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The Keys of Predictability: A Comprehensive Study


  • Giovanni Barone-Adesi

    (University of Lugano; Swiss Finance Institute)

  • Antonietta Mira

    (Università della Svizzera italiana - InterDisciplinary Institute of Data Science)

  • Matteo Pisati

    (Universita' della Svizzera Italiana)


The problem of market predictability can be decomposed into two parts: predictive models and predictors. At first, we show how the joint employment of model selection and machine learning models can dramatically increase our capability to forecast the equity premium out-of-sample. Secondly, we introduce batteries of powerful predictors which brings the monthly S&P500 R-square to a high level of 24%. Finally, we prove how predictability is a generalized characteristic of U.S. equity markets. For each of the three parts, we consider potential and challenges posed by the new approaches in the asset pricing field.

Suggested Citation

  • Giovanni Barone-Adesi & Antonietta Mira & Matteo Pisati, 2019. "The Keys of Predictability: A Comprehensive Study," Swiss Finance Institute Research Paper Series 19-15, Swiss Finance Institute, revised Apr 2019.
  • Handle: RePEc:chf:rpseri:rp1915

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    Markets Predictability; Machine Learning; Model Selection;

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