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The scale of predictability

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  • Bandi, F.M
  • Perron, B
  • Tamoni, Andrea
  • Tebaldi, C.

Abstract

We introduce a new stylized fact: the hump-shaped behavior of slopes and coefficients of determination as a function of the aggregation horizon when running (forward/backward) predictive regressions of future excess market returns onto past economic uncertainty (as proxied by market variance, consumption variance, or economic policy uncertainty). To justify this finding formally, we propose a novel modeling framework in which predictability is specified as a property of low-frequency components of both excess market returns and economic uncertainty. We dub this property scale-specific predictability. We show that classical predictive systems imply restricted forms of scale-specific predictability. We conclude that for certain predictors, like economic uncertainty, the restrictions imposed by classical predictive systems may be excessively strong.

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  • Bandi, F.M & Perron, B & Tamoni, Andrea & Tebaldi, C., 2018. "The scale of predictability," LSE Research Online Documents on Economics 85646, London School of Economics and Political Science, LSE Library.
  • Handle: RePEc:ehl:lserod:85646
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    2. Faria, Gonçalo & Verona, Fabio, 2020. "The yield curve and the stock market: Mind the long run," Journal of Financial Markets, Elsevier, vol. 50(C).
    3. Kang, Hankil & Kang, Jangkoo & Lee, Changjun, 2017. "Ultimate consumption risk and investment-based stock returns," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 473-486.
    4. Maio, Paulo & Xu, Danielle, 2020. "Cash-flow or return predictability at long horizons? The case of earnings yield," Journal of Empirical Finance, Elsevier, vol. 59(C), pages 172-192.
    5. Martin Lettau & Sydney C. Ludvigson & Sai Ma, 2019. "Capital Share Risk in U.S. Asset Pricing," Journal of Finance, American Finance Association, vol. 74(4), pages 1753-1792, August.
    6. Ilaria Piatti & Fabio Trojani, 2020. "Dividend Growth Predictability and the Price–Dividend Ratio," Management Science, INFORMS, vol. 66(1), pages 130-158, January.
    7. Asgharian, Hossein & Christiansen, Charlotte & Hou, Ai Jun & Wang, Weining, 2020. "Long- and Short-Run Components of Factor Betas: Implications for Stock Pricing," IRTG 1792 Discussion Papers 2020-020, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    8. Neuhierl, Andreas & Varneskov, Rasmus T., 2021. "Frequency dependent risk," Journal of Financial Economics, Elsevier, vol. 140(2), pages 644-675.
    9. Fosten, Jack, 2019. "CO2 emissions and economic activity: A short-to-medium run perspective," Energy Economics, Elsevier, vol. 83(C), pages 415-429.
    10. Lioui, Abraham & Poncet, Patrice, 2019. "Long horizon predictability: An asset allocation perspective," European Journal of Operational Research, Elsevier, vol. 278(3), pages 961-975.
    11. Faria, Gonçalo & Verona, Fabio, 2020. "Time-frequency forecast of the equity premium," Research Discussion Papers 6/2020, Bank of Finland.
    12. Lettau, Martin & Ludvigson, Sydney & Ma, Sai, 2015. "Capital Share Risk and Shareholder Heterogeneity in U.S. Stock Pricing," CEPR Discussion Papers 10335, C.E.P.R. Discussion Papers.

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    Keywords

    long run; predictability; aggregation; risk-return trade-off;
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    JEL classification:

    • F3 - International Economics - - International Finance
    • G3 - Financial Economics - - Corporate Finance and Governance

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