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Historical simulation approach to the estimation of stochastic discount factor models

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  • Andrei Semenov

Abstract

We propose an approach to the estimation of the parameters of stochastic discount factor (SDF) models which is based on the idea that the next period joint distribution of the variables in a SDF and asset returns can be well approximated by their joint historical distribution. The estimates of the SDF parameters may therefore be found as the values of the parameters at which the mean of the historical distribution of the product of the SDF with an asset return equals one. Each time period, the estimates are updated using the most recent periods of data and hence can change over time. This method can be viewed as an alternative to the approaches that specify a particular functional form relating the SDF parameters to proxies for the state of the world.

Suggested Citation

  • Andrei Semenov, 2008. "Historical simulation approach to the estimation of stochastic discount factor models," Quantitative Finance, Taylor & Francis Journals, vol. 8(4), pages 391-404.
    • Handle: RePEc:taf:quantf:v:8:y:2008:i:4:p:391-404
    DOI: 10.1080/14697680701561365
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    Cited by:

    1. Alexander, Carol & Han, Yang & Meng, Xiaochun, 2023. "Static and dynamic models for multivariate distribution forecasts: Proper scoring rule tests of factor-quantile versus multivariate GARCH models," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1078-1096.

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