Application of support vector machines on the basis of the first Hungarian bankruptcy model

In our study we rely on a data mining procedure known as support vector machine (SVM) on the database of the first Hungarian bankruptcy model. The models constructed are then contrasted with the results of earlier bankruptcy models with the use of classification accuracy and the area under the ROC curve. In using the SVM technique, in addition to conventional kernel functions, we also examine the possibilities of applying the ANOVA kernel function and take a detailed look at data preparation tasks recommended in using the SVM method (handling of outliers). The results of the models assembled suggest that a significant improvement of classification accuracy can be achieved on the database of the first Hungarian bankruptcy model when using the SVM method as opposed to neural networks

The Strategic Exploitation of Limited Information and Opportunity in Networked Markets

This paper studies the effect of constraining interactions within a market. A model is analysed in which boundedly rational agents trade with and gather information from their neighbours within a trade network. It is demonstrated that a trader’s ability to profit and to identify the equilibrium price is positively correlated with its degree of connectivity within the market. Where traders differ in their number of potential trading partners, well-connected traders are found to benefit from aggressive trading behaviour.Where information propagation is constrained by the topology of the trade network, connectedness affects the nature of the strategies employed

Older people presenting to the emergency department after a fall: a population with substantial recurrent healthcare use

ABSTRACT Objectives To document patient characteristics, care pathways, healthcare use and costs of fall-related emergency department (ED) presentations by older adults. Participants and methods All fallers aged $70 years, presenting to the ED of a 450-bed metropolitan university hospital in Sydney, Australia (1 April 2007 through 31 March 2009) were studied. Data were collected from the ED electronic information system, ED clinical records and the hospital electronic information system database. Population estimates for 2008 for the local areas served by the hospital were used to estimate ED presentation rates. Results Of 18 902 all-cause ED presentations, 3220 (17.0%) were due to a fall. Among fallers, 35.4% had one or more ED presentations and 20.3% had had one or more hospital admissions in the preceding 12 months. Fall-related ED presentation led directly to hospital admission in 42.7% of the cases, the majority of which (78.0%) received acute care only (length of stayd14.4 days for men and 13.7 days for women) and the remaining cases underwent further inpatient rehabilitation (length of stay 35.6 days for men and 3

Applications of Genetic Programming to Finance and Economics: Past, Present, Future

While the origins of Genetic Programming (GP) stretch back over fifty years, the field of GP was invigorated by John Koza’s popularisation of the methodology in the 1990s. A particular feature of the GP literature since then has been a strong interest in the application of GP to real-world problem domains. One application domain which has attracted significant attention is that of finance and economics, with several hundred papers from this subfield being listed in the Genetic Programming Bibliography. In this article we outline why finance and economics has been a popular application area for GP and briefly indicate the wide span of this work. However, despite this research effort there is relatively scant evidence of the usage of GP by the mainstream finance community in academia or industry. We speculate why this may be the case, describe what is needed to make this research more relevant from a finance perspective, and suggest some future directions for the application of GP in finance and economics

On the Evolution of Investment Strategies and the Kelly Rule – A Darwinian Approach

This paper complements theoretical studies on the Kelly rule in evolutionary finance by studying a Darwinian model of selection and reproduction in which the diversity of investment strategies is maintained through genetic programming. We find that investment strategies which optimize long-term performance can emerge in markets populated by unsophisticated investors. Regardless whether the market is complete or incomplete and whether states are i.i.d. or Markov, the Kelly rule is obtained as the asymptotic outcome. With price-dependent rather than just state-dependent investment strategies, the market portfolio plays an important role as a protection against severe losses in volatile markets