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Equity premium predictions with adaptive macro indexes


  • Jennie Bai


Fundamental economic conditions are crucial determinants of equity premia. However, commonly used predictors do not adequately capture the changing nature of economic conditions and hence have limited power in forecasting equity returns. To address the inadequacy, this paper constructs macro indexes from large data sets and adaptively chooses optimal indexes to predict stock returns. I find that adaptive macro indexes explain a substantial fraction of the short-term variation in future stock returns and have more forecasting power than both the historical average of stock returns and commonly used predictors. The forecasting power exhibits a strong cyclical pattern, implying the ability of adaptive macro indexes to capture time-varying economic conditions. This finding highlights the importance of using dynamically measured economic conditions to investigate empirical linkages between the equity premium and macroeconomic fundamentals.

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  • Jennie Bai, 2010. "Equity premium predictions with adaptive macro indexes," Staff Reports 475, Federal Reserve Bank of New York.
  • Handle: RePEc:fip:fednsr:475

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    References listed on IDEAS

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    1. repec:eee:econom:v:198:y:2017:i:2:p:231-252 is not listed on IDEAS
    2. Maio, Paulo & Philip, Dennis, 2015. "Macro variables and the components of stock returns," Journal of Empirical Finance, Elsevier, vol. 33(C), pages 287-308.
    3. Gonçalves, Sílvia & McCracken, Michael W. & Perron, Benoit, 2017. "Tests of equal accuracy for nested models with estimated factors," Journal of Econometrics, Elsevier, vol. 198(2), pages 231-252.
    4. Beber, Alessandro & Brandt, Michael & Luisi, Maurizio, 2013. "Economic Cycles and Expected Stock Returns," CEPR Discussion Papers 9528, C.E.P.R. Discussion Papers.

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    Stocks - Rate of return ; Forecasting ; Macroeconomics ; Economic indicators;

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