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Risk aversion and institutional information disclosure on the European carbon market: A case-study of the 2006 compliance event

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  • Chevallier, Julien
  • Ielpo, Florian
  • Mercier, Ludovic

Abstract

This article evaluates the impact of the 2006 compliance event on changes in investors' risk aversion on the European carbon market using the newly available option prices dataset. Thus, we aim at capturing the specific event that occurred on April 2007 as the European Commission disclosed the 2006 verified emissions data. Following the methodology existing for stock indices, we recover empirically risk aversion adjustments on the period 2006-2007 by estimating first the risk-neutral distribution from option prices and second the actual distribution from futures on the European Climate Exchange. Our results show evidence of a dramatic change in the market perception of risk around the 2006 yearly compliance event that has not been assessed yet.

Suggested Citation

  • Chevallier, Julien & Ielpo, Florian & Mercier, Ludovic, 2009. "Risk aversion and institutional information disclosure on the European carbon market: A case-study of the 2006 compliance event," Energy Policy, Elsevier, vol. 37(1), pages 15-28, January.
  • Handle: RePEc:eee:enepol:v:37:y:2009:i:1:p:15-28
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    1. Robert S. Pindyck, 1994. "Inventories and the Short-Run Dynamics of Commodity Prices," RAND Journal of Economics, The RAND Corporation, vol. 25(1), pages 141-159, Spring.
    2. Emmanuel Jurczenko & Bertrand Maillet & Bogdan Negrea, 2004. "A note on skewness and kurtosis adjusted option pricing models under the Martingale restriction," Quantitative Finance, Taylor & Francis Journals, vol. 4(5), pages 479-488.
    3. H. Bertholon & A. Monfort & F. Pegoraro, 2008. "Econometric Asset Pricing Modelling," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 6(4), pages 407-458, Fall.
    4. Dominique Guégan & Florian Ielpo, 2008. "Flexible time series models for subjective distribution estimation with monetary policy in view," Brussels Economic Review, ULB -- Universite Libre de Bruxelles, vol. 51(1), pages 79-103.
    5. Seifert, Jan & Uhrig-Homburg, Marliese & Wagner, Michael, 2008. "Dynamic behavior of CO2 spot prices," Journal of Environmental Economics and Management, Elsevier, vol. 56(2), pages 180-194, September.
    6. Ait-Sahalia, Yacine & Lo, Andrew W., 2000. "Nonparametric risk management and implied risk aversion," Journal of Econometrics, Elsevier, vol. 94(1-2), pages 9-51.
    7. Rama Cont & Jose da Fonseca, 2002. "Dynamics of implied volatility surfaces," Quantitative Finance, Taylor & Francis Journals, vol. 2(1), pages 45-60.
    8. Jackwerth, Jens Carsten, 2000. "Recovering Risk Aversion from Option Prices and Realized Returns," Review of Financial Studies, Society for Financial Studies, vol. 13(2), pages 433-451.
    9. Bødskov Andersen, Allan & Wagener, Tom, 2002. "Extracting risk neutral probability densities by fitting implied volatility smiles: some methodological points and an application to the 3M Euribor futures option prices," Working Paper Series 198, European Central Bank.
    10. Ernst R. Berndt & Bronwyn H. Hall & Robert E. Hall & Jerry A. Hausman, 1974. "Estimation and Inference in Nonlinear Structural Models," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 3, number 4, pages 653-665, National Bureau of Economic Research, Inc.
    11. Rosenberg, Joshua V. & Engle, Robert F., 2002. "Empirical pricing kernels," Journal of Financial Economics, Elsevier, vol. 64(3), pages 341-372, June.
    12. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    13. Giovanni Barone-Adesi & Robert F. Engle & Loriano Mancini, 2008. "A GARCH Option Pricing Model with Filtered Historical Simulation," Review of Financial Studies, Society for Financial Studies, vol. 21(3), pages 1223-1258, May.
    14. Gourieroux, Christian & Monfort, Alain & Trognon, Alain, 1984. "Pseudo Maximum Likelihood Methods: Theory," Econometrica, Econometric Society, vol. 52(3), pages 681-700, May.
    15. Breeden, Douglas T & Litzenberger, Robert H, 1978. "Prices of State-contingent Claims Implicit in Option Prices," The Journal of Business, University of Chicago Press, vol. 51(4), pages 621-651, October.
    16. Marc Chesney & Luca Taschini, 2008. "The Endogenous Price Dynamics of the Emission Allowances: An Application to CO2 Option Pricing," Swiss Finance Institute Research Paper Series 08-02, Swiss Finance Institute, revised Jan 2008.
    17. Szymon Borak & Wolfgang Härdle & Stefan Trück & Rafal Weron, 2006. "Convenience Yields for CO2 Emission Allowance Futures Contracts," SFB 649 Discussion Papers SFB649DP2006-076, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    18. Fama, Eugene F & French, Kenneth R, 1988. " Business Cycles and the Behavior of Metals Prices," Journal of Finance, American Finance Association, vol. 43(5), pages 1075-1093, December.
    19. Marie Briere, 2006. "Market Reactions to Central Bank Communication Policies :Reading Interest Rate Options Smiles," Working Papers CEB 38, ULB -- Universite Libre de Bruxelles.
    20. Junsoo Lee & Mark Strazicich, 2001. "Testing the null of stationarity in the presence of a structural break," Applied Economics Letters, Taylor & Francis Journals, vol. 8(6), pages 377-382.
    21. Fama, Eugene F & French, Kenneth R, 1987. "Commodity Futures Prices: Some Evidence on Forecast Power, Premiums,and the Theory of Storage," The Journal of Business, University of Chicago Press, vol. 60(1), pages 55-73, January.
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