Asset Pricing Model Specification and the Term Structure Evidence

In this paper, a set of tests of models of relative capital asset pricesis developed. The tests are used to examine how well the models explain maturity premiums on Government bonds, though they are perfectly general and hence could be applied to stocks or other assets. Allowance is made in the tests for the nonobservability of investors' optimal per capita consumption (or expected marginal utility). It is found that the returns on Government bonds bear a systematic risk which is better measured by their covariability with aggregate per capita consumption than with the returns on the NYSE stock market index, the latter being the surrogate-wealth portfolio typically used to measure risk in the traditional Sharpe-Lintner-Mossin CAPM.

Surprise volume and heteroskedasticity in equity market returns

Heterosedasticity in returns may be explainable by trading volume. We use different volume variables, including surprise volume - i.e. unexpected above-avergae trading activity - which is derived from uncorrelated volume innovations. Assuming eakly exogenous volume, we extend the Lamoureux and Lastrapes (1990) model by an asymmetric GARCH in-mean specification following Golstein et al. (1993). Model estimation for the U.S. as well as six large equity markets shows that surprise volume superior model fit and helps to explain volatility persistence as well as excess kurtosis. Surprise volume reveals a significant positive market risk premium, asymmetry, and a surprise volume effect in conditional variance. The findings suggest that, e.g., a surprise volume shock (breakdown) - i.e. large (small) contemporaneous and small (large) lagged surprise volume - relates to increased (decreased) conditional market variance and return. --ARCH,trading volume,return volume dependence,asymmetric volatility,market risk premium,leverage effect

Surprise Volume and Heteroskedasticity in Equity Market Returns

Heteroskedasticity in returns may be explainable by trading volume. We use different volume variables, including surprise volume---i.e. unexpected above-average trading activity---which is derived from uncorrelated volume innovations. Assuming weakly exogenous volume, we extend the Lamoureux and Lastrapes (1990) model by an asymmetric GARCH in-mean specification following Golsten et al. (1993). Model estimation for the U.S. as well as six large equity markets shows that surprise volume provides superior model fit and helps to explain volatility persistence as well as excess kurtosis. Surprise volume reveals a significant positive market risk premium, asymmetry, and a surprise volume effect in conditional variance. The findings suggest that, e.g., a surprise volume shock (breakdown)---i.e. large (small) contemporaneous and small (large) lagged surprise volume---relates to increased (decreased) conditional market variance and return.ARCH, trading volume, return volume dependence, asymmetric volatility, market risk premium, leverage effect

Japanese banks' bad loans: What happened?

In this paper we trace the increase in Japanese banks' loan spreads and ex ante riskiness of their loan portfolios in the late 1980s and early 1990s. We show that within the three sets of city, trust, and long-term banks, the banks with the highest late-1980s capital deficiencies vis-a-vis the then-impending BIS capital standards had the highest growth rates in risky lending. They also had the highest short-term growth rates in retained earnings which count as Tier I capital. We describe how banks were led to enhance their BIS capital ratios in this way because of the inflexible loan loss provisioning and write-off procedures they faced in Japan. Taken together, the events illustrate the perils of partial regulatory change, whether in the process of deregulation or "new-regulation" as the BIS standards were, when the affected regulations are part of an inter-related system of regulations, incentives, and economic agents' decision rules

BIS capital regulations and Japanese banks' bad loan problems

We present evidence that the loan problems of Japanese banks are related to the introduction of the 1992 BIS capital regulations. The cross-sectional correlation between the major twenty-one banks' prior-to-1992 BIS capital deficiencies and their risky lending is around 50%. The risky lending generated higher short-term retained earnings and thus increases in capital. More capital-deficient banks also used the external capital market less, indicating greater asymmetry-of-information problems for the weaker banks. Regional II banks that were not affected by the BIS regulations did not increase their risky lending, while their brethren with overseas operations did. Finally, we find no evidence in excess returns on Japanese banks' stocks that the BIS regulations ex ante benefited them

Terminal restriction fragment length polymorphism data analysis for quantitative comparison of microbial communities

Includes bibliographical references (page 932).Terminal restriction fragment length polymorphism (T-RFLP) is a culture-independent method of obtaining a genetic fingerprint of the composition of a microbial community. Comparisons of the utility of different methods of (i) including peaks, (ii) computing the difference (or distance) between profiles, and (iii) performing statistical analysis were made by using replicated profiles of eubacterial communities. These samples included soil collected from three regions of the United States, soil fractions derived from three agronomic field treatments, soil samples taken from within one meter of each other in an alfalfa field, and replicate laboratory bioreactors. Cluster analysis by Ward's method and by the unweighted-pair group method using arithmetic averages (UPGMA) were compared. Ward's method was more effective at differentiating major groups within sets of profiles; UPGMA had a slightly reduced error rate in clustering of replicate profiles and was more sensitive to outliers. Most replicate profiles were clustered together when relative peak height or Hellinger-transformed peak height was used, in contrast to raw peak height. Redundancy analysis was more effective than cluster analysis at detecting differences between similar samples. Redundancy analysis using Hellinger distance was more sensitive than that using Euclidean distance between relative peak height profiles. Analysis of Jaccard distance between profiles, which considers only the presence or absence of a terminal restriction fragment, was the most sensitive in redundancy analysis, and was equally sensitive in cluster analysis, if all profiles had cumulative peak heights greater than 10,000 fluorescence units. It is concluded that T-RFLP is a sensitive method of differentiating between microbial communities when the optimal statistical method is used for the situation at hand. It is recommended that hypothesis testing be performed by redundancy analysis of Hellinger-transformed data and that exploratory data analysis be performed by cluster analysis using Ward's method to find natural groups or by UPGMA to identify potential outliers. Analyses can also be based on Jaccard distance if all profiles have cumulative peak heights greater than 10,000 fluorescence units

Stock Return Seasonalities and the Tax-Loss Selling Hypothesis: Analysis of the Arguments and Australian Evidence

A ‘tax-loss selling’ hypothesis has frequently been advanced to explain the ‘January effect’ reported in this issue by Keim. This paper concludes that U.S. tax laws do not unambiguously predict such an effect. Since Australia has similar tax laws but a July–June tax year, the hypothesis predicts a small-firm July premium. Australian returns show pronounced December–January and July–August seasonals, and a premium for the smallest-firm decile of about four percent per month across all months. This contrasts with the U.S. data in which the small-firm premium is concentrated in January. We conclude that the relation between the U.S. tax year and the January seasonal may be more correlation than causation

Reference hydrologic networks II: using reference hydrologic networks to assess climate-driven changes in streamflow

Reference hydrologic networks (RHNs) can play an important role in monitoring for changes in the hydrological regime related to climate variation and change. Currently, the literature concerning hydrological response to climate variations is complex and confounded by the combinations of many methods of analysis, wide variations in hydrology, and the inclusion of data series that include changes in land use, storage regulation and water use in addition to those of climate. Three case studies that illustrate a variety of approaches to the analysis of data from RHNs are presented and used, together with a summary of studies from the literature, to develop approaches for the investigation of changes in the hydrological regime at a continental or global scale, particularly for international comparison. We present recommendations for an analysis framework and the next steps to advance such an initiative. There is a particular focus on the desirability of establishing standardized procedures and methodologies for both the creation of new national RHNs and the systematic analysis of data derived from a collection of RHNs

Reference hydrologic networks I: the status and potential future directions of national reference hydrologic networks for detecting trends

Identifying climate-driven trends in river flows on a global basis is hampered by a lack of long, quality time series data for rivers with relatively undisturbed regimes. This is a global problem compounded by the lack of support for essential long-term monitoring. Experience demonstrates that, with clear strategic objectives, and the support of sponsoring organizations, reference hydrologic networks can constitute an exceptionally valuable data source to effectively identify, quantify and interpret hydrological change—the speed and magnitude of which is expected to a be a primary driver of water management and flood alleviation strategies through the future—and for additional applications. Reference hydrologic networks have been developed in many countries in the past few decades. These collections of streamflow gauging stations, that are maintained and operated with the intention of observing how the hydrology of watersheds responds to variations in climate, are described. The status of networks under development is summarized. We suggest a plan of actions to make more effective use of this collection of networks