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The forecasting performance of German stock option densities

Author

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  • Ben R. Craig
  • Ernst Glatzer
  • Joachim G. Keller
  • Martin Scheicher

Abstract

In this paper the authors estimate risk-neutral densities (RND) for the largest euro-area stock market (the index of which is the German DAX), reporting their statistical properties, and evaluating their forecasting performance. The authors have applied an innovative test procedure to a new, rich, and accurate data set. They have two main results. First, They have recorded strong negative skewness in the densities. Second, they find evidence for a significant difference between the actual density and the risk-neutral density, leading to the conclusion that market participants were surprised by the extent of both the rise and the fall of the DAX.

Suggested Citation

  • Ben R. Craig & Ernst Glatzer & Joachim G. Keller & Martin Scheicher, 2003. "The forecasting performance of German stock option densities," Working Papers (Old Series) 0312, Federal Reserve Bank of Cleveland.
    • Handle: RePEc:fip:fedcwp:0312
    DOI: 10.26509/frbc-wp-200312
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    10. Keller, Joachim G. & Craig, Ben R., 2002. "The Empirical Performance of Option Based Densities of Foreign Exchange," Discussion Paper Series 1: Economic Studies 2002,07, Deutsche Bundesbank.
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    Cited by:

    1. Pedro Serrano & Antoni Vaello‐Sebastià & M. Magdalena Vich Llompart, 2024. "International evidence of the forecasting ability of option‐implied distributions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(5), pages 1447-1464, August.
    2. repec:ehu:dfaeii:6739 is not listed on IDEAS
    3. Didier Sornette & Peter Cauwels & Georgi Smilyanov, 2017. "Can We Use Volatility to Diagnose Financial Bubbles? Lessons from 40 Historical Bubbles," Swiss Finance Institute Research Paper Series 17-27, Swiss Finance Institute.
    4. Scharnagl, Michael & Stapf, Jelena, 2015. "Inflation, deflation, and uncertainty: What drives euro-area option-implied inflation expectations, and are they still anchored in the sovereign debt crisis?," Economic Modelling, Elsevier, vol. 48(C), pages 248-269.
    5. repec:hum:wpaper:sfb649dp2005-021 is not listed on IDEAS
    6. Belén Nieto & Gonzalo Rubio, 2007. "Measuring time-varying economic fears with consumption-based stochastic discount factors," Economics Working Papers 1029, Department of Economics and Business, Universitat Pompeu Fabra, revised Sep 2007.
    7. Kaufmann Sylvia & Scheicher Martin, 2006. "A Switching ARCH Model for the German DAX Index," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 10(4), pages 1-37, December.
    8. Scharnagl, Michael & Stapf, Jelena, 2014. "Inflation, deflation, and uncertainty: What drives euro area option-implied inflation expectations and are they still anchored in the sovereign debt crisis?," Discussion Papers 24/2014, Deutsche Bundesbank.
    9. Francisco Alonso & Roberto Blanco & Gonzalo Rubio, 2009. "Option-implied preferences adjustments, density forecasts, and the equity risk premium," Spanish Economic Review, Springer;Spanish Economic Association, vol. 11(2), pages 141-164, June.
    10. Härdle, Wolfgang Karl & Hlávka, Zdeněk, 2005. "Dynamics of state price densities," SFB 649 Discussion Papers 2005-021, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    11. Francisco Alonso & Roberto Blanco & Gonzalo Rubio, 2005. "Testing the forecasting performace of IBEX 35 option implied risk neutral densities," Working Papers 0504, Banco de España.

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    More about this item

    Keywords

    Stock market - Germany; Stock options;

    JEL classification:

    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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