## A Global Macroeconomic Risk Explanation for Momentum and Value Thursday, 19 May, 2016

**A related paper has been added to:**

#28 - Value and Momentum across Asset Classes

**Authors: **Cooper, Mitrache, Priestley

**Title: **A Global Macroeconomic Risk Explanation for Momentum and Value

**Link:** http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2768040

**Abstract:**

Value and momentum returns and combinations of them are explained by their loadings on global macroeconomic risk factors across both countries and asset classes. These loadings describe why value and momentum have positive return premia and why they are negatively correlated. The global macroeconomic risk factor model also performs well in summarizing the cross section of various additional asset classes. The findings identify the source of the common variation in expected returns across asset classes and countries suggesting that markets are integrated.

**Notable quotations from the academic research paper:**

"U.S. macreconomic risk factors can successfully describe the return premia on both value and momentum strategies, and combinations of them across both countries and asset classes. In addition, it can explain the negative correlation between these two return premia. We present three main results.

First, the positive return premia on value and momentum, across both asset classes and countries, can be explained by the estimated prices of risk and loadings on the global risk factors. For example, the value, momentum, and combination return premia that are aggregated across all asset classes and all countries are 0.29%, 0.34%, and 0.32% per month, respectively, and they are statistically significant. The global macroeconomic factor model produces expected returns that are 87%, 109%, and 103% of the actual return premia, respectively, with small and statistically insignificant pricing errors. We find similar results for separate asset classes and across different countries, thus, offering a unified macroeconomic risk explanation of value and momentum return premia.

The second result is that the negative correlation between the return premia can be explained by their differing factor loadings. For example, for the aggregated value, momentum, and combination return premia, the factor loadings on the global industrial production factor are -0.34 for value, 1.77 for momentum, and 0.80 for the combination. For global unexpected inflation they are -2.20, 7.81, and 3.16. For the change in expected inflation they are -1.69, 3.92, and 1.31. For global term structure they are 0.35, -0.01, and 0.17, and for global default risk they are -0.04, 0.17, and 0.07. Based on these loadings, we calculate the expected returns of the return premia and compare the expected

return correlations with the correlations of the return premia. For example, remaining with aggregated value and momentum across all asset classes and markets, the actual correlation between the value and momentum strategies is -0.48, whereas the implied correlation of the two strategies from their expected returns is -0.47. We also observe differing factor loadings within each asset class and country. These differences in the factor loadings allow us to match the actual negative correlation between value and momentum return premia with a negative correlation between the expected returns of value and momentum strategies across asset classes and countries.

The third result shows that the global macroeconomic factor model does a good job in explaining the return premia on the combinations of the value and momentum strategies both in the time series and cross section. This is interesting since Asness, Moskowitz, and Pedersen (2013) note that because of the opposite sign exposure of value and momentum to liquidity risk, the equal-weighted (50/50) combination is neutral to liquidity risk. However, we show that this 50/50 combination is not neutral to global macroeconomic risk even if the value and momentum return premia have opposite sign exposures with respect to the global macroeconomic factors. These exposures have different magnitudes and this is clearly seen when we examine the loadings of the combination strategies."

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