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Macro Factors in UK Excess Bond Returns: Principal Components and Factor-Model Approach

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  • Erdemlioglu, Deniz

Abstract

We use factor augmented predictive regressions to investigate the relationship between excess bond returns and the macro economy. Our application is for the case of United Kingdom. The dimension of the large data set with 127 variables is reduced by the method of principal components and the Onatski (2009) procedure is used to determine the number factors. Our data covers the period 1983:09 - 2006:10. We find that variation in the one year ahead excess returns on 2 to 5-year UK government bonds can be modeled by macroeconomic fundamentals with R-square values varying from 34 percent to 44 percent. Specifically, three macro factors "unemployment" factor, "inflation" factor and "stock market" factor have significant predictive power in explaining the variation in the excess bond returns. Our results provide new evidence against the expectations hypothesis for the case of UK. We contribute to the literature by analyzing the direct link between macroeconomic variables and excess bond returns for a European market rather than the US. Unpredictability of excess bond returns is not the case in the UK either.

Suggested Citation

  • Erdemlioglu, Deniz, 2009. "Macro Factors in UK Excess Bond Returns: Principal Components and Factor-Model Approach," MPRA Paper 28895, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:28895
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    More about this item

    Keywords

    Principal Components Analysis (PCA); Expectations Hypothesis; Excess Bond Returns; Factor Models.;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • E00 - Macroeconomics and Monetary Economics - - General - - - General
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • E4 - Macroeconomics and Monetary Economics - - Money and Interest Rates

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