Sungjun Cho

The Size Premium: What Role Does Macroeconomic Risk Play?

The size effect is alive well but visible only when the economy is in a high volatility regime. This result is robust across different sample periods and model specifications. Independent business cycle and volatility regimes are identified from bivariate regime switching models of the industrial production growth and the small firm premium (SMB). The SMB factor is not priced by the market excess return (RMRF) and the value premium (HML) in the high volatility regime rather than in a recession regime. This new result is not explained by the January effect. An economic story for the size premium is provided through the capital market imperfection hypothesis.

The Cross-Section of Stock Returns and Monetary Policy

This study investigates whether monetary policy shocks identified from Bayesian estimation of New-Keynesian dynamic stochastic general equilibrium (DSGE) models are critical for understanding the risk premium in stock markets. As test assets, I use the cross-section of average returns on either the Fama-French 25 size and B/M sorted portfolios alone or with 30 industry portfolios. Empirical resultsreveal that the implied ICAPMs are at least comparable to or better than the Fama-French three-factor model for the periods of 1980 to 2004. In particular, the permanent monetary policy shocks to inflation target are crucial for capturing the value premium and part of industry risk premium once I account for the capital market imperfection endogenously in New-Keynesian models following the specifications proposed by Graeve (2006). The shocks to investment technology, as a main determinant of the external finance premium, are also important for understanding the value premium.

The Time-Varying Risk Return Tradeoff in the Long-Run

Lundblad (2007, JFE) shows that the risk-return tradeoff is unequivocally positive with a two-century history of equity market data. A further examination of the relation with the UK monthly stock returns from 1836 to 2010 produces rather weak risk-return relation. I show that the risk-return relation is mostly positive but varies considerably over time based on a new nonlinear ICAPM with multivariate GARCH-M terms with the time-varying risk-return tradeoffs and hedging coefficients. The often observed negative risk-return relation is also statistically insignificant with the 95% confidence bounds. The hedging coefficients also vary significantly across time. This complex nonlinearity seems to be the main culprit of the weak risk-return relation.