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Four types of bankruptcy prediction models based on financial statement ratios, cash flows, stock returns, and return standard deviations are compared. Based on a sample of bankruptcies from 1980 to 1991, results indicate that no existing model of bankruptcy adequately captures the data. During the last fiscal year preceding bankruptcy, none of the individual models may be excluded without a loss in explanatory power. If considered in isolation, the cash flow model discriminates most consistently two to three years before bankruptcy. By comparison, the ratio model is the best single model during the year immediately preceding bankruptcy. Quasi-jack-knifing procedures suggest that none of the models can reliably predict bankruptcy more than two years in advance.Other research which compares alternative prediction models on the same data includes Collins (1980) and Hamer (1983).

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The Dow Dividend Strategy recommends the highest-yielding stocks from the 30 Dow Industrials. These stocks have come to be known as the “Dogs of the Dow” since they often include some of the previous year’s worst performers. While the strategy’s successes—and more recently, its failures—have been well documented in the popular press, there have not been any convincing explanations of why the strategy worked. This paper demonstrates that the behavior of these stocks is consistent with the market overreaction hypothesis. In years before the stock market crash of 1987, the dogs were indeed “losers” which went on to become “winners.” But in the post-crash period, the high-yield stocks actually outperformed the market during the previous year. The Dow Dividend Strategy is no longer selecting the true dogs. © 1998 Elsevier Science Inc. All rights reserved.

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This paper examines the profitability of trading strategies derived from stock rankings published in Investor's Business Daily. The best system provides market-adjusted abnormal monthly returns of 1.81% from buying S&P 500 stocks, and a 3.18% abnormal return on an arbitrage portfolio. Stocks selected for trading have above average volatility, but a portion of abnormal return may be a reward for identifying stocks with short-run sustainable price momentum. Results seem indicative of market inefficiency, but the phenomena may be temporary since abnormal returns are lower during the second half of the data set.

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Many studies find that stock returns are related to firm size and the book-to-market ratio. This article provides a theoretical explanation for this phenomenon. We show that profit maximizing homogenous firms should converge to a stable long-run equilibrium in which firm's capital size and growth rates are shaped by the economic environment, and both influence stock returns. Our evidence shows firm convergence towards the optimum profitability size in a changing equilibrium. Firm characteristics reflect sensitivity to the macroeconomic environment. Our model and empirical tests demonstrate a linkage between this sensitivity and the relationship of returns to market value and book-to-market.