scholarly journals Does the stock market react to unexpected inflation differently across the business cycle?

2009 ◽  
Vol 19 (24) ◽  
pp. 1947-1959 ◽  
Author(s):  
Chao Wei
Author(s):  
Jesper Rangvid

This chapter studies the characteristics of the most important and well-known factors. Factor portfolios are portfolios of stocks based on certain characteristics, such as the size of the company, the price of the stock in relation to, e.g., the earnings of the company, the sector within which the firm operates, etc.Factors that perform better than the overall stock market tend to suffer more during recessions. To compensate investors for their underperformance during recessions, returns on these factors during expansions are so high that average stock returns over the full business cycle end out being high. Conversely, those factors that provide lower average returns than the overall stock market do so because they perform relatively better during recessions. The business cycle again plays an important role for understanding stock-market patterns.


2002 ◽  
Vol 182 ◽  
pp. 96-105 ◽  
Author(s):  
Denise R. Osborn ◽  
Marianne Sensier

This paper discusses recent research at the Centre for Growth and Business Cycle Research on the prediction of the expansion and recession phases of the business cycle for the UK, US, Germany, France and Italy. Financial variables are important predictors in these models, with the stock market playing a key role in the US but not the European countries, including the UK. In contrast, international linkages are important for the European countries. Our models suggest that the US and German economies have now emerged from the recession of 2001, and that all five countries will be in expansion during the third quarter of this year.


2011 ◽  
Vol 47 (1) ◽  
pp. 137-158 ◽  
Author(s):  
Henri Nyberg

AbstractIn the empirical finance literature, findings on the risk-return tradeoff in excess stock market returns are ambiguous. In this study, I develop a new qualitative response (QR)-generalized autoregressive conditional heteroskedasticity-in-mean (GARCH-M) model combining a probit model for a binary business cycle indicator and a regime-switching GARCH-M model for excess stock market return with the business cycle indicator defining the regime. Estimation results show that there is statistically significant variation in the U.S. excess stock returns over the business cycle. However, consistent with the conditional intertemporal capital asset pricing model (ICAPM), there is a positive risk-return relationship between volatility and expected return independent of the state of the economy.


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