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Conditional variance forecasts for long-term stock returns

Author

Listed:
  • Enno Mammen

    () (University of Heidelberg, Germany)

  • Jens Perch Nielsen

    () (Cass Business School, City, University of London, UK)

  • Michael Scholz

    () (University of Graz, Austria)

  • Stefan Sperlich

    () (Universite de Geneve, Switzerland)

Abstract

In this paper, we apply machine learning to forecast the conditional variance of long-term stock returns measured in excess of different benchmarks, including the short-term interest rate, long-term interest rate, earnings-by-price ratio, and inflation. In particular, we apply and implement in a two-step procedure a fully nonparametric smoother with the covariates and the smoothing parameters chosen via cross-validation. We find that volatility forecastability is much less important at longer horizons regardless of the chosen model and that the homoscedastic historical average of the squared return prediction errors gives an adequate approximation of the unobserved realized conditional variance for both the one-year and five-year horizon.

Suggested Citation

  • Enno Mammen & Jens Perch Nielsen & Michael Scholz & Stefan Sperlich, 2019. "Conditional variance forecasts for long-term stock returns," Graz Economics Papers 2019-08, University of Graz, Department of Economics.
  • Handle: RePEc:grz:wpaper:2019-08
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    File URL: http://www100.uni-graz.at/vwlwww/forschung/RePEc/wpaper/2019-08.pdf
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    More about this item

    Keywords

    Benchmark; Cross-validation; Prediction; Stock return volatility; Long-term forecasts; Overlapping returns; Autocorrelation;

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies

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