Haugen and Baker (1996) report that a long-short stock selection strategy based on more than 50 measures of accounting information and past return behavior would have generated excess returns of approximately 3% per month. We find that the Haugen and Baker strategies do not provide attractive returns after transaction costs if an investor already has access to strategy portfolios based on book-to-market and momentum. We also provide an extensive analysis of transaction costs over a long sample and we report results of independent interest to researchers in market microstructure.

We examine a sample of 5896 stocks listed on Nasdaq between 1974 and 1988 to see whether the price per share has significant statistical power in forecasting subsequent returns and attrition rates. Consistent with anecdotal evidence, we document a higher mortality rate for lower-priced stocks than for higher-priced issues. Surprisingly, mortality is not related to market capitalization. Our results also hold for subsamples partitioned by industry and issue year. On average, investors are not adequately compensated for this additional mortality risk, earning lower risk-adjusted rates of return on portfolios of lower-priced shares than on portfolios of higher-priced shares.

This paper identifies observable firm-specific attributes that drive momentum. We find that a firm's revenues, costs, and growth options combine to determine the dynamics of its return autocorrelation. We use these insights to implement momentum strategies (buying winners and selling losers) with both numerically simulated returns and CRSP/Compustat data. In both sets of data, momentum strategies that use firms with high revenue growth volatility, low costs, or valuable growth options outperform traditional momentum strategies by approximately 5% per year.

Conventional tests of the predictability of stock returns could be invalid, that is reject the null too frequently, when the predictor variable is persistent and its innovations are highly correlated with returns. We develop a pretest to determine whether the conventional t-test leads to invalid inference and an efficient test of predictability that corrects this problem. Although the conventional t-test is invalid for the dividend–price and smoothed earnings–price ratios, our test finds evidence for predictability. We also find evidence for predictability with the short rate and the long-short yield spread, for which the conventional t-test leads to valid inference.

China is an important counterexample to the findings in the law, institutions, finance, and growth literature: Neither its legal nor financial system is well developed, yet it has one of the fastest growing economies. While the law–finance–growth nexus applies to the State Sector and the Listed Sector, with arguably poorer applicable legal and financial mechanisms, the Private Sector grows much faster than the others and provides most of the economy's growth. The imbalance among the three sectors suggests that alternative financing channels and governance mechanisms, such as those based on reputation and relationships, support the growth of the Private Sector.

We provide empirical evidence on how the practice of competitive benchmarking affects chief executive officer (CEO) pay. We find that the use of benchmarking is widespread and has a significant impact on CEO compensation. One view is that benchmarking is inefficient because it can lead to increases in executive pay not tied to firm performance. A contrasting view is that benchmarking is a practical and efficient mechanism used to gauge the market wage necessary to retain valuable human capital. Our empirical results generally support the latter view. Our findings also suggest that the documented asymmetry in the relationship between CEO pay and luck is explained by the firm's desire to adjust pay for retention purposes and is not the result of rent-seeking behavior on the part of the CEO.