Statistical inference and efficient portfolio investment performance

Two main methods have been used in mutual funds evaluation. One is portfolio evaluation, and the other is data envelopment analysis (DEA). The history of portfolio evaluation dates from the 1960s with emphasis on both expected return and risk. However, there are many criticisms of traditional portfolio analysis which focus on their sensitivity to chosen benchmarks. Imperfections in portfolio analysis models have led to the exploration of other methodologies to evaluate fund performance, in particular data envelopment analysis (DEA). DEA is a non-parametric methodology for measuring relative performance based on mathematical programming. Based on the unique characteristics of investment trusts, Morey and Morey (1999) developed a mutual funds efficiency measure in a traditional mean-variance model. It was based on Markowitz portfolio theory and related the non-parametric methodologies to the foundations of traditional performance measurement in mean-variance space. The first application in this thesis is to apply the non-linear programming calculation of the efficient frontier in mean variance space outlined in Morey and Morey (1999) to a new modern data set comprising a multi-year sample of investment funds. One limitation of DEA is the absence of sampling error from the methodology. Therefore the second innovation in this thesis extends Morey and Morey (1999) model by the application of bootstrapped probability density functions in order to develop confidence intervals for the relative performance indicators. This has not previously been achieved for the DEA frontier in mean variance space so that the DEA efficiency scores obtained through Morey and Morey (1999) model have not hitherto been tested for statistical significance. The third application in this thesis is to examine the efficiency of investment trusts in order to analyze the factors contributing to investment trusts’ performance and detect the determinants of inefficiency. Robust-OLS regression, Tobit models and Papke-Wooldridge (PW) models are conducted and compared to evaluate contextual variables affecting the performance of investment funds. From the thesis, new and original Matlab codes designed for Morey and Morey (1999) models are presented. With the Matlab codes, not only the results are obtained, but also how this quadratic model is programming could be very clearly seen, with all the details revealed

Regional Efficiency Improvement by Means of Data Envelopment Analysis through Euclidean Distance Minimization including Fixed Input Factors - An Application to Tourist Regions in Italy

Standard Data Envelopment Analysis (DEA) is characterized by uniform proportional input reduction or output augmentation in calculating improvement projections. This paper develops a new Euclidean Distance Minimization model in the context of DEA in order to derive a more appropriate efficiency-improving projection model by means of a weighted projection function. The model is extended to the situation where some factor inputs are fixed, for instance, due to lumpiness or natural constraints. The extended DEA model is illustrated in the context of regional planning by using a data set on Italian tourist destination regions. © 2010 the author(s). Journal compilation © 2010 RSAI

Efficiency of the Welfare State: A Comparative Approach Using Data Envelopment Analysis

As governments continue to evolve over the past century or so in their perceived role of providing economic security for their populations, a ubiquitous yet ill-defined concept of the welfare state is increasingly taking center stage in political and economic debates. With fiscal crises looming over the horizon in many parts of the world, the fingers of blame point with greater frequency to the welfare state as the entity which is contributing more to fiscal problems than to economic solutions. Reformation of the welfare state is rapidly becoming more likely and more urgent and this study proposes one mechanism for evaluating welfare state performance and setting benchmarks for optimizing such performance. The study uses Data Envelopment Analysis to evaluate comparative efficiencies of various welfare state models in 137 countries, and to propose potential pathways to efficiency savings in the laggard efficiency states. The study contextualizes the welfare state efficiency differences by referring to the well-established welfare state typologies of 18 Organisation for Economic Co-operation and Development (OECD) countries. The results are consistent with previous findings in identifying the lower spending states as generally more efficient and finding the social-democratic welfare state model less efficient. The results are qualified by the recognition that definitional and data availability issues remain to be solved by future studies, as many of the ideal variables for welfare state performance measurement do not exist at this time

Value Efficiency Analysis for Incorporating Preference Information in Data Envelopment Analysis

We develop a procedure and the requisite theory for incorporating preference information in a novel way in the efficiency analysis of Decision Making Units. The efficiency of Decision Making Units is defined in the spirit of Data Envelopment Analysis (DEA), complemented with Decision Maker's preference information concerning the desirable structure of inputs and outputs. Our procedure begins by aiding the Decision Maker in searching for the most preferred combination of inputs and outputs of Decision Making Units (for short, Most Preferred Solution) which are efficient in DEA. Then, assuming that the Decision Maker's Most Preferred Solution maximizes his/her underlying (unknown) value function at the moment when the search is terminated, we approximate the indifference contour of the value function at this point with its possible tangent hyperplanes. Value Efficiency scores are then calculated for each Decision Making Unit comparing the inefficient units to units having the same value as the Most Preferred Solution. The resulting Value Efficiency scores are optimistic approximations of the true scores. The procedure and the resulting efficiency scores are immediately applicable to solving practical problems

Identification of linkage between strategic group and performance of Indian commercial banks : a combined approach using DEA and Co-Plot

This paper explores the linkage between strategic grouping and performance of the Indian banking sector. Strategic grouping and performance were identified using published financial information for all public sector banks. Grouping of Indian public sector banks following comparable financial strategy – with similar asset quality, operational efficiency and profitability – was operationalized using the graphical display method of Co-plot. From their position in the two dimensional conceptual map, banks with identical financial performance formed strategic groups with significant positive linkage between better groups and their superior financial performance, which showed their inherent homogeneity in business policy decisions. Relative performance of the banks in terms of their efficiency in converting the resources to financial outputs was obtained using data envelopment analysis technique. The measures for potential financial improvements were obtained from the output slacks calculated. Efficient banks were found to be more profitable and their grouping as observed in the efficiency-profitability matrix was found to be identical to the strategic groups obtained using financial ratios. This paper offers a framework to commercial banks to make informed policy decisions about their competitive positioning in the target market, develop long-term strategic focus and identify a benchmark for improving their performance.Este artículo explora el vínculo entre el agrupamiento estratégico y el rendimiento del sector bancario indio. El agrupamiento estratégico y el rendimiento fueron identificados mediante el uso de información financiera publicada perteneciente a todos los bancos de los sectores públicos. El agrupamiento de los bancos del sector público indio siguió una estrategia financiera comparable (con una calidad de activos similar, eficiencia operativa y rentabilidad) se puso en funcionamiento utilizando el método de visualización gráfica de Co-plot. Desde su posición en el mapa conceptual bidimensional, los bancos con rendimiento financiero idéntico formaron grupos estratégicos con una relación significativamente positiva entre los mejores grupos y su rendimiento financiero superior, que mostraron su homogeneidad inherente en las decisiones de política de negocios. El rendimiento relativo de los bancos en términos de su eficiencia en la conversión de los recursos a productos financieros se obtuvo utilizando la técnica de análisis envolvente de datos. Las medidas para las potenciales mejoras financieras se obtuvieron del cálculo de producciones no utilizadas. Los bancos eficientes en este aspecto resultaron ser más rentables, y en su agrupamiento se observó cómo la matriz eficiencia-rentabilidad era idéntica a la de los grupos estratégicos obtenidos utilizando ratios financieros. Este artículo ofrece un contexto de trabajo para que los bancos comerciales realicen decisiones informadas sobre su posicionamiento competitivo en el mercado objetivo, desarrollando técnicas de concentración a largo plazo e identificando un punto de referencia para mejorar su rendimiento

Integrating multiple criteria decision analysis and production theory for performance evaluation: framework and review

Accounting, life cycle assessment (LCA) and data envelopment analysis (DEA) are examples of various research areas that independently develop and apply diverse methodologies to evaluate performance. Though, many methods have in common that the results to be assessed are mainly determined by the inputs and outputs of the activities which are to be evaluated. Based on both production and decision theory, our comprehensive framework integrates and systematically distinguishes specific types of production-based performance assessment. It allows to examine and categorise the existing literature on such approaches. Our review focuses on sources which explicitly apply concepts or methods of multiple criteria decision analysis (MCDA). We did not find any elaborated methodology that fully integrates MCDA with production theory. At least, a basic approach to multicriteria performance analysis, which generalises the methodology of data envelopment analysis, appears to be well-grounded on production theory. It was already presented in this journal in 2001 and has rarely been noticed in the literature until now. A short overview outlines its recent insights and main findings. A key finding is that a category mistake prevails among well-known methodologies of efficiency measurement like DEA. It may imply invalid empirical results because the inputs and outputs of production processes are confused with resulting impacts destroying or creating values (to be minimised or maximised, respectively). We conclude by defining open problems and by indicating prospective research directions