finally, we will be able to get a better view on the systemic risk that will be implied by a carbo-friendly revaluation of companies.


Publikationsliste herunterladen

  • R. Kiesel, and F. Paraschiv: Econometric analysis of 15-minute intraday electricity prices. In: Energy Economics, Jg. 64 (2017), S. 77-90. Details
  • Stahl, G., J. Zheng, R. Kiesel and R. Ru ̈hlicke: The Wasserstein Metric and Robustness in Risk Management. In: Risks, Jg. 4 (2016) Nr. 32. doi:10.3390/risks4030032
  • R. Kiesel and F. Rahe: Option pricing under time-varying risk aversion with applications to risk forecasting. In: Journal of Banking and Finance, Jg. 76 (2016) Nr. 3, S. 120-138. Details
  • R.Kiesel, M. Mroz, and U. Stadtmu ̈ller: Time-Varying Copula Models for Financial Time Series. In: Probability, Analysis and Number Theory, Jg. 48 (2016), S. 159-180. Details
  • R. Kiesel, and M. Kustermann: Structural Models for Coupled Electricity Markets. In: Journal of Commodity Finance, Jg. 3 (2016) Nr. 1, S. 1638. Details
  • C. Harms and R. Kiesel: Application of electricity bid stack models for dynamic hedging purposes. In: Journal of Energy Markets, Jg. 10 (2015) Nr. 1, S. 1-29.
  • R. Kiesel and Ya, Wen: Modelling the market price of risk for emission allowance certificates. In: G. Di Nunno and F. E. Benth (Hrsg.): Stochastics of environmental and financial economics. Springer Proceedings in Mathematics & Statistics, 2015.
  • S. Ebbeler, F. E. Benth and R. Kiesel: Indifference Pricing of Weather Derivatives based on Electricity Futures. In: M. Prokopczuk (Hrsg.): Energy Pricing Models: Recent Advances, Methods, and Tools. Palgrave Macmillan, New York 2014.
  • R. Kiesel, A. Rupp and K. Urban: Valuation of structured financial products by adaptive multilevel. In: S. Dalhlke et. al. (Hrsg.): Extraction of Quantifiable Information from Complex Systems. Springer, Heidelberg 2014.
  • F. E. Benth, R. Kiesel and A. Nazarova: A critical empirical study of three electricity spot price models. In: Energy Economics journal, Jg. 34 (2013) Nr. 5, S. 1589-1616. doi:10.1016/j.eneco.2011.11.012 Details
  • R. Biegler-König, F. E. Benth and R. Kiesel: Electricity Options and Additional Information, F. E. Benth, V. Kholodnyi and P. Laurence (Hrsg.), Quantitative Energy Finance, Springer 2013. Details
  • R. Biegler-König, F. E. Benth and R. Kiesel: An Empirical Study of the Information Premium on Electricity Markets, Energy Economics, 2013. Details
  • R. Kiesel and K. Metka: A Multivariate Commodity Analysis with Time-Dependent Volatility - Evidence from the German Energy Market. In: Zeitschrift für Energiewirtschaft, Jg. 37 (2013) Nr. 2, S. 107-126. doi:10.1007/s12398-012-0102-4 Details
  • G. Grüll and R. Kiesel: Quantifying the CO2 Permit Price Sensitivity. In: Zeitschrift für Energiewirtschaft, Jg. 36 (2012) Nr. 2, S. 101-111. doi:10.1007/s12398-012-0082-4 Details
  • D. Bauer, F. E. Benth and R. Kiesel : Modelling the forward surface of mortality. In: SIAM Journal on Financial Mathematics, Jg. 3 (2012) Nr. 1, S. 639-666. doi:10.1137/100818261 Details
  • R. Kiesel : Martingales. In: Lovric, M. (Hrsg.): International Encyclopedia of Statistical Science. Springer, 2011, S. 779-781.
  • J. Gernard, R. Kiesel and S.-O. Stoll: Valuation of Commodity-Based Swing Options. In: Journal of Energy Markets (2010) Nr. 3, S. 91-112. Details
  • N.H. Bingham, J. M. Fry and R. Kiesel : Multivariate elliptical processes. In: Statistica Neerlandica (2010) Nr. 64 (3), S. 352-366. Details
  • R. Kiesel and P. Scherer: The Freight Market and its Derivatives. In: R. Kiesel, M. Scherer and Rudi Zagst (Hrsg.): Alternative Assets and Strategies. World Scientific, 2010, S. 71-90.
  • R. Kiesel and M. Scherer: Structural default risk models. In: Encyclopedia of Quantitative Finance. John Wiley & Sons, Ltd. All , 2010.
  • R. Kiesel and M. Lutz: Efficient pricing of CMS spread options in a stochastic volatility LMM. In: Journal of Computational Finance, Jg. 14 (2010) Nr. 3, S. 37-72. Details
  • D. Bauer, D. Bergmann and R. Kiesel: On the risk-neutral valuation of life insurance contracts with numerical methods in view. In: Astin Bulletin (2010) Nr. 40, S. 65-95. Details
  • R. Kiesel, R.Börger and G. Schindlmayr: A two-factor model for the electricity forward market. In: Quantitative Finance, Jg. 9 (2009) Nr. 3, S. 279-287. Details
  • R. Börger, A. Cartea, R. Kiesel and G. Schindelmayer: A multivariate commodity analysis and applications to risk management. In: Journal of Future Markets (2009) Nr. 29 (3), S. 197-217. Details
  • F.E. Benth, A. Cartea and R. Kiesel: Pricing forward contracts in power markets by the certainty equivalence principle: Explaining the sign of the market risk premium. In: Journal of Banking and Finance, Jg. 32 (2008) Nr. 10, S. 2006-2021. doi:10.1016/j.jbankfin.2007.12.022 Details
  • R. Kiesel, L. Veraart: Asset-based Estimates for Default Probabilities for Commercial Banks. In: Journal of Credit Risk, Jg. 4 (2008) Nr. 2. Details
  • R. Kiesel, T. Liebmann, S. Kassberger: Fair valuation of insurance contracts under Lévy process specifications. In: Insurance: Mathematics and Economics, Jg. 42 (2007) Nr. 1, S. 419-433. Details
  • R. Kiesel, D. Bauer, A. Kling, J. Ruß: Risk neutral valuation of with profit life insurance contracts. In: Insurance: Mathematics and Economics, Jg. 39 (2006), S. 171-183. Details
  • R. Kiesel, S. Kassberger: A fully parametric approach to return modelling and risk management for hedge funds. In: Financial Markets and Portfolio Management, Jg. 4 (2006), S. 472-491. Details
  • R. Kiesel, R. Schmidt: A survey of dependency modelling: Copulas, tail dependence and estimation. In: W.Perraudin (Hrsg.): Structured Credit Products. RISK Book, 2005.
  • R. Kiesel, T.Kleinow: Fair Value-basierende Optionspreisbewertung, R. Heyd, H. Bieg (Hrsg.), Vahlen, 2005.
  • R. Kiesel, M. Lesko, C. Prestele: Modellierung von Abhängigkeiten bei der Bewertung von Verbriefungen. In: H. Braun, J. Gruber, W. Gruber (Hrsg.): Praktiker-Handbuch – Asset-Backed-Securities und Kreditderivate. Schäffer-Poeschel Verlag, Stuttgart 2005.
  • R. Börger and R. Kiesel: Finanzmathematische Modelle für Strompreise. In: emw (2004) Nr. 6.
  • R. Kiesel, H.Höfling and G. Löffler: Understanding the Corporate Bond Yield Curve. In: The Pension Forum, Jg. 15 (2004), S. 2-34.
  • R. Kiesel, S. Kassberger: F. Black und M.Scholes als Aktuare: Anwendungen der Optionspreistheorie in der Lebensversicherungsmathematik. In: K. Spremann (Hrsg.): Versicherung im Umbruch. Springer, 2004.
  • R. Kiesel, W. Perraudin and A.Taylor: An extremes analysis of VaRs for emerging market benchmark bonds. In: G. Bol et al. (Hrsg.): Credit Risk: Measurement, Evaluation and Management. Physica-Verlag, 2004.
  • R. Kiesel, N.H. Bingham, R.Schmidt: A semi-parametric approach to risk management . In: Quantitative Finance, Jg. 3 (2003), S. 426-441. Details
  • R. Kiesel, W.Perraudin and A. Taylor: The structure of credit risk: Spread volatility and ratings transitions. In: Journal of Risk, Jg. 6 (2003), S. 1-27.
  • N.H. Bingham and R. Kiesel: Semi-parametric modelling in finance: theoretical foundations. In: Quantitative Finance, Jg. 2 (2002), S. 241-250. Details
  • R. Kiesel, Y.-T. Hu and W. Perraudin: Estimation of transition matrices for sovereign credit risk. In: Journal of Banking and Finance, Jg. 26 (2002) Nr. 7, S. 1383-1406. Details
  • R. Kiesel, : Nonparametric statistical methods and the pricing of derivative securities. In: Journal of Applied Mathematics & Decision Sciences, Jg. 6 (2002) Nr. 1, S. 1-22. Details
  • R. Kiesel, T.Kleinow: Sensitivity analysis of credit portfolio models. In: in G. Stahl W. Härdle, T. Kleinow (Hrsg.): Applied Quantitative Finance. Springer, 2002.
  • R. Kiesel, U.Stadtmüller: Dimensions of credit risk - Proceedings of the 25th Annual Conference of the Gesellschaft für Klassifikation e.V. In: M.Schwaiger and O.Opitz (Hrsg.): Exploratory Data Analysis in Empirical Research. Springer, 2002.
  • R. Kiesel, N.H. Bingham: Hyperbolic and semi-parametric models in finance. In: P.Sollich,A.C.C.Coolen,L.P.Houghston, and R.F.Streater (Hrsg.): Disordered and Complex Systems. 2001.
  • R. Kiesel, N.H. Bingham: Modelling asset returns with hyperbolic distributions. In: J. Knight and S. Satchel (Hrsg.): Asset return distributions. Butterworth-Heinemann, 2001, S. 1-20.
  • R. Kiesel, W.Perraudin and A.Taylor: Estimating volatility for long holding periods. In: Measuring Risk in Complex Systems, eds. W.Härdle,J.Franke,G.Stahl, Springer (2000), S. 19-30.
  • R. Kiesel, B.Schmid, Risklab, Germany: Aspekte der stochastischen Modellierung von Ausfallwahrscheinlichkeiten in Kreditportfoliomodellen. In: Kreditrisikomanagement, ed.K.Oehler, Schäffer-Poeschel Verlag (2000), S. 51-83. Details
  • (Hrsg.): Mathematical framework for integrating market and credit risk, .
  • K. Bannör, R. Kiesel, A. Nazarova, M. Scherer: Model Risk for Energy Markets. In: Energy Economics, Jg. 59 , S. 423-434. doi:10.1016/j.eneco.2016.08.004


Lehrveranstaltungen im WS