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On October 26, 2004 the Securities and Exchange Commission (the “SEC”) adopted new rules and rule amendments under the Investment Advisers Act of 1940 (the “Advisers Act”) that will require most hedge fund managers to register with the SEC as investment advisers by February 1, 2006. The actions taken by the SEC will necessitate that hedge fund managers begin preparing for SEC registration at least four to six months in advance of registration. In light of these new rules, this article summarizes: The significant provisions of the Advisers Act that hedge fund managers will need to become familiar with; The SEC registration process that a hedge fund adviser will have to follow; The SEC inspection program and some practical tips that hedge fund advisers should consider implementing. Because the regulatory framework imposes a variety of obligations and prohibitions on hedge fund managers, who, up until now, have operated without significant regulatory oversight, we recommend that fund managers who are likely to become subject to the registration rules should, well in advance of the February 1, 2006 registration deadline, familiarize themselves with the legal and operational changes that will affect them and assemble the information they will need to commence and complete the registration process. This article is designed to introduce fund managers to that framework.

Speaking about hedge funds, Stephen M. Cutler, Director of the United States Securities and Exchange Commission’s Division of Enforcement, stated that “firms that provide… prime brokerage services while recommending that fund to their customers may raise conflict issues as thorny as the hedging strategies these funds employ.” These conflicts have contributed to an increased level of regulatory scrutiny over hedge funds and their relationships with brokers. The purpose of this article is to discuss the regulatory background surrounding the relationship between hedge funds and their prime brokers and capital introduction programs sponsored by prime brokers.

This paper aims to consider a soft computing approach to pattern classification using the basic tools of fuzzy relational calculus (FRC) and genetic algorithm (GA).

The paper introduces a new interpretation of multidimensional fuzzy implication (MFI) to represent the author's knowledge about the training data set. It also considers the notion of a fuzzy pattern vector (FPV) to handle the fuzzy information granules of the quantized pattern space and to represent a population of training patterns in the quantized pattern space. The construction of the pattern classifier is essentially based on the estimate of a fuzzy relation Ri between the antecedent clause and consequent clause of each one‐dimensional fuzzy implication. For the estimation of Ri floating point representation of GA is used. Thus, a set of fuzzy relations is formed from the new interpretation of MFI. This set of fuzzy relations is termed as the core of the pattern classifier. Once the classifier is constructed the non‐fuzzy features of a test pattern can be classified.

The performance of the proposed scheme is tested on synthetic data. Subsequently, the paper uses the proposed scheme for the vowel classification problem of an Indian language. In all these case studies the recognition score of the proposed method is very good. Finally, a benchmark of performance is established by considering Multilayer Perceptron (MLP), Support Vector Machine (SVM) and the proposed method. The Abalone, Hosse colic and Pima Indians data sets, obtained from UCL database repository are used for the said benchmark study. The benchmark study also establishes the superiority of the proposed method.

This new soft computing approach to pattern classification is based on a new interpretation of MFI and a novel notion of FPV. A set of fuzzy relations which is the core of the pattern classifier, is estimated using floating point GA and very effective classification of patterns under vague and imprecise environment is performed. This new approach to pattern classification avoids the curse of high dimensionality of feature vector. It can provide multiple classifications under overlapped classes.

This paper aims to critique the rationalist theoretical framework of international mediation, which ignores emotions in analyzing the decision by conflict parties to pursue a negotiated settlement or continue fighting, and to present an alternative framework that integrates emotions.

The paper draws on psychology research on emotions and conflict to develop an emotionally informed framework for analyzing conflict parties’ decision-making regarding a settlement. It demonstrates the framework’s validity and value through a case study of the 2000 Camp David mediation to resolve the Israeli–Palestinian conflict.

A rationalist approach to mediation does not have adequate explanatory and predictive power theoretically. In practice, it can reduce the prospect of success.

The paper highlights the necessity for mediation researchers to study the effects of emotion, draw on psychology studies on conflict and explore the emotional implications of different mediation strategies and tactics.

The framework highlights the challenge of designing and conducting mediation in a way that cultivates emotions favorable to a settlement and lessens emotions unfavorable to a settlement.

This is the first study, to the best of the authors’ knowledge, to critique the rationalist framework of international mediation studies and develop an alternative framework that integrates emotions.

Alvin Hansen and John Williams’ Fiscal Policy Seminar at Harvard University is widely regarded as a key mechanism for the spread of Keynesianism in the United States. An original and regular participant, Richard A. Musgrave was invited to prepare remarks for the fiftieth anniversary of the seminar in 1988. These were never published, though a copy was filed with Musgrave’s papers at Princeton University. Their reproduction here is important for several reasons. First, it is one of the last reminiscences of the original participants. Second, the remarks make an important contribution to our understanding of the Harvard School of macro-fiscal policy. Third, the remarks provide interesting insights into Musgrave’s views on national economic policymaking as well as the intersection between theory and practice. The reminiscence demonstrates the importance of the seminar in shifting Musgrave’s research focus and moving him to a more pragmatic approach to public finance.

The study aims to analyze the changes in banking market structure and their impact on the bank efficiency.

This study uses a one-stage stochastic frontier analysis (SFA) to compare the impact of the market structure and the GFC on the economic efficiency of the major banks in both countries.

A significant negative impact of the GFC is observed on bank efficiency. Overall, Canadian banks posted better efficiency scores than their American counterparts. Additionally, cost-efficient banks are found to be more resilient to crises and more profit-efficient in the post-GFC period. The authors found that market power had a positive impact on the cost and profit efficiency of banks. Higher levels of equity, market power and concentration helped banks be more cost-efficient.

Only large banks are selected for study although it represents the majority stake of both banking sectors.

Banking regulators should include more measures to assess the banking market structure and performance.

As per the best knowledge of the authors, it is the first study to assess the change in banking market structure and efficiency of the US and Canadian banking sectors in the post-GFC period.

In this study, we test the so-called “Quiet Life Hypothesis” (QLH), which postulates that banks with market power are less efficient.

We employ instrumental variable Ordinary Least Squares, Fixed Effects, Tobit and Logistic regressions. The empirical evidence is based on a panel of 162 banks consisting of 42 African countries for the period 2001–2011. There is a two-step analytical procedure. First, we estimate Lerner indices and cost efficiency scores. Then, we regress cost efficiency scores on Lerner indices contingent on bank characteristics, market features and the unobserved heterogeneity.

The empirical evidence does not support the QLH because market power is positively associated with cost efficiency.

Owing to data availability constraints, this is one of the few studies to test the QLH in African banking.