Unintended Consequences of Trade Distortions and Price Controls: A National Tragedy provides a Teaching Moment

The tragedy at Valley Forge during George Washington’s military encampment in the winter of 1777-1778 provides a vivid lesson in economics. Trade disruptions and price controls - mistaken policies of the nascent republic, consistent with the political philosophy of the times - were contributing factors to death of nearly two thousand soldiers camped at Valley Forge. In this paper, we employ a fundamental supply and demand analysis, and then we illustrate a price ceiling and subsequent shortage. The glitter of British entertainments in Philadelphian society and the harshness of the Continental soldiers’ meager existence twenty miles away provide a sharp contrast and sparks the imagination for any student of economics

Refraction of shear zones in granular materials

We study strain localization in slow shear flow focusing on layered granular materials. A heretofore unknown effect is presented here. We show that shear zones are refracted at material interfaces in analogy with refraction of light beams in optics. This phenomenon can be obtained as a consequence of a recent variational model of shear zones. The predictions of the model are tested and confirmed by 3D discrete element simulations. We found that shear zones follow Snell's law of light refraction.Comment: 4 pages, 3 figures, minor changes, jounal ref. adde

Enhance Teamwork Outcomes Through Guanxi

According to a recent article in the Chronicle of Higher Education (April 2011), team assignments are increasingly prevalent in business schools. Not only are they ubiquitous, they are critically important, as our university’s strategic plan states, “collaboration and teamwork are the keys to creating successful leaders.”[1] Despite this prominence, teamwork assignments are often flawed, particularly by students who free-ride on the efforts of others and neither contribute nor learn from the projects. We suggest faculty seek insight from the Asian concept, guanxi, to improve the quality of team dynamics and project outcomes. [1] http://www.philau.edu/strategicinitiatives/dec.ht

Digital Assignments: The Importance Of Pedagogical Context

We assess students appreciation and use of various tools designed to extend effective learning beyond the classroom. For a given tool, results vary depending upon the overall pedagogical approach of the course

Direction-of-Change Forecasts Based on Conditional Variance, Skewness and Kurtosis Dynamics : International Evidence

Recent theoretical work has revealed a direct connection between asset return volatility forecastability and asset return sign forecastability. This suggests that the pervasive volatility forecastability in equity returns could, via induced sign forecastability, be used to produce direction-of-change forecasts useful for market timing. We attempt to do so in an international sample of developed equity markets, with some success, as assessed by formal probability forecast scoring rules such as the Brier score. An important ingredient is our conditioning not only on conditional mean and variance information, but also conditional skewness and kurtosis information, when forming direction-of-change forecasts.Volatility, variance, skewness, kurtosis, market timing, asset management, asset allocation, portfolio management

Direction-of-Change Forecasts for Asian Equity Markets Based on Conditional Variance, Skewness and Kurtosis Dynamics: Evidence from Hong Kong and Singapore

Recent theoretical work has revealed a direct connection between asset return volatility forecastability and asset return sign forecastability. This suggests that the pervasive volatility forecastability in equity returns could, via induced sign forecastability, be used to produce direction-ofchange forecasts useful for market timing. We attempt to do so in the context of two key Asian equity markets, with some success, as assessed by formal probability forecast scoring rules such as the Brier score. An important ingredient is our conditioning not only on conditional variance information, but also conditional skewness and kurtosis information, when forming direction-of-change forecasts.Volatility, variance, skewness, kurtosis, market timing, asset management, asset allocation, portfolio management.

Direction-of-Change Forecasts Based on Conditional Variance, Skewness and Kurtosis Dynamics: International Evidence

Recent theoretical work has revealed a direct connection between asset return volatility forecastability and asset return sign forecastability. This suggests that the pervasive volatility forecastability in equity returns could, via induced sign forecastability, be used to produce direction-of change forecasts useful for market timing. We attempt to do so in an international sample of developed equity markets, with some success, as assessed by formal probability forecast scoring rules such as the Brier score. An important ingredient is our conditioning not only on conditional mean and variance information, but also conditional skewness and kurtosis information, when forming direction-of-change forecasts.Volatility, variance, skewness, kurtosis, market timing, asset management, asset allocation, portfolio management

Direction-of-Change Forecasts Based on Conditional Variance, Skewness and Kurtosis Dynamics : International Evidence

Recent theoretical work has revealed a direct connection between asset return volatility forecastability and asset return sign forecastability. This suggests that the pervasive volatility forecastability in equity returns could, via induced sign forecastability, be used to produce direction-of change forecasts useful for market timing. We attempt to do so in an international sample of developed equity markets, with some success, as assessed by formal probability forecast scoring rules such as the Brier score. An important ingredient is our conditioning not only on conditional mean and variance information, but also conditional skewness and kurtosis information, when forming direction-of-change forecasts.Volatility, variance, skewness, kurtosis, market timing, asset management, asset allocation, portfolio management

Space Plasma Ion Processing of the Lunar Soil: Modeling of Radiation-Damaged Rim Widths on Lunar Grains

Chemically and microstructurally complex altered rims around grains in the finest size fraction (<20 micron) of the lunar regolith are the result of multi-stage processes involving both solar ion radiation damage and nanoscale deposition of impact or sputter-derived vapors. The formation of the rims is an important part of the space weathering process, and is closely linked to key changes in optical reflectance and other bulk properties of the lunar surface. Recent application of field-emission scanning transmission electron microscope techniques, including energy dispersive X-ray spectral imaging, is making it easier to unravel the "nano-stratigraphy" of grain rims, and to delineate the portions of rims that represent Radiation-Amorphized (RA) host grain from overlying amorphous material that represents vapor/sputter deposits. For the portion of rims formed by host grain amorphization (henceforth called RA rims), we have been investigating the feasibility of using Monte Carlo-type ion-atom collision models, combined with experimental ion irradiation data, to derive predictive numerical models linking the width of RA rims to the grain s integrated solar ion radiation exposure time

Value at Risk models with long memory features and their economic performance

We study alternative dynamics for Value at Risk (VaR) that incorporate a slow moving component and information on recent aggregate returns in established quantile (auto) regression models. These models are compared on their economic performance, and also on metrics of first-order importance such as violation ratios. By better economic performance, we mean that changes in the VaR forecasts should have a lower variance to reduce transaction costs and should lead to lower exceedance sizes without raising the average level of the VaR. We find that, in combination with a targeted estimation strategy, our proposed models lead to improved performance in both statistical and economic terms