How many independent bets are there?

The benefits of portfolio diversification is a central tenet implicit to modern financial theory and practice. Linked to diversification is the notion of breadth. Breadth is correctly thought of as the number of in- dependent bets available to an investor. Conventionally applications us- ing breadth frequently assume only the number of separate bets. There may be a large discrepancy between these two interpretations. We uti- lize a simple singular-value decomposition (SVD) and the Keiser-Gutman stopping criterion to select the integer-valued effective dimensionality of the correlation matrix of returns. In an emerging market such as South African we document an estimated breadth that is considerably lower than anticipated. This lack of diversification may be because of market concentration, exposure to the global commodity cycle and local currency volatility. We discuss some practical extensions to a more statistically correct interpretation of market breadth, and its theoretical implications for both global and domestic investors.Comment: Less technical rewrite. 12 Pages, 6 Figures (.eps

A simple scheme for allocating capital in a foreign exchange proprietary trading firm

We present a model of capital allocation in a foreign exchange proprietary trading firm. The owner allocates capital to individual traders, who operate within strict risk limits. Traders specialize in individual currencies, but are given discretion over their choice of trading rule. The owner provides the simple formula that determines position sizes – a formula that does not require estimation of the firm-level covariance matrix. We provide supporting empirical evidence of excess risk-adjusted returns to the firm-level portfolio, and we discuss a modification of the model in which the owner dictates the choice of trading rule

Can modeling of HIV treatment processes improve outcomes? Capitalizing on an operations research approach to the global pandemic

<p>Abstract</p> <p>Background</p> <p>Mathematical modeling has been applied to a range of policy-level decisions on resource allocation for HIV care and treatment. We describe the application of classic operations research (OR) techniques to address logistical and resource management challenges in HIV treatment scale-up activities in resource-limited countries.</p> <p>Methods</p> <p>We review and categorize several of the major logistical and operational problems encountered over the last decade in the global scale-up of HIV care and antiretroviral treatment for people with AIDS. While there are unique features of HIV care and treatment that pose significant challenges to effective modeling and service improvement, we identify several analogous OR-based solutions that have been developed in the service, industrial, and health sectors.</p> <p>Results</p> <p>HIV treatment scale-up includes many processes that are amenable to mathematical and simulation modeling, including forecasting future demand for services; locating and sizing facilities for maximal efficiency; and determining optimal staffing levels at clinical centers. Optimization of clinical and logistical processes through modeling may improve outcomes, but successful OR-based interventions will require contextualization of response strategies, including appreciation of both existing health care systems and limitations in local health workforces.</p> <p>Conclusion</p> <p>The modeling techniques developed in the engineering field of operations research have wide potential application to the variety of logistical problems encountered in HIV treatment scale-up in resource-limited settings. Increasing the number of cross-disciplinary collaborations between engineering and public health will help speed the appropriate development and application of these tools.</p

Efficient computation and long range optimization applications using a two-characteristic Markov-type manpower flow model

In [1] the author has compared and contrasted Markov and longitudinal manpower flow models. The Markov model requires relatively little data and has been widely analyzed (see [2] and [3]). The longitudinal model incorporates more realistic personnel flows, but requires extensive data which is not always available. In [4] Hayne and Marshall analyze a two-characteristic Markov model which can be viewed as a hybrid of the Markov and longitudinal models. The purpose of this paper is to show how efficient computational methods can be used with the two-characteristic model by exploiting the special structure of its underlying matrix. These methods make possible the efficient use of this basic flow model in optimization models similar to those described in Chapter 5 of [3]. (Author)NAhttp://archive.org/details/efficientcomputa52marsNAN