Unit operations for gas-liquid mass transfer in reduced gravity environments

Basic scaling rules are derived for converting Earth-based designs of mass transfer equipment into designs for a reduced gravity environment. Three types of gas-liquid mass transfer operations are considered: bubble columns, spray towers, and packed columns. Application of the scaling rules reveals that the height of a bubble column in lunar- and Mars-based operations would be lower than terrestrial designs by factors of 0.64 and 0.79 respectively. The reduced gravity columns would have greater cross-sectional areas, however, by factors of 2.4 and 1.6 for lunar and Martian settings. Similar results were obtained for spray towers. In contract, packed column height was found to be nearly independent of gravity

A Quantile Monte Carlo approach to measuring extreme credit risk

We apply a novel Quantile Monte Carlo (QMC) model to measure extreme risk of various European industrial sectors both prior to and during the Global Financial Crisis (GFC). The QMC model involves an application of Monte Carlo Simulation and Quantile Regression techniques to the Merton structural credit model. Two research questions are addressed in this study. The first question is whether there is a significant difference in distance to default (DD) between the 50% and 95% quantiles as measured by the QMC model. A substantial difference in DD between the two quantiles was found. The second research question is whether relative industry risk changes between the pre-GFC and GFC periods at the extreme quantile. Changes were found with the worst deterioration experienced by Energy, Utilities, Consumer Discretionary and Financials; and the strongest improvement shown by Telecommunication, IT and Consumer goods. Overall, we find a significant increase in credit risk for all sectors using this model as compared to the traditional Merton approach. These findings could be important to banks and regulators in measuring and providing for credit risk in extreme circumstances.Asset Selection, Factor Model, DEA, Quantile Regression

Comparing Australian and US Corporate Default Risk using Quantile Regression

The severe bank stresses of the Global Financial Crisis (GFC) have underlined the importance of understanding and measuring extreme credit risk. The Australian economy is widely considered to have fared much better than the US and most other major world economies. This paper applies quantile regression and Monte Carlo simulation to the Merton structural credit model to investigate the impact of extreme asset value fluctuations on default probabilities of Australian companies in comparison to the USA. Quantile regression allows modelling of the extreme quantiles of a distribution which allows measurement of capital and PDs at the most extreme points of an economic downturn, when companies are most likely to fail. Daily asset value fluctuations of over 600 Australian and US investment and speculative entities are examined over a ten year period spanning pre-GFC and GFC. The events of the GFC also showed how the capital of global banks was eroded as defaults increased. This paper therefore also examines the impact of these fluctuating default probabilities on the capital adequacy of Australian and US banks. The paper finds highly significant variances in default probabilities and capital between quantiles in both Australia and the US, and shows how these variances can assist banks and regulators in calculating capital buffers to sustain banks through volatile times.Classification-JEL:Probability of default; Quantile regression; Australian banks; United States banks.

Visual Acuity does not Moderate Effect Sizes of Higher-Level Cognitive Tasks.

Background/study contextDeclining visual capacities in older adults have been posited as a driving force behind adult age differences in higher-order cognitive functions (e.g., the "common cause" hypothesis of Lindenberger & Baltes, 1994, Psychology and Aging, 9, 339-355). McGowan, Patterson, and Jordan (2013, Experimental Aging Research, 39, 70-79) also found that a surprisingly large number of published cognitive aging studies failed to include adequate measures of visual acuity. However, a recent meta-analysis of three studies (La Fleur and Salthouse, 2014, Psychonomic Bulletin & Review, 21, 1202-1208) failed to find evidence that visual acuity moderated or mediated age differences in higher-level cognitive processes. In order to provide a more extensive test of whether visual acuity moderates age differences in higher-level cognitive processes, we conducted a more extensive meta-analysis of topic.MethodsUsing results from 456 studies, we calculated effect sizes for the main effect of age across four cognitive domains (attention, executive function, memory, and perception/language) separately for five levels of visual acuity criteria (no criteria, undisclosed criteria, self-reported acuity, 20/80-20/31, and 20/30 or better).ResultsAs expected, age had a significant effect on each cognitive domain. However, these age effects did not further differ as a function of visual acuity criteria.ConclusionThe current meta-analytic, cross-sectional results suggest that visual acuity is not significantly related to age group differences in higher-level cognitive performance-thereby replicating La Fleur and Salthouse (2014). Further efforts are needed to determine whether other measures of visual functioning (e.g., contrast sensitivity, luminance) affect age differences in cognitive functioning

Tail Risk for Australian Emerging Market Entities

Whilst the Australian economy is widely considered to have fared better than many of its global counterparts during the Global Financial Crisis, there was nonetheless extreme volatility experienced in Australian financial markets. To understand the extent to which emerging Australia entities were impacted by these extreme events as compared to established entities, this paper compares entities comprising the Emerging Markets Index (EMCOX) to established entities comprising the S&P/ASX 200 Index using four risk metrics. The first two are Value at Risk (VaR) and Distance to Default (DD), which are traditional measures of market and credit risk. The other two focuses on extreme risk in the tail of the distribution and include Conditional Value at Risk (CVaR) and Conditional Distance to Default (CDD), the latter metric being unique to the authors, and which applies CVaR techniques to default measurement. We apply these measures both prior to and during the GFC, and find that Emerging Market shares show higher risk for all metrics used, the spread between the emerging and established portfolios narrows during the GFC period and that the default risk spread between the two portfolios is greatest in the tail of the distribution. This information can be important to both investors and lenders in determining share or loan portfolio mix in extreme economic circumstances. Classification-JEL:Conditional value at risk; Conditional distance to default; Australian emerging markets

Financial Analysis South Dakota Farm Panel Records Program 1975

The data in this report have been obtained from a selected number of farms located in Central South Dakota. It is a summary of data gained in a pilot program for the development of a computerized farm financial information system. For this reason the data in this report cannot be interpreted as representative of all farms or areas in South Dakota. However, it can serve as a guide to those persons with farm operations similar to the ones included in this report. Data is presented in this report on the average of all farms participating in the record keeping activities. It includes data for the high one third of the farms and the low one third of the farms. The high and the low are in terms of net farm income realized and not the high and low for each individual factor. Such data is useful to acquaint oneself with the range of results as well as the average