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Industry based equity premium forecasts

Author

Listed:
  • Nuno Silva

    (University of Coimbra/GEMF)

Abstract

In this paper we used industry indexes to predict the equity premium in the US. We considered several types of predictive models: i) constant coefficients and constant volatility, ii) drifting coefficients and constant volatility, iii) constant coefficients and stochastic volatility and iv) drifting coefficients and stochastic volatility. The models were estimated through the particle learning algorithm, which is suitable for dealing with the problem that an investor faces in practice, given that it allows the investor to revise the parameters as new information arrives. All the models exhibit similar statistical predictive ability, but stochastic volatility models generate slightly higher utility gains.

Suggested Citation

  • Nuno Silva, 2015. "Industry based equity premium forecasts," GEMF Working Papers 2015-19, GEMF, Faculty of Economics, University of Coimbra.
  • Handle: RePEc:gmf:wpaper:2015-19
    as

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    References listed on IDEAS

    as
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    More about this item

    Keywords

    equity premium prediction; industries; particle filter; combination of forecasts;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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