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Mixed-Frequency Predictive Regressions with Parameter Learning

Author

Listed:
  • Markus Leippold

    (University of Zurich; Swiss Finance Institute)

  • Hanlin Yang

    (University of Zurich)

Abstract

We explore the performance of mixed-frequency predictive regressions for stock returns from the perspective of a Bayesian investor. We develop a constrained parameter learning approach for sequential estimation allowing for belief revisions. Empirically, we find that mixed-frequency models improve predictability, not only because of the combination of predictors with different frequencies but also due to the preservation of high-frequency features such as time-varying volatility. Temporally aggregated models misspecify the evolution frequency of the volatility dynamics, resulting in poor volatility timing and worse portfolio performance than the mixed-frequency specification. These results highlight the importance of preserving the potential mixed-frequency nature of predictors and volatility in predictive regressions.

Suggested Citation

  • Markus Leippold & Hanlin Yang, 2023. "Mixed-Frequency Predictive Regressions with Parameter Learning," Swiss Finance Institute Research Paper Series 23-39, Swiss Finance Institute, revised Jun 2023.
  • Handle: RePEc:chf:rpseri:rp2339
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    More about this item

    Keywords

    Mixed-frequency data; predictive regressions; stochastic volatility; consumption-wealth ratio; parameter learning; portfolio optimization;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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