The Nonlinear Multidimensional Relationship Between Stock Returns and the Macroeconomy. Chen, P. & Smith, A. Applied Economics, 45(35):4985–4999, Routledge, 2013.
Paper abstract bibtex We use nonparametric dimension-reduction methods to extract from a set of 15 macroeconomic variables the risk factors that are priced in the stock market. The dominant factor moves with the business cycle but, because it is a nonlinear function of observed macroeconomic variables, it captures a rich set of interactions. Low-credit risk and low-inflationary expectations have a greater positive effect on stock returns when leading macroeconomic indicators are high relative to current economic activity, i.e. early in the business cycle as the economy emerges from recession. High-stock returns also arise in periods when the economy is booming relative to its leading indicators, but such periods tend to portend crashes.
@article{chen2013nonlinear,
title={The Nonlinear Multidimensional Relationship Between Stock Returns and the Macroeconomy},
author={Chen, Pian and Smith, Aaron},
journal={Applied Economics},
volume={45},
number={35},
pages={4985--4999},
year={2013},
url={https://files.asmith.ucdavis.edu/2013_AE_CS_SIR.pdf},
keywords={finance},
abstract={We use nonparametric dimension-reduction methods to extract from a set of 15 macroeconomic variables the risk factors that are priced in the stock market. The dominant factor moves with the business cycle but, because it is a nonlinear function of observed macroeconomic variables, it captures a rich set of interactions. Low-credit risk and low-inflationary expectations have a greater positive effect on stock returns when leading macroeconomic indicators are high relative to current economic activity, i.e. early in the business cycle as the economy emerges from recession. High-stock returns also arise in periods when the economy is booming relative to its leading indicators, but such periods tend to portend crashes.},
publisher={Routledge}
}
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The dominant factor moves with the business cycle but, because it is a nonlinear function of observed macroeconomic variables, it captures a rich set of interactions. Low-credit risk and low-inflationary expectations have a greater positive effect on stock returns when leading macroeconomic indicators are high relative to current economic activity, i.e. early in the business cycle as the economy emerges from recession. High-stock returns also arise in periods when the economy is booming relative to its leading indicators, but such periods tend to portend crashes.","publisher":"Routledge","bibtex":"@article{chen2013nonlinear,\r\n title={The Nonlinear Multidimensional Relationship Between Stock Returns and the Macroeconomy},\r\n author={Chen, Pian and Smith, Aaron},\r\n journal={Applied Economics},\r\n volume={45},\r\n number={35},\r\n pages={4985--4999},\r\n year={2013},\r\n\turl={https://files.asmith.ucdavis.edu/2013_AE_CS_SIR.pdf},\r\n\tkeywords={finance},\r\n\tabstract={We use nonparametric dimension-reduction methods to extract from a set of 15 macroeconomic variables the risk factors that are priced in the stock market. The dominant factor moves with the business cycle but, because it is a nonlinear function of observed macroeconomic variables, it captures a rich set of interactions. Low-credit risk and low-inflationary expectations have a greater positive effect on stock returns when leading macroeconomic indicators are high relative to current economic activity, i.e. early in the business cycle as the economy emerges from recession. High-stock returns also arise in periods when the economy is booming relative to its leading indicators, but such periods tend to portend crashes.},\r\n publisher={Routledge}\r\n}\r\n\r\n\r\n","author_short":["Chen, P.","Smith, A."],"key":"chen2013nonlinear","id":"chen2013nonlinear","bibbaseid":"chen-smith-thenonlinearmultidimensionalrelationshipbetweenstockreturnsandthemacroeconomy-2013","role":"author","urls":{"Paper":"https://files.asmith.ucdavis.edu/2013_AE_CS_SIR.pdf"},"keyword":["finance"],"metadata":{"authorlinks":{"smith, a":"https://asmith.ucdavis.edu/"}}},"bibtype":"article","biburl":"https://www.dropbox.com/s/1yaa9wha4jhlrgu/pubs.bib?dl=1","creationDate":"2020-03-23T21:37:30.534Z","downloads":2,"keywords":["finance"],"search_terms":["nonlinear","multidimensional","relationship","between","stock","returns","macroeconomy","chen","smith"],"title":"The Nonlinear Multidimensional Relationship Between Stock Returns and the Macroeconomy","year":2013,"dataSources":["m3trFABzuGWj6pcfa","4PiJhMSXhsNKJ9rxM"]}