Solving the Forecast Combination Puzzle Using Double Shrinkages*

Author:

Liu Li1,Hao Xianfeng2,Wang Yudong3

Affiliation:

1. School of Finance Nanjing Audit University China

2. Antai College of Economics and Management Shanghai Jiao Tong University China

3. School of Economics and Management Nanjing University of Science and Technology China

Abstract

AbstractThis study develops a new approach that shrinks the forecast combination weights towards equal weights by using weighted least squares and towards zero weight by using regularization constraints. We reveal the significant predictability of excess returns to the S&P500 index that can be achieved by using this double shrinkage combination (DSC). Furthermore, our DSC approach significantly outperforms the naïve equal‐weighted combination, solving the combination puzzle. The equal‐weight shrinkage has greater effect in economic recessions, whereas the zero‐weight shrinkage dominates in economic expansions. The DSC's superior performance over that of the naïve combination is observed in the application of forecasting macroeconomic indicators.

Funder

National Natural Science Foundation of China

Publisher

Wiley

Subject

Statistics, Probability and Uncertainty,Economics and Econometrics,Social Sciences (miscellaneous),Statistics and Probability

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