A Study of Panel Logit Model and Adaptive Neuro-Fuzzy Inference System in the Prediction of Financial Distress Periods

The purpose of this paper is to present two different approaches of financial distress pre-warning models appropriate for risk supervisors, investors and policy makers. We examine a sample of the financial institutions and electronic companies of Taiwan Security Exchange (TSE) market from 2002 through 2008. We present a binary logistic regression with paned data analysis. With the pooled binary logistic regression we build a model including more variables in the regression than with random effects, while the in-sample and out-sample forecasting performance is higher in random effects estimation than in pooled regression. On the other hand we estimate an Adaptive Neuro-Fuzzy Inference System (ANFIS) with Gaussian and Generalized Bell (Gbell) functions and we find that ANFIS outperforms significant Logit regressions in both in-sample and out-of-sample periods, indicating that ANFIS is a more appropriate tool for financial risk managers and for the economic policy makers in central banks and national statistical services

Analysis of binary trading patterns in Xetra

This paper proposes the Shannon entropy as an appropriate one-dimensional measure of behavioural trading patterns in financial markets. The concept is applied to the illustrative example of algorithmic vs. non-algorithmic trading and empirical data from Deutsche Börse's electronic cash equity trading system, Xetra. The results reveal pronounced differences between algorithmic and non-algorithmic traders. In particular, trading patterns of algorithmic traders exhibit a medium degree of regularity while non-algorithmic trading tends towards either very regular or very irregular trading patterns. JEL Classification: C40, D0, G14, G15, G2

Health insurance in Zaire

This study of health insurance systems in Zaire was carried out as part of a larger program of initiatives designed to improve the sustainability of health care systems and increase the health status of the Zairian population. This paper presents the objectives of the study and a discussion of the economic aspects of health insurance, background information about the health sector and health financing systems in Zaire and highlights of previous related work. The major motivations for this study were: (a) to provide information for the ongoing social sector adjustment dialogue in Zaire; and (b) to serve as a case study in the World Bank's Region Study of Health Finance. Specifically, the study sought to document different types of insurance systems in Zaire, and to conduct in-depth case studies of several schemes. The in-depth case studies presented in this report evaluate the design, management operational efficiency of four health insurance programs from both rural and urban areas. The case studies also attempt to analyze the effects of insurance on equity of access, utilization of health care services, and mobilization of financial resources for the health sector. From these analyses, the report draws conclusions about the advantages and disadvantages of health insurance programs as a means of financing health care services in Zaire, and suggests avenues for future research, policy, and programming initiatives.Health Monitoring&Evaluation,Insurance Law,Health Economics&Finance,Insurance&Risk Mitigation,Health Systems Development&Reform

GeD spline estimation of multivariate Archimedean copulas

A new multivariate Archimedean copula estimation method is proposed in a non-parametric setting. The method uses the so called Geometrically Designed splines (GeD splines), recently introduced by Kaishev et al. (2006 a,b) [10] and [11], to represent the cdf of a random variable Wµ, obtained through the probability integral transform of an Archimedean copula with parameter µ. Sufficient conditions for the GeD spline estimator to posses the properties of the underlying theoretical cdf, K(µ; t), of Wµ, are given. The latter conditions allow for defining a three-step estimation procedure for solving the resulting non-linear regression problem with linear inequality constraints. In the proposed procedure,finding the number and location of the knots and the coefficients of the unconstrained GeD spline estimator and solving the constraint least-squares optimisation problem, are separated. Thus, the resulting spline estimator ^K (^µ; t) is used to recover the generator and the related Archimedean copula by solving an ordinary differential equation. The proposed method is truly multivariate, it brings about numerical efficiency and as a result can be applied with large volumes of data and for dimensions d ¸ 2, as illustrated by the numerical examples presented

A neural network model to forecast and describe bond ratings

Neural Network;Bond Ratings;accountancy

Societal assessment overview

The decision to proceed with SPS depends on a political determination that commitment of the economic, institutional, and social energies required for its implementation is a worthwhile investment. This determination is national (and international) in scope and is based on knowledge of the environmental and societal impacts of the SPS, its projected economics and technological risks, expressed through the influence of contending segments of society. To assist the decision makers, an assessment of societal issues associated with the SPS was undertaken as part of the Concept Development and Evaluation Program. Results of the assessment are reported. The primary societal assessment objectives are to determine if the societal ramifications of an SPS might significantly impede its development, and to establish an information base regarding these issues. Estimates regarding SPS impacts commensurate with its stage of development and the needs of the decision makers are provided

Climate change adaptation in industry and business

This report delivers a best practice framework to integrate financial risk assessment, governance and disclosure with existing governance principles around climate change adaptation.AbstractThe Australian business community has long been aware of the risks and opportunities associated with greenhouse gas mitigation and climate change policies. Some businesses have taken initial steps to adapt to the expected effects of climate change; however, most enterprises are only vaguely aware of the breadth of adaptation that may be required. Associated with strategic adaptation are the principles of financial/operational risk management and governance, as well as financial impact disclosure to investors and regulators. We develop a consolidated framework in which boards and executive managers can develop a robust approach to climate change adaptation governance, climate change risk assessment and financial disclosure. The project outlines a matrix of disclosures required for investors to enable them to evaluate corporate exposure to climate change risk.The project initially comprised a set of workshops with members of the Australian business community, industry representatives, regulatory authorities and academics with expertise in business risk and disclosure effects. Each workshop focused on a separate theme that built upon the work of previous workshops. A set of follow-up discussions was held with some of the key members who contributed to the project, including the Australian Stock Exchange (ASX) Investor Group on Climate Change (IGCC), the Australian Accounting Standards Board (AASB) and the Australian Institute of Company Directors. This discussion permitted each body to comment on the final report, advise on the mechanics of the costing, reporting and disclosure approaches of climate change adaptation, and lend their expertise to the formulation of an appropriate framework.The scope of the research is constrained to firm behaviour and the requirements for investor disclosure and governance of adaptation activities. The project therefore focuses on financial analyses – including real options – undertaken by firms with regard to investing in climate change adaptation activities and projects. While the economic costs and benefits are important to organisational adaptation activities, they represent a secondary level of analysis that may need to be carried out on either an independent or cumulative scale by governments or other bodies to measure the wider effects.As the degree of sophistication in climate change adaptation activities, modelling and cost estimation increases, along with the anticipated growth in interest of both company boards and managers, it is expected that accounting standards, ASX listing rules and disclosures required under the Corporations Act would need to explicitly reflect these corporate actions. The asset allocation of banks, mutual funds, superannuation funds and other investments is also likely to adapt as companies quantify their exposure to climate change. The makeup of assets in investment portfolios may therefore markedly shift, and thus indirectly adjust to the climate change adaptation activities of companies in the broader market