Efficiency in microfinance: financial and social performance of agricultural credit cooperatives in Bulgaria

Efficiency in microfinance requires accounting for a specific ambiguous production goal. Beyond financial performance, microfinance institutions are to be assessed with regard to their social impact. Based on a comprehensive data collection campaign on 15 Bulgarian agricultural credit cooperatives (ACCs), we compiled a database uniting financial (perennial data from 2000 to 2009) and social performance indicators (2009). The social performance assessment follows an internationally renowned methodology of social auditing. It provides the database for the construction of a social output, which, apart from outreach, evaluates social network quality, client benefits (protection from over-indebtedness) and other items that have not been assessed in efficiency analysis before. We develop a new analytical model for Data Envelopment Analysis and gain meaningful results for the sample of ACCs. Interestingly, the efficiency rankings revealed that only ACCs with sound financial performance can achieve a higher ranking in the specification including the social output.     

Financial sustainability and poverty outreach within a network of village banks in Cameroon: A multi-DEA approach

Microfinance institutions face a double bottom-line. They perform financial tasks by giving microcredits to their customers and support projects aiming at reducing poverty. In doing so, they have to be financially self-sufficient and to target poor people excluded from the traditional financial systems. However, a trade-off may exist between financial sustainability and poverty outreach for these institutions. By using a multi-DEA approach, this paper shows that even if a trade-off exists for 15% of the MC² (Mutuelles Communautaires de Croissance) in Cameroon, there is no trade-off for 46% of them. In order to increase, without trade-off, financial and social performance of inefficient MC², a benchmarking approach combing DEA and performance indicators has been developed. DEA is used for identifying best-practices and setting benchmarking goals. Performance indicators are used for characterizing areas needing improvements and following the evolution of MC² toward their goals, i.e., for implementing benchmarking. Complementarity of both approaches provides a tool box for improving financial and social efficiency and reducing the trade-off between financial sustainability and poverty outreach of microfinance institutions.     

Applicability and effectiveness of classifications models for achieving the twin objectives of growth and outreach of microfinance institutions

Measuring performance of microfinance institutions (MFIs) is challenging as MFIs must achieve the twin objectives of outreach and sustainability. We propose a new measure to capture the performance of MFIs by placing their twin achievements in a 2 × 2 grid of a classification matrix. To make a dichotomous classification, MFIs that meet both their twin objectives are classified as ‘1’ and MFIs who could not meet their dual objectives simultaneously are designated as ‘0’. Six classifiers are applied to analyze the operating and financial characteristics of MFIs that can offer a predictive modeling solution in achieving their objectives and the results of the classifiers are comprehended using technique for order preference by similarity to ideal solution to identify an appropriate classifier based on ranking of measures of performance. Out of six classifiers applied in the study, kernel lab-support vector machines achieved highest accuracy and lowest classification error rate that discriminates the best achievement of the MFIs’ twin objective. MFIs can use both these steps to identify whether they are on the right path to attaining their multiple objectives from their operating characteristics.     

The efficiency effects of a single market for financial services in Europe

This paper examines the potential efficiency effects of a single market for financial services in Europe. The topics covered include universal banking, the merger and acquisition process itself, cross-border ownership and management of financial institutions, and the effects of consolidation of financial institutions on the supply of relationship lending services to informationally opaque small businesses. The research reviewed here suggests that the creation of a single market for the European financial services industry is not likely to bring about strong efficiency gains and that cross-border efficiency barriers may prevent the single market from becoming a reality.     

A tale of two sets of norms: Comparing opportunities for student agency in mathematics lessons with and without interactive simulations

Previous research has documented the importance of setting up productive norms in mathematics classrooms. Studies have also shown the potential for activities involving interactive simulations (sims) to support student engagement and learning. In this study, we investigated the relationship between norms and sim-based activities. In particular, we examined the social and sociomathematical norms in lessons taught with and without the use of PhET sims in the same teacher’s middle-school mathematics classroom. There were statistically significant differences in indicators of social norms between the two types of lessons. In sim lessons, the teacher more frequently took the role of a facilitator of mathematical ideas, and students exhibited conceptual agency more often than they did in non-sim lessons. On the other hand, there was substantial overlap: the teacher usually acted as an evaluator, and the students usually exhibited disciplinary agency in both types of lessons. However, there was a stark contrast in sociomathematical norms between the two types of lessons. Students’ specifically mathematical obligations in non-sim lessons consistently included practicing procedures in isolation and appealing to rules. Obligations in sim lessons included developing and sharing strategies, making conjectures and providing justifications. In both types of lessons, students were obligated to recall mathematical facts and vocabulary. Thus, the social norms were broadly consistent except for important differences in frequency, whereas we found substantial qualitative contrasts in the sociomathematical norms in the two types of lessons. This case provides evidence that contrasting norms can exist within the same classroom. We argue from our data that these differences may be mediated by curricular choices—in this case, the use of sims.     

Development and calibration of a currency trading strategy using global optimization

We have developed a new financial indicator—called the Interest Rate Differentials Adjusted for Volatility (IRDAV) measure—to assist investors in currency markets. On a monthly basis, we rank currency pairs according to this measure and then select a basket of pairs with the highest IRDAV values. Under positive market conditions, an IRDAV based investment strategy (buying a currency with high interest rate and simultaneously selling a currency with low interest rate, after adjusting for volatility of the currency pairs in question) can generate significant returns. However, when the markets turn for the worse and crisis situations evolve, investors exit such money-making strategies suddenly, and—as a result—significant losses can occur. In an effort to minimize these potential losses, we also propose an aggregated Risk Metric that estimates the total risk by looking at various financial indicators across different markets. These risk indicators are used to get timely signals of evolving crises and to flip the strategy from long to short in a timely fashion, to prevent losses and make further gains even during crisis periods. Since our proprietary model is implemented in Excel as a highly nonlinear “black box” computational procedure, we use suitable global optimization methodology and software—the Lipschitz Global Optimizer solver suite linked to Excel—to maximize the performance of the currency basket, based on our selection of key decision variables. After the introduction of the new currency trading model and its implementation, we present numerical results based on actual market data. Our results clearly show the advantages of using global optimization based parameter settings, compared to the typically used “expert estimates” of the key model parameters.     

Linking customer satisfaction, employee appraisal, and business performance: an evaluation methodology in the banking sector

The linkage among customer satisfaction, employee evaluation, and business performance data is very important in modern business organizations. Several previous research efforts have studied this linkage, focusing mainly on the financial or business performance in order to analyze the efficiency of an organization. However, recent studies have tried to consider other important performance indicators, which are able to affect business operations and future growth (e.g., external and internal customer satisfaction). In the case of the banking industry, studying the relations among the aforementioned variables is able to give insight in the performance evaluation of bank branches and the viability analysis of the banking organization. This paper presents a real-world study for measuring the relative efficiency of a set of bank branches using a Data Envelopment Analysis (DEA) approach. In particular, a multistage DEA network model is proposed, using a set of performance indicators that combine customer satisfaction, employee evaluation, and business performance indices. The main aim of the presented study is to evaluate the relative efficiency of each customer service delivery step, in the environment of a bank branch. The results are also able to estimate the contribution of the assessed performance indicators to the branch’s overall efficiency, and to determine potential improvement actions.     

Chinese companies distress prediction: an application of data envelopment analysis

Bankruptcy prediction is a key part in corporate credit risk management. Traditional bankruptcy prediction models employ financial ratios or market prices to predict bankruptcy or financial distress prior to its occurrence. We investigate the predictive accuracy of corporate efficiency measures along with standard financial ratios in predicting corporate distress in Chinese companies. Data Envelopment Analysis (DEA) is used to measure corporate efficiency. In contrast to previous applications of DEA in credit risk modelling where it was used to generate a single efficiency—Technical Efficiency (TE), we assume Variable Returns to Scale, and decompose TE into Pure Technical Efficiency and Scale Efficiency. These measures are introduced into Logistic Regression to predict the probability of distress, along with the level of Returns to Scale. Effects of efficiency variables are allowed to vary across industries through the use of interaction terms, while the financial ratios are assumed to have the same effects across all sectors. The results show that the predictive power of the model is improved by this corporate efficiency information.     

基于政府补贴的养老服务市场供给研究

随着我国老龄化速度加快,养老服务的有效供给问题是政府和学者关注的焦点。考虑政府财政补贴下,引入民办与公办养老服务的替代因子,构建民办养老机构与公办养老机构的服务动态供给模型,分析不同补贴方式和补贴力度对服务均衡供给量的影响,并进一步通过补贴乘数分析政府补贴对养老服务机构最优供给决策的影响程度。结果表明:政府对民办养老机构的财政补贴可以增加养老服务市场供给量,相较于运营补贴,政府建设补贴的政策效应更加明显;财政补贴降低了民办养老机构的建设成本和投资风险,刺激社会资本投入的积极性,民办养老服务供给增加幅度大于公办养老服务供给减少幅度,养老服务市场有效供给增加。在财政预算约束下,选择恰当的财政补贴方式,可以提高财政资源的配置效率,增加养老服务市场的有效供给,缓解养老服务财政压力。     

Transformation of wealth produced into quality of life: analysis of the social efficiency of nation-states with the DEA’s triple index approach

Although an essential condition for the occurrence of human development, economic growth is not always efficiently converted into quality of life by nation-states. Accordingly, the objective of this study is to measure the social efficiency—the ability of a nation-state to convert its produced wealth into quality of life—of a set of 101 countries. To achieve this goal, the Data Envelopment Analysis method was used in its standard, cross-multiplicative and inverted form, by means of a new approach called ‘triple index’. The main results indicated that the former Soviet republics and Eastern European countries stood out in terms of social efficiency. The developed countries, notwithstanding their high social indicators, did not excel in efficiency; however, the countries of south of Africa, despite having the worst social conditions, were also the most inefficient.     

随机波动率模型下技术分析指标的一些性质(英文)

一些流行的技术指标(例如布林带,RSI,ROC等)被股市交易者广为使用.交易者将每日(小时,周,……)的实际股价作为计算某个技术指标的样本,通过观察相关频率来指导投资.技术指标的有效性已在广泛的应用中得到了验证.我们已经证明在Black-Scholes模型下,某些技术指标有许多有用的统计性质.作为更一般的情况,随机波动率模型在金融数学中得到了广泛的讨论.本文基于随机波动率模型对技术指标的统计性质进行了研究.研究结果表明,如果股票价格服从随机波动率模型,则技术指标的合理性可以得到有力的证明,从这个角度我们为技术分析奠定理论基础.     

Multiple goals and ownership structure: Effects on the performance of Spanish savings banks

Spanish savings banks (SBs) are financial institutions with a wide mission that includes different stakeholders’ goals. Profit maximization is only one among several goals, and the widespread use of cost or profit efficiency as the only comparative performance measure may prove to be insufficient in this context. To overcome this problem, we build an aggregate performance index for organizations with multiple goals. Furthermore, we show how the ownership structure of SBs influences their economic behavior in two basic ways: (1) the performance level and (2) their goal priorities. In particular, we distinguish two types of ownership structures in our application, namely, organizations controlled by Public Administrations and those controlled by insiders (i.e. managers and workers). Our results indicate that each type has different priorities and differ in their performance indexes. More specifically, the empirical analysis shows that insider-controlled SBs favor goals related to profit maximization and the universal access to financial services and, furthermore, they perform better. In contrast, contributing to regional development becomes the most favored goal when Public Administrations have a majority in the bank.     

Non-Parametric Regression Methods

The nature of the financial time series is complex, continuous interchange of stochastic and deterministic regimes. Therefore, it is difficult to forecast with parametric techniques. Instead of parametric models, we propose three techniques and compare with each other. Neural networks and support vector regression (SVR) are two universally approximators. They are data-driven non parametric models. ARCH/GARCH models are also investigated. Our assumption is that the future value of Istanbul Stock Exchange 100 index daily return depends on the financial indicators although there is no known parametric model to explain this relationship. This relationship comes from the technical analysis. Comparison shows that the multi layer perceptron networks overperform the SVR and time series model (GARCH).     

A literature review on the application of evolutionary computing to credit scoring

The last years have seen the development of many credit scoring models for assessing the creditworthiness of loan applicants. Traditional credit scoring methodology has involved the use of statistical and mathematical programming techniques such as discriminant analysis, linear and logistic regression, linear and quadratic programming, or decision trees. However, the importance of credit grant decisions for financial institutions has caused growing interest in using a variety of computational intelligence techniques. This paper concentrates on evolutionary computing, which is viewed as one of the most promising paradigms of computational intelligence. Taking into account the synergistic relationship between the communities of Economics and Computer Science, the aim of this paper is to summarize the most recent developments in the application of evolutionary algorithms to credit scoring by means of a thorough review of scientific articles published during the period 2000–2012.     

突发事件对交通网络的影响评估指标和方法

近年来,由于自然灾害,不断地环境恶化以及不可预测的灾害侵袭,突发事件时有发生,突发事件可能对交通网络产生非常严重的影响。本文给出了一些指标来表征突发事件对交通网络的影响程度。这些指标适用于用户最优、系统最优以及效率损失等情形。 我们给出了这些指标的性质并讨论了在用户最优、系统最优以及效率损失等情形下的指标之间的关系。交通网络的数值算例表明了关于突发事件的指标的合理性。突发事件对交通网络的影响程度评估对于道路规划、道路维护以及网络脆弱性分析均有重要意义。     

货市与股市波动的超前滞后关系 ——基于复主成分分析法

在传统主成分分析的基础上,复数希尔伯特主成分分析通过将希尔伯特变换与随机矩阵理论相结合获取滤噪经济数据的频域信息,为揭示股票市场与货币市场波动的超前滞后关系提供了途径.实证研究结果显示,在样本区间内,中国股票市场指标相对于货币市场指标来说大部分呈现出超前的变化,而在货币市场中,数量型指标波动较为靠前,价格型指标的反应则较为滞后.此外,股票价格与货币供应量的波动之间存在反馈效应.探索两市场间这样一种动态关系能为政府对金融市场的监管工作提供相应的政策建议.     

The Distance Perspective of Generalized Biadditive Models: Scalings and Transformations

Recently two articles studied scalings in biplot models, and concluded that these have little impact on the interpretation. In this article again scalings are studied for generalized biadditive models and correspondence analysis, that is, special cases of the general biplot family, but from a different perspective. The generalized biadditive models, but also correspondence analysis, are often used for Gaussian ordination. In Gaussian ordination one takes a distance perspective for the interpretation of the relationship between a row and a column category. It is shown that scalings—but also nonsingular transformations—have a major impact on this interpretation. So, depending on the perspective one takes, the inner product or distance perspective, scalings and transformations do have (distance) or do not have (inner-product) impact on the interpretation. If one is willing to go along with the assumption of the author that diagrams are in practice often interpreted by a distance rule, the findings in this article influence all biplot models.     

基于信用利差与Logistic回归的公司违约概率测算模型与实证研究

用Logistic模型计算公司违约概率在实际应用中存在两个问题:一是在缺乏公司违约记录数据库或违约记录数据库不典型的情况下,无法应用该模型或模型计算结果不准确;二是现有Logistic违约概率模型忽视了不同行业财务指标分布特征的差异性,导致公司违约概率计算结果的准确性降低。针对问题一,本文通过公司债券信用利差计算市场隐含的公司违约概率,在Logistic变换的基础上进一步确定Logistic线性回归的参数,使得公司违约概率的计算结果符合债券市场的实际状况。针对问题二,通过不同行业关键财务指标的单因子方差分析,证实了行业间财务指标的分布特征具有显著性差异,通过拟合优度证实了区分行业建立Logistic违约概率模型可显著提高违约概率测算的准确性。本文Logistic违约概率模型的构建过程如下:通过初选财务指标的相关性分析,删除反映信息重复的财务指标;通过Logistic回归中财务指标系数的显著性检验,删除对违约概率解释能力弱的财务指标;以Logistic回归的拟合优度为标准,选取各样本行业Logistic违约概率模型的关键财务指标,建立了机械设备等5个样本行业的Logistic违约概率模型,为样本内行业公司违约概率的准确测算提供模型与方法。本文的创新与特色:一是在无套利条件下,通过公司债券信用利差计算市场隐含的公司违约概率,并对其进行Logistic变换,作为Logistic线性回归的被解释变量,解决了在缺乏公司违约记录数据情况下Logistic违约概率模型的参数估计问题;二是通过单因子方差分析方法,证实了行业间财务指标的分布特征具有显著性差异,说明应区分行业建立Logistic违约概率模型;三是通过财务指标间的相关分析删除反映信息重复的财务指标,通过财务指标系数的显著性检验删除对公司违约概率解释能力弱的财务指标,保证了Logistic违约概率模型中关键财务指标选取的合理性;四是实证研究结果表明,不同行业的Logistic违约概率模型的关键财务指标不同,同一财务指标的参数也存在显著差异。实证研究结果还表明,区分行业建立Logistic违约概率模型与不区分行业相比,前者可将拟合优度及调整后的拟合优度提高近1倍。本文研究结果对于提高公司违约概率测算的准确性具有重要参考意义,对于商业银行贷款定价、公司债券发行定价、银行信用风险管理具有重要参考意义。     

A sequential goal programming model with fuzzy hierarchies to sustainable and responsible portfolio selection problem

Sustainable and responsible (SR) investors have to address two criteria types: both financial ones and those pertaining to sustainability and social responsibility. We present a comfortable tool for SR investors that allow them to express their preferences at two levels: first, by comparing criteria of the same nature, and second, via the comparison between the two superior level criteria (the financial and the SR objectives). Owing to the difficulty involved in determining a precise preference between the conflicting objectives, we address this by goal programming with fuzzy hierarchies (GPFH) modelling. This methodology is a modification of the lexicographic GP approach whereby the relative importance relations among the criteria are modelled by fuzzy relations. The proposed sequential handling for the SR portfolios selection provides information to the investors on the best result they can achieve in regard to their goals. An application to a set of UK-SR mutual funds is presented.     

基于DEA-Malmquist和Tobit regression的物联网上市公司效率评价

物联网的发展已经成为我国实现经济转型的有力支撑,但其发展过程中呈现的波动性问题仍亟需深入研究.从效率的角度,对我国19家物联网公司的发展状况进行了研究.首先,运用DEA模型测算了19家公司2013-2015年的技术效率、纯技术效率、规模效率以及各公司的规模收益状况.计算结果表明物联网上市公司的效率在整体上呈现上升趋势,只有同方股份在三年内规模收益状况为递减.其次,运用DEA-Malmquist测算了19家公司的技术效率变化指数、技术进步指数、纯技术效率变化指数、规模效率变化指数和全要素生产率变化指数.结果表明,技术进步指数低是制约这19家公司生产力发展的关键问题.最后,运用Tobit regression分析了11项财务指标对技术效率、纯技术效率以及规模效率影响的显著性,得出财务指标对规模效率存在显著影响.基于效率和影响因素分析的实际,为物联网上市公司的发展提供合理的建议,推动我国物联网产业实现良性有序发展.