Publications

Filter:
  • Blasberg, A.: Climate Risk and Credit Risk - Theory and Empirics (Dissertation). 2024. doi:10.17185/duepublico/81488Full textCitationDetails

    Given the potentially severe financial consequences due to climate change, understanding how climate risks contribute to firms’ credit risk is essential. Building on a Merton-type model, we propose a new model that introduces a random growth adjustment factor in the firm value dynamics to reflect the depreciation due to climate risks. We also review the current state of the literature on how structural models of credit risk are employed to model the impact of climate risk on financial markets. Motivated by the theoretical models, we utilize the information contained in the spreads of Credit Default Swap (CDS) contracts to construct a market-implied, forward-looking carbon risk (CR) factor. We examine empirically how the scope and speed of economic transformation vary across jurisdictions, sectors, and over time. Explicit carbon emission pricing enables lenders to sharpen their assessments. The breadth of the regulation intensifies financial repercussions from carbon risk. The impact differs significantly across industries, indicating that the market identifies which sectors are better poised for a transition to a low-carbon economy. Lenders expect that adjustments in carbon regulations in Europe will cause relatively higher policy-related costs in the near future.

  • Blasberg, A.; Kiesel, R.: Climate Risk in Structural Credit Models. In: Benth, F. E.; Veraart, A. E. D. (Ed.): Quantitative Energy Finance: Recent Trends and Developments. 2nd Edition. Springer, 2023, p. 247-267. doi:10.1007/978-3-031-50597-3_7Full textCitationDetails

    This survey article reviews the current state of literature on how structural models of credit risk are employed to model the impact of climate risk on financial markets. We discuss how the two prominent types of climate risk, physical and transition risk, are captured by the seminal Merton model and its well-known extensions. Theoretical and practical advantages and drawbacks are worked out and an outlook on possible model improvements is provided.

  • Kremer, M.: High-frequency electricity trading: Empirics, fundamentals, and stochastics (Dissertation). 2021. doi:10.17185/duepublico/74512Full textCitationDetails
  • Kremer, M.; Kiesel, R.; Paraschiv, F.: An econometric model for intraday electricity trading. In: Philosophical Transactions of the Royal Society A, Vol 379 (2021) No 2202. doi:10.1098/rsta.2019.0624Full textCitationDetails
  • Blasberg, A.; Kiesel, R.; Taschini, L.: Carbon Default Swap – Disentangling the Exposure to Carbon Risk Through CDS. 2021. Full textCitationDetails

    Using Credit Default Swap spreads, we construct a forward-looking, market-implied carbon risk factor and show that carbon risk affects firms’ credit spread. The effect is larger for European than North American firms and varies substantially across industries, suggesting the market recognises where and which sectors are better positioned for a transition to a low-carbon economy. Moreover, lenders demand more credit protection for those borrowers perceived to be more exposed to carbon risk when market-wide concern about climate change risk is elevated. Finally, lenders expect that adjustments in carbon regulations in Europe will cause relatively larger policy-related costs in the near future.

  • Kramer, A.; Kiesel, R.: Exogenous factors for order arrivals on the intraday electricity market. In: Energy Economics, Vol 97 (2021) No 105186, p. 1-14. doi:10.1016/j.eneco.2021.105186Full textCitationDetails

    We examine if the trading activity on the German intraday electricity market is linked to fundamental as well as market-induced factors. Thus, we propose a novel point process model in which the intensity process of order arrivals consists of a self-exciting term and additional exogenous factors, such as the production of renewable en- ergy or the activated volume on the balancing market. The model parameters are estimated by a maximum like- lihood approach that explicitly accounts for such factor processes. By comparing the proposed model to several nested models, we investigate whether adding the exogenous factors significantly increases the accuracy of the model fit. We find that intensity processes that only take into account exogenous factors are improved if we add a self-exciting term. On the other hand, to capture the market dynamics correctly, pure self-exciting models need to be extended such that they additionally account for exogenous impacts.

  • Graf von Luckner, N.; Kiesel, R.: Modeling Market Order Arrivals on the Intraday Market for Electricity Deliveries in Germany with the Hawkes Process. In: Journal of Risk and Financial Management, Vol 14 (2021) No 4. doi:10.3390/jrfm14040161Full textCitationDetails

    We use point processes to analyze market order arrivals on the intraday market for hourly electricity deliveries in Germany in the second quarter of 2015. As we distinguish between buys and sells, we work in a multivariate setting. We model the arrivals with a Hawkes process whose baseline intensity comprises either only an exponentially increasing component or a constant in addition to the exponentially increasing component, and whose excitation decays exponentially. Our goodness-of-fit tests indicate that the models where the intensity of each market order type is excited at least by events of the same type are the most promising ones. Based on the Akaike information criterion, the model without a constant in the baseline intensity and only self-excitation is selected in almost 50% of the cases on both market sides. The typical jump size of intensities in case of the arrival of a market order of the same type is quite large, yet rather short lived. Diurnal patterns in the parameters of the baseline intensity and the branching ratio of self-excitation are observable. Contemporaneous relationships between different parameters such as the jump size and decay rate of self and cross-excitation are found.

  • Kremer, M.; Kiesel, R.; Paraschiv, F.: Intraday electricity pricing of night contracts. In: Energies, Vol 13 (2020) No 17, p. 4501. doi:10.3390/en13174501Full textCitationDetails
  • Kremer, M.; Benth, F. E.; Felten, B.; Kiesel, R.: Volatility and liquidity on high-frequency electricity futures markets: Empirical analysis and stochastic modeling. In: International Journal of Theoretical and Applied Finance, Vol 23 (2020) No 4. doi:10.1142/S0219024920500272Full textCitationDetails
  • Kremer, M.: thrreg: Threshold regression model. R Package, 2020. Full textCitationDetails
  • Kremer, M.: kcopula: The bivariate K-copula - R Package. In: CRAN (2020). Full textCitationDetails
  • Glas, S.; Kiesel, R.; Kolkmann, S.; Kremer, M.; Graf von Luckner, N.; Ostmeier, L.; Urban, K.; Weber, C.: Intraday renewable electricity trading: Advanced modeling and numerical optimal control. In: Journal of Mathematics in Industry, Vol 10 (2020) No 3, p. 1-17. doi:10.1186/s13362-020-0071-xFull textCitationDetails
  • Blasberg, A.; Graf von Luckner, N.; Kiesel, R.: Modeling the Serial Structure of the Hawkes Process Parameters for Market Order Arrivals on the German Intraday Power Market. In: 16th International Conference on the European Energy Market (EEM) (2019), p. 1-6. doi:10.1109/EEM.2019.8916326Full textCitationDetails

    Existing research indicates that on the intraday market for power deliveries in Germany market orders tend to arrive in clusters. To capture such clustering, point processes with an intensity depending on past events, so-called Hawkes processes, appear to be promising. We consider the question whether there is a temporal structure prevalent in the parameters of Hawkes processes estimated for adjacent delivery hours. First we model a diurnal seasonality pattern found in the data and provide an economic intepretation for it. For the remaining decomposed series, we then propose simple (vector) autoregressive models to describe the serial structure. To evaluate our model we conduct a forecasting study. Testing against a benchmark model and a model without any serial structure, we find evidence for our proposed model. Our study reveals that capturing the serial structure in the parameters proves to be useful in understanding the underlying market microstructure.

  • Glas, S.; Kiesel, R.; Kolkmann, S.; Kremer, M.; Graf von Luckner, N.; Ostmeier, L.; Urban, K.; Weber, C.: Intraday renewable electricity trading: Advanced modeling and optimal control. In: Faragó, I.; Izsák, F.; Simon, P. (Ed.): Progress in Industrial Mathematics at ECMI 2018. Mathematics in Industry, vol 30. Springer, Cham, 2019, p. 469-475. doi:10.1007/978-3-030-27550-1_59Full textCitationDetails
  • Kremer, M.; Becker, A. P.; Vodenska, I.; Stanley, H. E.; Schäfer, R.: Economic and political effects on currency clustering dynamics. In: Quantitative Finance, Vol 19 (2019) No 5, p. 705-716. doi:10.1080/14697688.2018.1532101Full textCitationDetails
  • Kiesel, R.; Paraschiv, F.: Econometric analysis of 15-minute intraday electricity prices. In: Energy Economics, Vol 64 (2017), p. 77-90. Full textCitationDetails
  • Wollschläger, M.; Schäfer, R.: Impact of nonstationarity on estimating and modeling empirical copulas of daily stock returns. In: Journal of Risk, Vol 19 (2016) No 1, p. 1-23. doi:10.21314/JOR.2016.342Full textCitationDetails
  • Kollenberg, S.; Taschini, L.: Emissions trading systems with cap adjustments. In: Journal of Environmental Economics and Management (2016). doi:10.1016/j.jeem.2016.09.003CitationDetails

    Emissions Trading Systems (ETSs) with fixed caps lack provisions to address systematic imbalances in the supply and demand of permits due to changes in the state of the regulated economy. We propose a mechanism which adjusts the allocation of permits based on the current bank of permits. The mechanism spans the spectrum between a pure quantity instrument and a pure price instrument. We solve the firms' emissions control problem and obtain an explicit dependency between the key policy stringency parameter – the adjustment rate – and the firms' abatement and trading strategies. We present an analytical tool for selecting the optimal adjustment rate under both risk-neutrality and risk-aversion, which provides an analytical basis for the regulator's choice of a responsive ETS policy.

  • Kiesel, R.; Rühlicke, R.; Stahl, G.; Zheng, J.: The Wasserstein Metric and Robustness in Risk Management. In: Risks, Vol 4 (2016) No 32. doi:10.3390/risks4030032CitationDetails
  • Kollenberg, S.; Taschini, L.: Dynamic Supply Adjustment and Banking Under Uncertainty - The Market Stability Reserve. Working Paper. 2016. Full textCitationDetails
  • Kiesel, R.; Rahe, F.: Option pricing under time-varying risk aversion with applications to risk forecasting. In: Journal of Banking and Finance, Vol 76 (2016) No 3, p. 120-138. Full textCitationDetails
  • Kiesel, R.; Mroz, M.; Stadtmüller, U.: Time-Varying Copula Models for Financial Time Series. In: Probability, Analysis and Number Theory, Vol 48 (2016), p. 159-180. doi:10.13140/RG.2.1.4894.5368CitationDetails
  • Kiesel, R.; Kustermann, M.: Structural Models for Coupled Electricity Markets. In: Journal of Commodity Markets, Vol 3 (2016) No 1, p. 1638. Full textCitationDetails
  • Chetalova, D.; Wollschläger, M.; Schäfer, R.: Dependence structure of market states. In: Journal of Statistical Mechanics: Theory and Experiment (2015) No P08012, p. 1-19. doi:10.1088/1742-5468/2015/08/P08012Full textCitationDetails
  • Neuhoff, K.; Acworth, W.; Betz, R.; Burtraw, D.; Cludius, J.; Fell, H.; Hepburn, C.; Holt, C.; Jotzo, F.; Kollenberg, S.; Landis, F.; Salant, S.; Schopp, A.; Shobe, W.; Taschini, L.; Trotignon, R.: Is a Market Stability Reserve Likely to Improve the Functioning of the EU ETS? - Evidence from a Model Comparison Exercise. Strategies, Climate (Ed.), London 2015. Full textCitationDetails
  • Gilbert; A.; Lam, L.; Sachweh; C.; Smith; Ecofys, M.; Taschini; Lse, L.; Kollenberg; Ude, S.: Assessing Design Options for a Market Stability Reserve in the EU ETS. 2015. Full textCitationDetails
  • Harms, C.; Kiesel, R.: Application of electricity bid stack models for dynamic hedging purposes. In: Journal of Energy Markets, Vol 10 (2015) No 1, p. 1-29. CitationDetails
  • Kiesel, R.; Ya, Wen: Modelling the market price of risk for emission allowance certificates. In: Nunno, G. Di; Benth, F. E. (Ed.): Stochastics of environmental and financial economics. Springer Proceedings in Mathematics & Statistics, 2015. CitationDetails
  • Ebbeler, S.; Benth, F. E.; Kiesel, R.: Indifference Pricing of Weather Derivatives based on Electricity Futures. In: Prokopczuk, M. (Ed.): Energy Pricing Models: Recent Advances, Methods, and Tools. Palgrave Macmillan, New York 2014. CitationDetails
  • Kiesel, R.; Kustermann, M.: Structural Models for Coupled Electricity Markets. Essen 2014. Full textCitationDetails
  • Bannor, K.; Kiesel, R.; Nazarova, A.; Scherer, M. A.: Model Risk and Power Plant Valuation. 2014. Full textCitationDetails
  • Taschini, L.; Kollenberg, S.; Duffy, C.: System Responsiveness and the European Union Emissions Trading System - Policy Paper . Cccep; Economics, London School Of; Science, Political (Ed.), 2014. Full textCitationDetails
  • Kiesel, R.; Rupp, A.; Urban, K.: Valuation of structured financial products by adaptive multilevel. In: Dalhlke, S.; Dahmen, W.; Giebel, M.; Hackbusch, W.; Ritter, K.; Schneider, R.; Schwab, C.; Yserentant, H. (Ed.): Extraction of Quantifiable Information from Complex Systems. Springer, Heidelberg 2014, p. 321-345. doi:10.1007/978-3-319-08159-5_16CitationDetails
  • Benth, F. E; Kiesel, R.; Nazarova, A.: A critical empirical study of three electricity spot price models. In: Energy Economics journal, Vol 34 (2013) No 5, p. 1589-1616. doi:10.1016/j.eneco.2011.11.012Full textCitationDetails
  • Bannör, K.; Kiesel, R.; Nazarova, A.; Scherer, M.: Model Risk for Energy Markets. In: Energy Economics, Vol 59 (2013), p. 423-434. doi:10.1016/j.eneco.2016.08.004CitationDetails
  • Biegler-König, R.; Benth, F. E.; Kiesel, R.: Electricity Options and Additional Information. Working Paper. F. E. Benth, V. Kholodnyi; Laurence, P. (Ed.), Quantitative Energy Finance, Springer 2013. CitationDetails
  • Biegler-König, R.; Benth, F. E.; Kiesel, R.: An Empirical Study of the Information Premium on Electricity Markets. 36:55-77. Energy Economics, 2013. Full textCitationDetails
  • Kiesel, R.; Metka, K.: A Multivariate Commodity Analysis with Time-Dependent Volatility - Evidence from the German Energy Market. In: Zeitschrift für Energiewirtschaft, Vol 37 (2013) No 2, p. 107-126. doi:10.1007/s12398-012-0102-4Full textCitationDetails
  • Grüll, G.; Kiesel, R.: Quantifying the CO2 Permit Price Sensitivity. In: Zeitschrift für Energiewirtschaft, Vol 36 (2012) No 2, p. 101-111. doi:10.1007/s12398-012-0082-4Full textCitationDetails
  • Stahl, Gerhard; Zheng, Jinsong; Kiesel, Rüdiger; Rühlicke, Robin: Conceptualizing Robustness in Risk Management. 2012. doi:10.2139/ssrn.2065723Full textCitationDetails

    Working Paper, available at ssrn.com/abstract=2065723

  • Bauer, D.; Benth, F. E.; Kiesel, R.: Modelling the forward surface of mortality. In: SIAM Journal on Financial Mathematics, Vol 3 (2012) No 1, p. 639-666. doi:10.1137/100818261Full textCitationDetails
  • Grüll, G.; Taschini, L.: Cap-and-Trade Properties Under Different Scheme Designs. In: Journal of Environmental Economics and Management (2011) No 61, p. 107-108. CitationDetails
  • Kiesel, R.: Martingales. In: Lovric, M. (Ed.): International Encyclopedia of Statistical Science. 1st Edition. Springer, 2011, p. 779-781. CitationDetails
  • Hess, M.: Pricing Temperature Derivatives under Future Weather Information. Working Paper. 2011. CitationDetails
  • Gernard, J.; Kiesel, R.; Stoll, S. - O: Valuation of Commodity-Based Swing Options. In: Journal of Energy Markets (2010) No 3, p. 91-112. Full textCitationDetails
  • Grüll, G.; Kiesel, R.: Pricing CO2 Permits Using Approximation Approaches. In: Preprint (2010). CitationDetails
  • Bingham, N. H.; Fry, J. M.; Kiesel, R.: Multivariate elliptical processes. In: Statistica Neerlandica (2010) No 64 (3), p. 352-366. Full textCitationDetails
  • Kiesel, R.; Scherer, P.: The Freight Market and its Derivatives. In: Kiesel, R.; Scherer, M.; Zagst, Rudi (Ed.): Alternative Assets and Strategies. World Scientific, 2010, p. 71-90. CitationDetails
  • Kiesel, R.; Scherer, M.: Structural default risk models. In: Encyclopedia of Quantitative Finance. John Wiley & Sons, Ltd. All , 2010. CitationDetails
  • G. Grüll, L. Taschini: Linking Emission Trading Schemes. In: Preprint (2010). CitationDetails
  • Kiesel, R.; Lutz, M.: Efficient pricing of CMS spread options in a stochastic volatility LMM. In: Journal of Computational Finance, Vol 14 (2010) No 3, p. 37-72. Full textCitationDetails

    Working Paper available at:

    papers.ssrn.com/sol3/papers.cfm

  • Kiesel, R.; Scherer, M.: Dynamic credit portfolio modelling in structural models with jumps. In: Preprint (2010). CitationDetails
  • D. Bauer, D. Bergmann; Kiesel, R.: On the risk-neutral valuation of life insurance contracts with numerical methods in view. In: Astin Bulletin (2010) No 40, p. 65-95. Full textCitationDetails
  • Hess, M.: A Forward-Looking Multi-Factor Ornstein-Uhlenbeck Model for Pricing Electricity Risk. Working Paper. 2010. CitationDetails
  • Hess, M.: Explicit Pricing Measures for Commodity Forwards in a Heath-Jarrow-Morton-Framework with Jumps. Working Paper. 2010. CitationDetails
  • Hess, M.: Nonlinear Double-Jump Stochastic Filtering Using Generalized Levy-Type Processes. Working Paper. 2010. CitationDetails
  • Georg Grüll, Luca Taschini: A Comparison of Reduced-Form Permit Price Models and Their Empirical Performances. In: MIT CEEPR Working Paper Series (2009). CitationDetails
  • Kiesel, R.; Börger, R.; Schindlmayr, G.: A two-factor model for the electricity forward market. In: Quantitative Finance, Vol 9 (2009) No 3, p. 279-287. Full textCitationDetails
  • Kiesel, R.; Cartea, A.; Börger, R.; Schindlmayr, G.: Cross-Commodity Analysis and Applications to Risk Management. In: Journal of Futures Markets (2009) No 29, p. 197-217. CitationDetails
  • Börger, R.; Cartea, A.; Kiesel, R.; Schindelmayer, G.: A multivariate commodity analysis and applications to risk management. In: Journal of Future Markets (2009) No 29 (3), p. 197-217. Full textCitationDetails
  • Ebbeler, S.; Kiesel, R.; Metka, K.: Empirical comparison of future pricing models. In: Working Paper (2009). CitationDetails
  • Benth, F. E.; Cartea, A.; Kiesel, R.: 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, Vol 32 (2008) No 10, p. 2006-2021. doi:10.1016/j.jbankfin.2007.12.022Full textCitationDetails
  • Kiesel, R.; Veraart, L.: Asset-based Estimates for Default Probabilities for Commercial Banks. In: Journal of Credit Risk, Vol 4 (2008) No 2. Full textCitationDetails
  • Kiesel, R.; Liebmann, T.; Kassberger, S.: Fair valuation of insurance contracts under Lévy process specifications. In: Insurance: Mathematics and Economics, Vol 42 (2007) No 1, p. 419-433. Full textCitationDetails
  • Kiesel, R.; Kassberger, S.: A fully parametric approach to return modelling and risk management for hedge funds. In: Financial Markets and Portfolio Management, Vol 4 (2006), p. 472-491. Full textCitationDetails
  • Kiesel, R.; Bauer, D.; Kling, A.; Ruß, J.: Risk neutral valuation of with profit life insurance contracts. In: Insurance: Mathematics and Economics, Vol 39 (2006), p. 171-183. Full textCitationDetails
  • Mathematical framework for integrating market and credit risk. 2006. CitationDetails
  • Kiesel, R.; Stahl, G.; Liebmann, T.: Mathematical framework for integrating market and credit risk. In: Ong, M. (Ed.): Risk Management. 2005. CitationDetails
  • Kiesel, R.; Schmidt, R.: A survey of dependency modelling: Copulas, tail dependence and estimation. In: Perraudin, W. (Ed.): Structured Credit Products. RISK Book, 2005. CitationDetails
  • Kiesel, R.; Lesko, M.; Prestele, C.: Modellierung von Abhängigkeiten bei der Bewertung von Verbriefungen. In: Braun, H.; Gruber, J.; Gruber, W. (Ed.): Praktiker-Handbuch – Asset-Backed-Securities und Kreditderivate. Schäffer-Poeschel Verlag, Stuttgart 2005. CitationDetails
  • Kiesel, R.; Kleinow, T.: Fair Value-basierende Optionspreisbewertung. R. Heyd, H. Bieg (Ed.), Vahlen, 2005. CitationDetails
  • Börger, R.; Kiesel, R.: Finanzmathematische Modelle für Strompreise. In: emw (2004) No 6. CitationDetails
  • Nicholas H. Bingham, Rüdiger Kiesel: Risk-neutral valuation. 2nd Edition. Springer, New-York 2004. CitationDetails
  • Kiesel, R.; Höfling, H.; Löffler, G.: Understanding the Corporate Bond Yield Curve. In: The Pension Forum, Vol 15 (2004), p. 2-34. CitationDetails
  • Kiesel, R.; Kassberger, S.: F. Black und M.Scholes als Aktuare: Anwendungen der Optionspreistheorie in der Lebensversicherungsmathematik. In: Spremann, K. (Ed.): Versicherung im Umbruch. Springer, 2004. CitationDetails
  • Kiesel, R.; Perraudin, W.; Taylor, A.: An extremes analysis of VaRs for emerging market benchmark bonds. In: Al., G. Bol Et (Ed.): Credit Risk: Measurement, Evaluation and Management. Physica-Verlag, 2004. CitationDetails
  • Kiesel, R.; Bingham, N. H.: Risk Neutral Valuation: An Introduction to the Pricing and Hedging of Financial Derivatives. 2nd Edition. Springer, 2004. CitationDetails
  • Kiesel, R.; Bingham, N. H.; Schmidt, R.: A semi-parametric approach to risk management. In: Quantitative Finance, Vol 3 (2003), p. 426-441. Full textCitationDetails
  • Kiesel, R.; Perraudin, W.; Taylor, A.: The structure of credit risk: Spread volatility and ratings transitions. In: Journal of Risk, Vol 6 (2003), p. 1-27. CitationDetails
  • Kiesel, R.; Bingham, N. H.: Semi-parametric methods in finance: Theoretical foundations. In: Quantitative Finance (2002), p. 241-250. CitationDetails
  • Kiesel, R.; Hu, Y. - T; Perraudin, W.: Estimation of transition matrices for sovereign credit risk. In: Journal of Banking and Finance, Vol 26 (2002) No 7, p. 1383-1406. Full textCitationDetails
  • Kiesel, R.; Stadtmüller, U.: Dimensions of credit risk - Proceedings of the 25th Annual Conference of the Gesellschaft für Klassifikation e.V. In: M. Schwaiger, O. Opitz (Ed.): Exploratory Data Analysis in Empirical Research. Springer, 2002. CitationDetails
  • Kiesel, R.; Kleinow, T.: Sensitivity analysis of credit portfolio models. In: in G. Stahl W. Härdle, T. Kleinow (Ed.): Applied Quantitative Finance. Springer, 2002. CitationDetails
  • Kiesel, R.; Perraudin, W.; Taylor, A.: Credit and interest rate risk. In: Risk Management: Value at risk and beyond, eds.: M.A.H. Dempster and H.K.Moffat,Cambridge University Press (2002), p. 129-144. CitationDetails
  • Kiesel, R.: Nonparametric statistical methods and the pricing of derivative securities. In: Journal of Applied Mathematics & Decision Sciences, Vol 6 (2002) No 1, p. 1-22. Full textCitationDetails
  • Kiesel, R.; Hu, Y. -T; Perraudin, W.; Stahl, G.: Judgmental versus quantitative credit risk measures for sovereigns. In: Preprint (2002). CitationDetails
  • Bingham, N. H.; Kiesel, R.: Semi-parametric modelling in finance: theoretical foundations. In: Quantitative Finance, Vol 2 (2002), p. 241-250. Full textCitationDetails
  • Kiesel, R.; Bingham, N. H.: Modelling asset returns with hyperbolic distributions. In: Knight, J.; Satchel, S. (Ed.): Asset return distributions. Butterworth-Heinemann, 2001, p. 1-20. CitationDetails
  • Kiesel, R.; Bingham, N. H.: Hyperbolic and semi-parametric models in finance. In: Sollich, P.; Coolen, A. C. C.; Houghston, L. P.; ; Streater, R. F. (Ed.): Disordered and Complex Systems. 2001. CitationDetails
  • Kiesel, R.; Perraudin, W.; Taylor, A.: Estimating volatility for long holding periods. In: Measuring Risk in Complex Systems, eds. W.Härdle,J.Franke,G.Stahl, Springer (2000), p. 19-30. CitationDetails
  • Kiesel, R.; Schmid, B.; Risklab, Germany: Aspekte der stochastischen Modellierung von Ausfallwahrscheinlichkeiten in Kreditportfoliomodellen. In: Kreditrisikomanagement, ed.K.Oehler, Schäffer-Poeschel Verlag (2000), p. 51-83. Full textCitationDetails
  • R. Kisel, U. Stadtmüller: Large deviations for weighted sums of independent identically distributed random variables. In: Journal of Mathematical Analysis and Applications, Vol 251 (2000), p. 929-939. CitationDetails
  • Kiesel, R.: Strong laws and summability for phi-mixing sequences of random variables. In: Journal of Theoretical Probability, Vol 11 (1998) No 1, p. 209-224. CitationDetails
  • Kiesel, R.; Stadtmüller, U.: Erdös-Rényi-Shepp laws for phi-mixing sequences of random variables. In: Studia Scientarium Math. Hungarian, Vol 34 (1998), p. 1-7. CitationDetails
  • Kiesel, R.: Strong laws and summability for sequences of phi-mixing random variables taking values in Banach spaces. In: Electronic Communications in Probability, Vol 2 (1997), p. 27-41. CitationDetails
  • Kiesel, R.: The law of the iterated logarithm for certain power series and generalized Nörlund methods. In: Math. Proc. Camb. Phil. Soc., Vol 120 (1996), p. 735-753. CitationDetails
  • Kiesel, R.; Stadtmüller, U.: Erdös-Rényi-Shepp laws and weighted sums of independent identically distributed random variables. In: Journal of Theoretical Probability, Vol 9 (1996) No 4, p. 961-982. CitationDetails
  • Kiesel, R.: Pricing contingent claims in incomplete markets: A quadratic utility approach. 15. Department of Statistics, Birkbeck College 1996. CitationDetails
  • Kiesel, R.: Taubersätze und Starke Gesetze für Potenzreihenverfahren (Dissertation). Universität Ulm 1995. CitationDetails
  • Kiesel, R.: On scales of summability methods. In: Mathematische Nachrichten, Vol 176 (1995), p. 129-138. CitationDetails
  • Kiesel, R.; Baron, S.: Absolute *-summability factors with a power for -methods. In: Analysis, Vol 15 (1995), p. 311-324. CitationDetails
  • Kiesel, R.; Borwein, D.: Weighted means and summability by generalized Nörlund and other methods. In: Journal Math. Analysis and Applications, Vol 183 (1994) No 3, p. 607-619. CitationDetails
  • Kiesel, R.; Stadtmüller, U.: Tauberian- and convexity theorems for certain (N,p,q)-methods. In: Canadian Journal of Mathematics , Vol 46 (1994) No 5, p. 982-994. CitationDetails
  • Kiesel, R.; Baron, S.: Absolute *-convergence factors with a power. In: Journal of Analysis, Vol 2 (1994), p. 116-122. CitationDetails
  • Kiesel, R.: Power series methods and almost sure convergence. In: Math. Proc. Camb. Phil. Soc., Vol 113 (1993), p. 195-204. CitationDetails
  • Kiesel, R.: General Nörlund transforms and power series methods. In: Math. Zeitschrift, Vol 214 (1993), p. 273-286. CitationDetails
  • Kiesel, R.; Stadtmüller, U.: Tauberian theorems for general power series methods. In: Math. Proc. Camb. Phil. Soc., Vol 110 (1991), p. 483-490. CitationDetails