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Several predetermined variables that reflect levels of bond and stock prices appear to predict returns on common stocks of firms of various sizes, long-term bonds of various default risks, and default-free bonds of various maturities. The returns on small-firm stocks and low-grade bonds are more highly correlated in January than in the rest of the year with previous levels of asset prices, especially prices of small-firm stocks. Seasonality is found in several conditional risk measures, but such seasonality is unlikely to explain, and in some cases is opposite to, the seasonal found in mean returns. Disciplines Finance | Finance and Financial Management Comments At the time of publication, author Robert F. Stambaugh was affiliated with the University of Chicago. Currently, he is a faculty member at the Wharton School at the University of Pennsylvania.

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This article develops a model of the upstairs market where order size, beliefs, and prices are determined endogenously. We test the model's predictions using unique data for 5,625 equity trades during the period 1985 to 1992 that are known to be upstairs transactions and are identified as either buyer or seller initiated. We find that price movements prior to the trade date are significantly positively related to trade size, consistent with information leakage as the block is "shopped" upstairs. Further, the temporary price impact or liquidity effect is a concave function of order size, which may result from upstairs intermediation.

This study uses a longer time period and additional stocks to further investigate the weekend effect. We find consistently negative Monday returns (1) for the S & P Composite as early as 1928, (2) for Exchange-traded stocks of firms of all sizes, and (3) for actively traded over-the-counter (OTC) stocks. The OTC results are based on bid prices and therefore appear to reject specialist-related explanations. For the 30 individual stocks of the Dow Jones Industrial Index, the average correlation between Friday and Monday returns is positive and the highest of all pairs of successive days. The latter finding is inconsistent with fairly general measurement-error explanations. SOME OF THE MOST puzzling empirical findings reported in recent years indicate that the distribution of common stock returns varies by day of the week. Most notably, the average return for Monday (close Friday to close Monday) is significantly negative. Cross [3] and French [6] find negative Monday returns using the Standard and Poor's Composite Index, and Gibbons and Hess [7] find negative Monday returns for the 30 individual stocks of the Dow Jones IndustrialIndex.1 This negative Monday return, or "weekend effect," has yet to be explained.This study undertakes a further investigation of the weekend effect in stock returns. We examine additional time periods, extending the total period covered to 55 years; we examine additional stocks, such as those of small (low-capitalization) firms and those traded over the counter. In all cases, the data exhibit a weekend effect that is at least as strong as that reported in previous studies. The study also readdresses potential explanations for the effect, such as measurement error, but concludes that none of these explanations is satisfactory.The first section presents a history of the weekend effect from 1928 through 1982 based on the Standard and Poor's Composite Index. We essentially double the length of the period (beginning in 1953) examined by French [6]. The results indicate consistently negative Monday returns throughout the 55-year period. During much of the 25-year period from 1928 through 1952, the New York Stock Exchange was open on Saturdays, so Monday's return is then computed from Saturday's close to Monday's close.2 These returns for "one-day" weekends are consistently negative and not significantly different from the "two-day" weekend * University of Pennsylvania and University of Chicago, respectively. ' Other studies suggest that the weekend effect is not confined to the stock market. Stickel [15] and Roll [13] find weekend effects in futures prices. Gibbons and Hess [7] conclude that mean first differences in Treasury Bill returns are not constant throughout the week. 2 Bruch [2] also examines returns by day of the week using the S & P Composite for the ten-year period from 1934-1943. 819 820The Journal of Finance returns reported in previous studies. We do find, though, that Friday's return is lower when Friday is followed by a Saturday trading day. Also, Saturday's return tends to be ...

This paper analyzes the risks and returns of different types of real estate-related firms traded on the New York and American stock exchanges (NYSE and AMEX). We examine the relation between real estate stock portfolio returns and returns on a standard appraisal-based index, and find that lagged values of traded real estate portfolio returns can predict returns on the appraisal-based index after controlling for persistence in the appraisal series. The stock market reflects information about real estate markets that is later imbedded in infrequent property appraisals. Additional analysis suggests that the differences in the return and risk characteristics across different types of traded real estate firms can be explained in part by appealing to real estate market fundamentals relating to the degree of dependence of the real estate firm upon rental cash flows from existing buildings. These findings highlight the heterogeneity of securitized real estate-related firms. Copyright American Real Estate and Urban Economics Association.

This paper examines the behavior of institutional traders. We use unique data on the equity transactions of 21 institutions of differing investment styles which provide a detailed account of the anatomy of the trading process. The data include information on the number of days needed to fill an order and types of order placement strategies employed. We analyze the motivations for trade, the determinants of trade duration, and the choice of order type. The analysis provides some support for the predictions made by theoretical models, but suggests that these models fail to capture important dimensions of trading behavior. Disciplines