The Sophisticated and the Simple: the Profitability of Contrarian Strategies

A variety of variables have been used to form contrarian portfolios, ranging from relatively simple measures, like book‐to‐market, cash flow‐to‐price, earnings‐to‐price and past returns, to more sophisticated measures based on the Ohlson model and residual income model (RIM). This paper investigates whether: (i) contrarian strategies based on RIM perform better or worse than those based on the Ohlson model; (ii) contrarian strategies based on more sophisticated valuation models (e.g. Ohlson and RIM) perform much better than the relatively simpler ranking variables that have been used so extensively in the finance literature. Given that the RIM and Ohlson models require greater information inputs and technical know‐how, and make different implicit assumptions on future abnormal earnings, it is important to ascertain if they offer significantly greater contrarian profits to outweigh the increased costs that they entail. Indeed, our surprising finding is that simple cash flow‐to‐price measures appear to do almost as well as the more sophisticated alternatives. One would have expected the sophisticated models to significantly outperform the simple cash flow to price model for the reasons given by Penman (2007) .     

Loss sensitive investors and positively biased analysts in Hong Kong stock market

Review of Quantitative Finance and Accounting - The Hong Kong stock market is known to be highly volatile. Professional investors have a strong demand for timely information because of the...     

Does the Size Effect Explain the UK Winner-Loser Effect?

Dissanaike (1997) found a long-term winner-loser effect in the UK, within a sample of large (FT500) companies. However, he did not investigate as to whether there was a size effect within his sample, nor did he check to see if it subsumed his winner-loser effect. We find evidence of a size effect within the FT500 sample, and the size and winner-loser effects are not unrelated. But, there is no evidence to suggest that the size effect subsumes the winner-loser effect.     

On the Use of the Log CAR Measure in Event Studies

Cross-sectional averages of log returns have been used to measure shareholder wealth effects in several event studies. No adequate explanation of the implied portfolio strategy has ever been provided in the literature. We argue that the method is biased or does not portray a realistic portfolio strategy. It should therefore be used with caution in the event-study' literature.     

Do Stock Market Investors Overreact?

This paper investigates the evidence on the stock market overreaction hypothesis (ORH), which holds that, if stock prices systematically overshoot as a consequence of excessive investor optimism or pessimism, price reversals should be predictable from past price performance. The ORH stands in contradiction to the efficient markets hypothesis which is a cornerstone of financial economics. This study is unique in the overreaction literature because it is restricted to larger and better-known listed companies, whose shares are more frequently traded. This restriction more or less eliminates two alternative explanations to the overreaction hypothesis: it minimises the influence of bid-ask biases and infrequent trading, and reduces the possibility that reversals are primarily a small-firm phenomenon. The paper also investigates a third alternative explanation, namely that time-varying risk explains the reversal effect. The study employs unbiased methods of return computation and uses data from 1975 to 1991 for nearly 1,000 UK companies. Overall, the evidence appears to be consistent with the overreaction hypothesis, subject to certain qualifications.