Komlan Sedzro

Hedge fund performance appraisal using data envelopment analysis

In this paper we apply data envelopment analysis (DEA) to evaluate the performance of hedge fund classifications. The purpose of alternative investment strategies such as hedge funds is to offer absolute returns, so using passive benchmarks to measure their performance could be ineffective. With the increasing number of hedge funds available, institutional investors, pension funds, and high net worth individuals urgently need a trustworthy efficiency appraisal method. DEA can achieve this. An important benefit of the DEA measure is that benchmarks are not required, thereby alleviating the problem of using traditional benchmarks to examine non-normal distribution of hedge fund returns. We suggest that DEA be used as a complimentary technique (or method) for the selection of efficient hedge funds and funds of hedge funds for investors. Using DEA can shed light and further validate hedge fund manager selection with other methodologies.

On the Market Timing of Hedge Fund Managers

In this article, the authors evaluate whether directional hedge fund managers benefit from market timing in investment strategies. Analysis of a sample of current and defunct onshore and offshore funds does not reveal any significant market-timing alpha. Most hedge fund managers exhibit good security selection skill, which tends to be negatively correlated with market-timing ability, but not correlated with asset size or age of the fund. Tests of single- and multi-index models are consistent with published findings in the mutual fund literature that the hedge fund returns exhibit low correlation with market index returns.

Assessing The Relative Efficiency Of Credit Unionbranches Using Data Envelopment Analysis

Abstract Dala envelopment analysis (DEA) is a linear programming-based technique developed to evaluate the relative efficiency of non-profit and public sector decision-making units that use multiple inputs to produce multiple outputs. Technically, as pointed out by Joro, Korhonen and Wallemius( 1998), DEA and Multiple Objective Linear Programming (MOLP) aim at suggesting improvements for inefficient units based on the identification of efficient units in a certain space. In this study, DEA is used as a managerial audit tool to identify and measure inefficiencies among a set of 73 independent decision-making units within one federation of the “Caisses Populaires Desjardins” in Québec. The DEA results were compared with the federation’s traditional accounting ratio measures. Management found that the DEA results confirmed most of their intuition on which units were unprofitable, and also pinpointed units that made a profit but were operationally inefficient. Overall, they agree with our results and on the benefits of using DEA to complement their accounting ratio analysis for improving the efficiency of some of their “caisses”.

Nonstationarity Tests of Managed Futures

This article examines whether the net asset values (NAVs) of managed futures follow random walks. Monthly data from January 1990 to December 2000 are tested for nonstationarity and random walk with drift, using the Augmented Dickey-Fuller test. All of the managed futures classifications are nonstationary, but on the other hand, none are found to behave as random walks. Even when random walk behavior is allowed, evidence of positive drift parameters ensures that the NAVs contain discernable trends. The authors conclude that historical NAVs can be used to create reliable predictive models of managed futures.

THE IMPACT OF THE ORGANIZATIONAL STRUCTURE ON THE PERFORMANCE OF MICROFINANCE INSTITUTIONS USING DATA ENVELOPMENT ANALYSIS

We apply data envelopment analysis to compare the relative efficiency of different forms of microfinance institutions (MFIs): banks, cooperatives, nongovernmental organizations (NGOs), and nonbank financial institutions. We find that MFIs that operate as NGOs are technically more efficient than bank MFIs. Using the same inputs (labor and physical and financial assets), NGOs serve more clients (number of borrowers or depositors) than bank MFIs.