Abstract

This paper investigates the presence of nonlinear influences in the relationship between stock returns and the macroeconomy is examined for eight countries. The markets chosen are Belgium, Canada, France, Germany, Ireland, Japan, U.K. and the U.S. Specifically we analyse both the contemporaneous (asset pricing) relationship and the lagged (return predictability) relationship. Significantly the asset pricing relationship highlights the importance of accounting for variations in the relationships between bear markets and other states. Nonlinearity is accounted for via regime switching using a smooth transition regression (STR) model with the world market return as the transition variable. There is evidence of nonlinearity in all countries. Given the potentially complex nonlinearities in the determination of stock market prices, the possibility of multiple regimes (MRSTR) is also investigated. With the exception of Belgium, all markets exhibit evidence of multiple regimes. Results show that covariance with the world market portfolio increases during 'crisis' regimes, complementing the findings of Longin and Solnik (2001) and Ang, Chen and Xing (2004). Interest rate and inflation variables are strong determinants of stock returns while dividend yields and oil prices only influence returns in regimes identified by multiple regime models. Industrial production growth is not a significant factor. Out-of-sample forecasting of the nonlinear models is not superior to that of the linear models. However the smooth transition regression models predict direction more frequently than linear specifications. Analysis of return predictability produces results consistent with the standard stylised facts, i.e. that the dividend yield and term structure variables are important predictors of future stock returns.

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