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Robust Estimation of Risk-Neutral Moments

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  • Manuel Ammann

    ()

  • Alexander Feser

    ()

Abstract

This study provides an in-depth analysis of how to estimate risk-neutral moments robustly. A simulation and an empirical study show that estimating risk-neutral moments presents a trade-off-between (1) the bias of estimates caused by a limited strike price domain and (2) the variance of estimates induced by mirco-structural noise. The best trade-off is offered by option-implied quantile moments estimated from a volatility surface interpolated with a local-linear kernel regression and extrapolated linearly. A similarly good trade-off is achieved by estimating regular central option-implied moments from a volatility surface interpolated with a cubic smoothing spline and flat extrapolation.

Suggested Citation

  • Manuel Ammann & Alexander Feser, 2019. "Robust Estimation of Risk-Neutral Moments," Working Papers on Finance 1902, University of St. Gallen, School of Finance.
  • Handle: RePEc:usg:sfwpfi:2019:02
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    File URL: http://ux-tauri.unisg.ch/RePEc/usg/sfwpfi/WPF-1902.pdf
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    More about this item

    Keywords

    risk-neutral moments; risk-neutral distribution;

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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