Data envelopment analysis in financial services: a citations network analysis of banks, insurance companies and money market funds

Development and application of the data envelopment analysis (DEA) method, have been the subject of numerous reviews. In this paper, we consider the papers that apply DEA methods specifically to financial services, or which use financial services data to experiment with a newly introduced DEA model. We examine 620 papers published in journals indexed in the Web of Science database, from 1985 to April 2016. We analyse the sample applying citations network analysis. This paper investigates the DEA method and its applications in financial services. We analyse the diffusion of DEA in three sub-samples: (1) banking groups, (2) money market funds, and (3) insurance groups by identifying the main paths, that is, the main flows of the ideas underlying each area of research. This allows us to highlight the main approaches, models and efficiency types used in each research areas. No unique methodological preference emerges within these areas. Innovations in the DEA methodologies (network models, slacks based models, directional distance models and Nash bargaining game) clearly dominate recent research. For each subsample, we describe the geographical distribution of these studies, and provide some basic statistics related to the most active journals and scholars

An Applied Credit Scoring Model and Christian Mutual Funds Performance

This dissertation comprises two different financial essays. Essay 1, “An Applied Credit Score Model,” uses data from local credit union to predict the probability of default. Due to recent financial crisis regulation has been enacted that makes it essential to develop a probability of default model that will mitigate charge-off losses. Using discriminant analysis and logistic regression this paper will attempt to see how well credit score can predict probability of default. While credit score does an adequate job at classifying loans, misclassification of loans can be costly. Thus while credit score is a predictor, there is danger in relying solely on its information. Thus other variables are needed in order to more accurately be able to find the probability of default. Essay 2, “Christian Mutual Fund Performance,” draws attention to a much ignored type of funds, Christian mutual funds. The following questions are asked: How does Christian mutual fund perform compared to the market? Is there a difference in performance during recessions as indicated by literature? Is Christian mutual fund performance different than SRI funds? How do Catholic and Protestant fund perform? Looking at qualitative evidence, Christian mutual funds place much more importance on moral issue than SRI funds. Thus there is a clear difference in objectives and the type of screening that these two mutual fund pursue. Overall data reflects that screened data perform worse than the market, however during recession screened funds perform as well and at times better than the market. Christian mutual funds tends to perform worse than SRI funds

An Applied Credit Scoring Model and Christian Mutual Funds Performance

This dissertation comprises two different financial essays. Essay 1, “An Applied Credit Score Model,” uses data from local credit union to predict the probability of default. Due to recent financial crisis regulation has been enacted that makes it essential to develop a probability of default model that will mitigate charge-off losses. Using discriminant analysis and logistic regression this paper will attempt to see how well credit score can predict probability of default. While credit score does an adequate job at classifying loans, misclassification of loans can be costly. Thus while credit score is a predictor, there is danger in relying solely on its information. Thus other variables are needed in order to more accurately be able to find the probability of default. Essay 2, “Christian Mutual Fund Performance,” draws attention to a much ignored type of funds, Christian mutual funds. The following questions are asked: How does Christian mutual fund perform compared to the market? Is there a difference in performance during recessions as indicated by literature? Is Christian mutual fund performance different than SRI funds? How do Catholic and Protestant fund perform? Looking at qualitative evidence, Christian mutual funds place much more importance on moral issue than SRI funds. Thus there is a clear difference in objectives and the type of screening that these two mutual fund pursue. Overall data reflects that screened data perform worse than the market, however during recession screened funds perform as well and at times better than the market. Christian mutual funds tends to perform worse than SRI funds

Financial crises and bank failures: a review of prediction methods

In this article we provide a summary of empirical results obtained in several economics and operations research papers that attempt to explain, predict, or suggest remedies for financial crises or banking defaults, as well as outlines of the methodologies used. We analyze financial and economic circumstances associated with the US subprime mortgage crisis and the global financial turmoil that has led to severe crises in many countries. The intent of the article is to promote future empirical research that might help to prevent bank failures and financial crises.financial crises; banking failures; operations research; early warning methods; leading indicators; subprime markets

Data envelopment analysis and data mining to efficiency estimation and evaluation

Purpose: This paper aims to assess the application of seven statistical and data mining techniques to second-stage data envelopment analysis (DEA) for bank performance. Design/methodology/approach: Different statistical and data mining techniques are used to second-stage DEA for bank performance as a part of an attempt to produce a powerful model for bank performance with effective predictive ability. The projected data mining tools are classification and regression trees (CART), conditional inference trees (CIT), random forest based on CART and CIT, bagging, artificial neural networks and their statistical counterpart, logistic regression. Findings: The results showed that random forests and bagging outperform other methods in terms of predictive power. Originality/value: This is the first study to assess the impact of environmental factors on banking performance in Middle East and North Africa countries.Scopu

Efficiency of mutual fund managers: a slacks-based manager efficiency index

This paper develops an innovative slacks-based manager efficiency index (SMEI) to evaluate the efficiency of mutual fund managers. First, the SMEI contributes to decisions by evaluating the efficiency of the manager as a whole instead of focusing on individual mutual funds. Second, the SMEI includes socio-demographic variables to extend the mere consideration of financial variables in the model. Third, the SMEI identifies locally efficient but globally inefficient managers. This local SMEI evaluates managers in reference to the ‘best practice’ competitors with similar management characteristics. Finally, this paper includes a real application of the SMEI in a sample of individual managers in the Spanish mutual fund industry. This empirical illustration further examines the persistence of the efficiency scores and the influence of the SMEI variables on the efficiency of individual managers

Reconstructing nonparametric productivity networks

Network models provide a general representation of inter-connected system dynamics. This ability to connect systems has led to a proliferation of network models for economic productivity analysis, primarily estimated non-parametrically using Data Envelopment Analysis (DEA). While network DEA models can be used to measure system performance, they lack a statistical framework for inference, due in part to the complex structure of network processes. We fill this gap by developing a general framework to infer the network structure in a Bayesian sense, in order to better understand the underlying relationships driving system performance. Our approach draws on recent advances in information science, machine learning and statistical inference from the physics of complex systems to estimate unobserved network linkages. To illustrate, we apply our framework to analyze the production of knowledge, via own and cross-disciplinary research, for a world-country panel of bibliometric data. We find significant interactions between related disciplinary research output, both in terms of quantity and quality. In the context of research productivity, our results on cross-disciplinary linkages could be used to better target research funding across disciplines and institutions. More generally, our framework for inferring the underlying network production technology could be applied to both public and private settings which entail spillovers, including intra-and inter-firm managerial decisions and public agency coordination. This framework also provides a systematic approach to model selection when the underlying network structure is unknown

Método análisis envolvente de datos y redes neuronales en la evaluación y predicción de la eficiencia técnica de pequeñas empresas exportadoras

In this research, a method was developed to evaluate and predict the efficiency of small exporting companies taking as input or asset variables the total assets, equity, total liabilities, operating expenses, sales costs and as output or result variables. net sales, net income and operating income. For this, the envelopment data analysis was used in the evaluation of the efficiency, the discriminant analysis in the evaluation of the classification of efficient and inefficient companies and the artificial neural networks to evaluate its capacity of classification prediction in 90 companies of the sector of the city of Barranquilla-Colombia. The results allowed to classify the companies according to level of efficiency showing an average technical efficiency of 41.38% of the sector with 11 representative companies of efficiency. The results show the relevance of the proposed methodology to correctly classify and forecast technical efficiency in small exporting companies. © Centro de Informacion Tecnologica. All rights reserved

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