Several hypotheses have been proposed to explain the stock return–inflation relation. The Modigliani and Cohn’s inflation illusion hypothesis has received renewed attention. Another hypothesis is the two-regime hypothesis. We reexamine these hypotheses using long sample data of the US and international data. We find that the inflation illusion hypothesis can explain the post-war negative stock return–inflation relation, but it is not compatible with the pre-war positive relation. Using a structural VAR identification method, we show that there are two regimes with positive and negative stock return–inflation relations not only in each period of the US but also in every developed country we consider. This seems inconsistent with the inflation illusion hypothesis that predicts only a negative relation.

We investigate the determinants of executive stock options (ESOs) and their impact on risky investment and subsequent firm performance in a dynamic setting. We find that, first, the dynamic response of ESOs to growth opportunity and risk is positive and lasts for two to three years. Second, the dynamic response of risky investments to option compensation is positive but converges to zero after three years. More importantly, the positive effect of ESOs on risky investments is observed when CEOs' personal risk-aversion is taken into account. Third, accounting performance responds positively to the risky, option-induced investment, but the dynamic effect lasts only for one year. Meanwhile, when managers undertake more risky investments than what ESOs imply, accounting performance responds negatively to the over-investment.

This study develops an econometric model that incorporates features of price dynamics across assets as well as through time. With the dynamic factors extracted via the Kalman filter, we formulate an asset pricing model, termed the dynamic factor pricing model (DFPM). We then conduct asset pricing tests in the in-sample and out-of-sample contexts. Our analyses show that the ex ante factors are a key component in asset pricing and forecasting. By using the ex ante factors, the DFPM improves upon the explanatory and predictive power of other competing models, including unconditional and conditional versions of the Fama and French (1993) 3-factor model. In particular, the DFPM can explain and better forecast the momentum portfolio returns, which are mostly missed by alternative models.