We demonstrate that a persistent pattern exists in the evolution of the MTB ratio from 1999 to 2023, wherein firms with high (low) MTB ratios tend to maintain those levels over time. The persistence of the MTB ratio is independent of industry effects and cannot be well explained by accounting performance. Intangible investment plays a crucial role in determining the MTB ratio, and its persistence is primarily maintained through continued internal intangible investment rather than external mergers and acquisitions. Moreover, although U.S. firms have increased their investment in intangible assets over the past 25 years, the gap between high- and low-MTB firms in intangible investment has widened. Our results suggest that the basis of stock value has shifted from tangible to intangible investments over time.

We examine the implications of short-run and long-run consumption risks on the momentum and long-term contrarian profits and the value premium in a unified economic framework. By introducing time-varying firm cash flow exposures to the short-run and long-run shocks in consumption growth, we find the otherwise standard intertemporal asset pricing model goes a long way toward generating the momentum and long-term contrarian profits and the value premium. The model also reproduces the size effect, the pairwise correlations between the profitabilities of these investment strategies, and the performance of the standard CAPM and the consumption CAPM in explaining these well-documented return behaviors. Received January 25, 2016; editorial decision July 21, 2016 by Editor Leonid Kogan.

In this study we show that both the price impact of trades and serial correlation in trade direction are positively and significantly related to the probability of information-based trading (PIN). The positive relation remains significant even after controlling for the effects of stock attributes. Higher trading activity (i.e., shorter intervals between trades) induces both larger price impact and stronger positive serial correlation in trade direction. The effect of time interval between trades on quote revision is stronger for stocks with higher PIN values. These results provide direct empirical support for the information models of trade and quote revision.