Mimicking portfolios have long been useful in asset pricing research. In most empirical applications, the portfolio weights are assumed to be fixed over time, while in theory they may be functions of the economic state. This paper derives and characterizes mimicking portfolios in the presence of predetermined state variables, or conditioning information. The results generalize and integrate multifactor minimum variance efficiency (Fama (1996)) with conditional and unconditional mean-variance efficiency (Hansen and Richard (1987), Ferson and Siegel (2001)). Empirical examples illustrate the potential importance of time-varying mimicking portfolio weights and highlight challenges in their application.

We compare the performance of organizational forms (M‐form and U‐form) in experimenting with uncertain projects. In our framework, organizational forms affect the information structure of an organization and thus the way to coordinate changes. Compared to the U‐form, the M‐form organization achieves better coordination in “attribute matching” but suffers from coordination in “attribute compatibility” and less gains in specialization. The distinctive advantage of the M‐form is its flexibility in choosing between small‐scale and full‐scale experimentation.

This paper examines volume and volatility dynamics by accounting for market activity measured by the time duration between two consecutive transactions. A time-consistent vector autoregressive (VAR) model is employed to test the dynamic relationship between return volatility and trades using intraday irregularly spaced transaction data. The model is used to identify the informed and uninformed components of return volatility and to estimate the speed of price adjustment to new information. It is found that volatility and volume are persistent and highly correlated with past volatility and volume. The time duration between trades has a negative effect on the volatility response to trades and correlation between trades. Consistent with microstructure theory, shorter time duration between trades implies higher probability of news arrival and higher volatility. Furthermore, bid–ask spreads are serially dependent and strongly affected by the informed trading and inventory costs.