The Effects of Credit Risk on Dynamic Portfolio Management: A New Computational Approach

The study investigates the role of credit risk in a continuous time stochastic asset allocation model, since the traditional dynamic framework does not provide credit risk flexibility. The general model of the study extends the traditional dynamic efficiency framework by explicitly deriving the optimal value function for the infinite horizon stochastic control problem via a weighted volatility measure of market and credit risk. The model's optimal strategy was then compared to that obtained from a benchmark Markowitz-type dynamic optimization framework to determine which specification adequately reflects the optimal terminal investment returns and strategy under credit and market risks. The paper shows that an investor's optimal terminal return is lower than typically indicated under the traditional mean-variance framework during periods of elevated credit risk. Hence I conclude that, while the traditional dynamic mean-variance approach may indicate the ideal, in the presence of credit-risk it does not accurately reflect the observed optimal returns, terminal wealth and portfolio selection strategies.

Developing an Agriculture-Related Digital Project

With the increasing expectation of information searchers for all information to be available online, digital projects are growing in number and importance. These projects allow libraries to become producers, if not of content, then of new accessibility options for their patrons. One librarian’s experience in the development and coordination of a digital project in an academic setting is presented, in order to demonstrate potential best practices for similar projects. Selection, coordination, standards, outsourcing, and funding of projects are all discussed. It is possible relatively quickly and inexpensively to produce a useful, quality digital project.