stock loading is quite consistent over time apart from a temporal drop in the 1975 – 1977 period, leading to rejection of the hypothesis that the size effect is the premium for a narrowly-held risk. Instead, the various size-based style analyses suggest that the small stocks may have been oversold

of aggregate returns indexes and size-sorted portofolios. Although the rejections are due largely to the behavior of small stocks, they cannot be attributed completely to the effects of infrequent trading or timevarying volatilities. Moreover, the rejection of the random walk for weekly returns does

This study examines the empirical relattonship between the return and the total market value of NYSE common stocks. It is found that smaller firms have had htgher risk adjusted returns, on average, than larger lirms. This ‘size effect ’ has been in existence for at least forty years and is evidence

affects more strongly small firm stocks, thus explaining time series variations in their premiums over time. r

. The average household earns an annual return of 16.4 percent, tilts its common stock investment toward high-beta, small, value stocks, and turns over 75 percent of its portfolio annually. Overconfidence can explain high trading levels and the resulting poor performance of individual investors. Our central

the material to offer a wide range of analyses of hitherto puzzling and problematic notions. We thereby effect a theoretical unification and simplification: with a small stock of primitives, we can analyze a number of important philosophical notions with a broad range of applications. But the analyses Lewis

We survey 392 CFOs about the cost of capital, capital budgeting, and capital structure. Large firms rely heavily on present value techniques and the capital asset pricing model, while small firms are relatively likely to use the payback criterion. We find that a surprising number of firms use

It is widely known that when there are errors with a moving-average root close to −1, a high order augmented autoregression is necessary for unit root tests to have good size, but that information criteria such as the AIC and the BIC tend to select a truncation lag (k) that is very small. We

We witness a rapid increase in the number of structured information sources that are available online, especially on the WWW. These sources include commercial databases on product information, stock market information, real estate, automobiles, and entertainment. We would like to use the data

We present an efficient indexing method to locate 1-dimensional subsequences within a collection of sequences, such that the subsequences match a given (query) pattern within a specified tolerance. The idea is to map each data sequence into a small set of multidimensional rectangles in feature