Efficient Frontier

Portfolio decision analysis models support decisions on the allocation of resources among assets with uncertain outcomes (e.g., investments, projects or stocks). These models require information on the decision maker's risk-preferences which can be difficult to obtain in practice. Stochastic dominance criteria show promise in this regard as they can compare portfolios without exact specification of risk-preferences, but the current literature lacks practical approaches for generating the efficient frontier, i.e., the set of those portfolios that are not stochastically dominated by any other portfolio. We address this gap by developing models to identify sets of portfolios that are efficient in the sense of second-or third-order stochastic dominance (SSD, TSD). These models provide novel insights into the composition of portfolios belonging to the efficient frontier by, e.g., identifying those assets that are included in all efficient portfolios. Moreover, the identification of the efficient frontier makes it possible to utilize additional information on the decision maker's risk-preferences to further reduce the set of admissible portfolio alternatives, and to analyze the implications this information has on the amount of capital that should be allocated to each individual asset. We illustrate the usefulness of these models with applications in project portfolio selection and financial portfolio diversification.

The creation of goods and services requires changing the expended resources into the output goods and services. How efficiently we transform these input resources into goods and services depends on the productivity of the transformation process. However, it has been observed there is always a vagueness or imprecision associated with the values of inputs and outputs. Therefore, it becomes hard for a productivity measurement expert to specify the amount of resources and the outputs as exact scalar numbers. The present paper, applies fuzzy set theory to measure and compare productivity performance of transformation processes when numerical data cannot be specified in exact terms. The approach makes it possible to measure and compare productivity of organizational units (including non-government and non-profit entities) when the expert inputs can not be specified as exact scalar quantities. The model has been applied to compare productivity of different branches of a company.

This paper develops the semi-parametrical two-stage Data Envelopment Analysis to detect the efficiency frontier of public Brazilian Minas Gerais state schools. The first stage computes the DEAefficiency, the second one inputs the DEA results to a truncated-regression with background and endowment variables. The new data basis of school proficiency, SIMAVE, and cost-measurement, SICA, either the Educational Census of Education Ministry 2005, permitted this new application of efficiency measurement for schools. The results shows that input-complementarity in and out school contribute to greater performance. Best located schools, where the educational inputs are better, are more efficient in probability. However, there are some good examples of efficient schools emerging from poor regions and, in general terms, all stated educational results can improve considerably if the schools get to improve their efficiency.

Data envelopment analysis is a linear programming‐based operations research technique for performance measurement of decision‐making units. In this paper, we investigate data envelopment analysis from a multiobjective point of view to compute both the efficient extreme points and the efficient facets of the technology set simultaneously. We introduce a dual multiobjective linear programming formulation of data envelopment analysis in terms of input and output prices and propose a procedure based on objective space algorithms for multiobjective linear programmes to compute the efficient frontier. We show that using our algorithm, the efficient extreme points and facets of the technology set can be computed without solving any optimization problems. We conduct computational experiments to demonstrate that the algorithm can compute the efficient frontier within seconds to a few minutes of computation time for real‐world data envelopment analysis instances. For large‐scale artificial da...

The purpose of this study is to provide a broader, economic perspective on customer value management. By developing an efficiency-based concept of customer value we aim at contributing to the presently underrepresented research field of marketing economics. The customer value concept is utilized to assess product performance and eventually to determine the competitive market structure and the product-market boundaries. Our analytical approach to product-market structuring based on customer value is developed within a microeconomic framework. We measure customer value as the product efficiency viewed from the customer's perspective, i.e., as a ratio of outputs (e.g., resale value, reliability, safety, comfort) that customers obtain from a product relative to inputs (price, running costs) that customers have to deliver in exchange. The efficiency value derived can be understood as the return on the customer's investment. Products offering a maximum customer value relative to all other alternatives in the market are characterized as efficient. Different efficient products may create value in different ways using different strategies (output-input-combinations). Each efficient product can be viewed as a benchmark for a distinct sub-market. Jointly, these products form the efficient frontier, which serves as a reference function for the inefficient products. Thus, we define customer value of alternative products as a relative concept. Market partitioning is achieved endogenously by clustering products in one segment that are benchmarked by the same efficient peer(s). This ensures that only products with a similar output-input structure are partitioned into the same sub-market. As a result, a sub-market consists of highly substitutable products. In addition, value-creating strategies (i.e., indications of how to vary inputs and outputs) to improve product performance in order to offer maximum customer value are provided. The impact of each performance parameter on customer value is determined, identifying the value drivers among them. This methodological framework is applied to data of the 1996 German Automobile Club (ADAC) survey.

This paper proposes a framework of IT portfolio selection and examines the impact of IT synergy on a firm's IT portfolio selection. IT resources can be distinguished from other forms of resources by their great potential of enhancing synergy between IT units. Based on prior discussion on types of IT synergy, we classify IT synergy into three types and examine the effects of the different types of IT synergy on the IT portfolio selection. We found that firms of moderate and high risk tolerance are likely to obtain a superior IT portfolio by enhancing IT synergy, whereas firms of low risk tolerance may not benefit from enhancement of IT synergy.

Os sistemas de saúde assumem a responsabilidade não só de melhorar a saúde das populações mas também de as proteger do custo da doença e de as tratar com dignidade. Tendo por base as três dimensões que definem os sistemas de saúde (regulação, financiamento e prestação), e que cada dimensão pode ser dominada por três tipos de atores (estado, social e privado), no âmbito deste trabalho é nosso propósito estudar os sistemas de saúde de tipo Seguro Nacional de Saúde (nomeadamente dos países como o Canadá, a Austrália, a Nova Zelândia e a Irlanda), na perspetiva das respostas às legitimas expectativas dos cidadãos. Assim, iremos proceder a uma revisão da literatura para chegarmos aos objetivos específicos: (i) descrever sucintamente os sistemas de saúde baseados no seguro nacional de saúde, onde se podem incluir a Austrália, Canadá, Irlanda e Nova Zelândia; (ii) caracterizar o conceito de responsiveness; (iii) identificar a presença da responsiveness nestes sistemas. A forma como os sistemas de saúde interagem com as pessoas é determinante para o seu bem estar. Avaliar o desempenho dos sistemas de saúde não se limita à avaliação dos resultados em saúde mas também no respeito e integração dos princípios éticos e dos direitos humanos.

This paper examines trends in banknote printing during the period 2000-2005 for a crosssection of 56 central banks. It was identified that central banks have implemented new strategies to increase efficiency in the production of banknotes, primarily due to the increase in the demand for currency in recent years. One of these strategies has been to involve the private sector through different modalities (e.g. joint ventures, subsidiaries or purchase of banknotes from specialized companies). With the aim to examine the effect of these strategies and other banknote printing features on production costs, a cost function using a panel data model with random effects was estimated. It was identified that the denomination structure, the size of banknotes, and the production method used by central banks have a significant impact over printing costs. Government printing was found to be the most costly method, while involving companies in the process substantially reduces production costs. Based on these results, a non-parametric efficient frontier model was used to measure technical cost efficiency and changes in productivity of central banks. It was found that most central banks have increased its technical efficiency during the period, especially when the private sector has been involved. The Malmquist index showed a moderate increase in productivity, mainly due to increases in scale efficiency instead of technical change.

In the transboundary water resources allocation issues, there has been so far very limited progress made in terms of allocation techniques. This study introduces a composite water resources allocation approach that integrates game theory and Pareto frontier technique over the case of the Euphrates and Tigris. The proposed approach searches an acceptable solution set over the Pareto frontier surface via game theory based core constraints. The base model to generate the Pareto Frontier Surface is the Euphrates and Tigris River Basin Model, which is a linear programming model maximizing net economic benefits while optimally allocating scarce water resources in the basin. Results show that i) game theory provides a determinative backbone for an efficient and effective use of Pareto Frontier Surface and ii) upstream countries have upper hand position due to the geographic context.

In the transboundary water resources allocation issues, there has been so far very limited progress made in terms of allocation techniques. This study introduces a composite water resources allocation approach that integrates game theory and Pareto frontier technique over the case of the Euphrates and Tigris. The proposed approach searches an acceptable solution set over the Pareto frontier surface via game theory based core constraints. The base model to generate the Pareto Frontier Surface is the Euphrates and Tigris River Basin Model, which is a linear programming model maximizing net economic benefits while optimally allocating scarce water resources in the basin. Results show that i) game theory provides a determinative backbone for an efficient and effective use of Pareto Frontier Surface and ii) upstream countries have upper hand position due to the geographic context.

El presente informe es realizado con el propósito de demostrar y explicar el análisis sobre la rentabilidad en la gestión de invertir en la bolsa de valores del mercado estadounidense, para ello el documento el desarrollo se encuentra explicado bajo tres objetivos específicos, en lo que corresponde con el primer objetivo específico se hace una consulta documental donde se profundiza en el marco teórico, se profundiza sobre teorías como portafolio, paridad y la teoría de diversificación en el siguiente apartado se profundiza en la descripción del sector, es decir, en el funcionamiento de la bolsa, los agentes que intervienen y entre otros factores. Para el segundo objetivo, se explica el comportamiento en la compra de acciones en las empresas: Amazon, Tesla, Apple, Roblox y Cronos Ground, mediante la metodología de realizar y aplicar los conocimientos en el ejercicio simulacro PLUS 500 donde se crea el portafolio con la compra de acciones en las empresas anteriormente mencionadas, para terminar en el tercer objetivo se realiza un análisis del portafolio creado para el  simulacro mediante los resultados y discusión.
Palabras clave: Acciones, Bolsa de valores, Mercado Bursátil, PLUS 500, Portfolio de inversión.


The article is made with the purpose of demonstrating the idea of investing in the stock market of the U.S. market, and thus, observe the behavior in the purchase of shares in the companies: Amazon, Tesla, Apple, Roblox and Cronos Ground, therefore, for the development of the article is divided into theoretical framework, conceptual framework and methodological section. In the theoretical framework, theories such as portfolio, parity and diversification theory are discussed in depth in the following section, the description of the sector, that is, the operation of the stock market, the agents involved and other factors, and finally the methodology, which responds to a simulation exercise conducted in PLUS 500 where the portfolio is created with the purchase of shares in the companies Amazon, Tesla, Apple, Roblox and Cronos Ground, and thus determines whether the creation and analysis of the portfolio in the simulation is feasible.

This article presents a model for investing in renewable energies in the framework of the Spanish electricity market in a way that risk is minimised for the investor while returns are maximised. The model outlined here is based on an economic model for calculating cash flows intended to obtain the internal rate of return (IRR) of the different energies being studied: wind, photovoltaic, mini hydro and thermo electrical. The IRRs obtained are considered the returns on investments, while their standard deviations are considered associated risks. In order to minimise risk, a comprehensive portfolio of investments is created that includes all of the available energies by means of a system of linear equations. The solution of the linear system is graphically checked using the efficient frontier method for the different financing options. Several case studies within the Renewable Energies Plan (PER is its Spanish abbreviation) that is in force in Spain in the period 2005-2010 are analysed in order to illustrate the method, as are other case studies using different types of financing, helping us to reach the pertinent conclusions.

Sugito, S.Si, M.Si NIP. 197610192005011001 iv KATA PENGANTAR Alhamdulillah, puji syukur penulis panjatkan kehadirat Allah SWT atas rahmat dan hidayah-Nya, sehingga penulis dapat menyelesaikan tugas akhir dengan judul "Penentuan Bobot Portofolio Optimal dengan Metode Resampled Efficient Frontier untuk Perhitungan Value at Risk pada Data Berdistribusi Normal". Dalam penulisan tugas akhir ini penulis mengalami banyak hambatan. Namun atas bantuan dari berbagai pihak, tugas akhir ini dapat diselesaikan dengan baik. Oleh karena itu, penulis ingin menyampaikan rasa terima kasih kepada:

The purpose of investors in investing is to get a return, but investors also have to bear the risks that might exist. There are 3 types of investors in investment based on their preference for risk, namely risk aversion (risk averter), moderate risk takers (risk moderate), and high risk takers (risk takers). To obtain an optimal portfolio for each type of investor, the Resampled Efficient Frontier Method is used with Monte Carlo Simulation as much as 700 times, to obtain more parameter estimates. The results of the Resampled Efficient Frontier from Efficient Frontier will take 51 efficient points to determine the optimal portfolio for each type of investor. The efficient point taken is the 1st, 26th and 51st efficient points for the investor risk averter type, risk moderate, and risk taker. To determine the estimated loss in investment, the VaR value is calculated based on the monthly return data of BBNI, UNTR, INKP, and KLBF shares for the period February 2013 to March 2017, with a...

Portfolio optimisation has a number of constraints resulting from some practical matters and regulations. The closed-form mathematical solution of portfolio optimisation problems usually cannot include these constraints. Exhaustive search to reach the exact solution can take prohibitive amount of computational time. Portfolio optimisation models are also usually impaired by the estimation error problem caused by lack of ability to predict the future accurately. A number of Multi-Objective Genetic Algorithms are proposed to solve the problem with two objectives subject to cardinality constraints, floor constraints and round-lot constraints. Fuzzy logic is incorporated into the Vector Evaluated Genetic Algorithm (VEGA) to but solutions tend to cluster around a few points. Strength Pareto Evolutionary Algorithm 2 (SPEA2) gives solutions which are evenly distributed portfolio along the effective front while MOGA is more time efficient. An Evolutionary Artificial Neural Network (EANN) is proposed. It automatically evolves the ANN"s initial values and structures hidden nodes and layers. The EANN gives a

Portfolio optimisation has a number of constraints resulting from some practical matters and regulations. The closed-form mathematical solution of portfolio optimisation problems usually cannot include these constraints. Exhaustive search to reach the exact solution can take prohibitive amount of computational time. Portfolio optimisation models are also usually impaired by the estimation error problem caused by lack of ability to predict the future accurately. A number of Multi-Objective Genetic Algorithms are proposed to solve the problem with two objectives subject to cardinality constraints, floor constraints and round-lot constraints. Fuzzy logic is incorporated into the Vector Evaluated Genetic Algorithm (VEGA) to but solutions tend to cluster around a few points. Strength Pareto Evolutionary Algorithm 2 (SPEA2) gives solutions which are evenly distributed portfolio along the effective front while MOGA is more time efficient. An Evolutionary Artificial Neural Network (EANN) is proposed. It automatically evolves the ANN"s initial values and structures hidden nodes and layers. The EANN gives a

The issue of government expenditure efficiency has recently attracted the interest of policymakers and academics all over the globe. Public expenditure is regarded an essential tool in a government's ongoing attempts to improve the provision of public goods and services to attain growth targets. With the rising demand for public spending, it is not appropriate to reduce public expenditures. Rising government expenditures may strain public resources, result in a tax burden and exert pressure on budgetary allocation leading to concern about evaluating the efficiency of public spending. The present study aims to evaluate the efficiency of public spendings in the health and education sectors in Punjab province from 2011-2018. In the first stage, this study employed a non-parametric data envelopment analysis technique. Various input and output-oriented efficiency scores are estimated using the DEA framework. The findings show that, on average, Punjab's government spends money more effectively on health care than education. This study also investigated the factors behind the variation in efficiency by using the Tobit regression model. The result of the regression model reveals that the availability of physical infrastructure in the health and education areas is associated with better outcomes, improving better human development spending. Inflation negatively and significantly affects spending *The authors are respectively MPHIL Scholar,

The risk-return relationship is an analysis especially for the investors who are risk aversion. In this context, their decision to invest in an investment strategy is a complex process. This complexity is larger for financial capital markets which are not very liquid. Hence, the aim of this study is the analysis of stock exchange capitalization in the Western Balkans Region, and the possibility of building an efficient frontier curve of investments, and finding the optimal potential portfolio. In this study, we analyzed the daily stock quotations of the five Western Balkan countries which are not members of the European Union, and these data are proceeded by five indexes with the official daily publications of quotations. The time-series data are divided into three semi-annual (2019 and 2020). The analysis also has calculations in terms of return on the capital distribution as well as the risk level. Realizing this major purpose used Lagrange multipliers and interpolating polynomial methods, which have generated the efficient frontier curves. Whereas, determining the profit or loss intervals based on the risk point used VaR and CVaR estimation techniques according to the Monte Carlo simulation for geometric Brownian motion for the historical data of daily logarithmic returns. The major hypothesis in this study finds out that the stock exchange indexes of the Western Balkans Region are not efficient (in the equilibrium) because an optimal portfolio cannot be found according to the active investing, nevertheless exists a possibility diversification only for the passive investing.

This study uses data for 2006/7, for the Hlabisa, Dumbe and Simdlangentsha districts in KwaZulu Natal, to investigate the relative efficiencies of conventional, insect resistant (Bt) and herbicide tolerant (RR) maize grown by small farmers. The paper fits a stochastic efficiency frontier using maximum likelihood methods. The results show that both GM technologies have very little impact on efficiency and that the tillage system is an important determinant of efficiency levels. This is despite the fact that farmers using herbicide tolerant seed have yields that were 85% higher. The cost of the seed cancels out this gain in the efficiency estimates and there is every reason to believe that these are the best farmers. The employment effects of the GM technologies are also investigated, as the RR technology is intended to be labour saving and used in conjunction with the minimum tillage method, locally known as planting without ploughing.

This study uses data for 2006/7, for the Hlabisa, Dumbe and Simdlangentsha districts in KwaZulu Natal, to investigate the relative efficiencies of conventional, insect resistant (Bt) and herbicide tolerant (RR) maize grown by small farmers. The paper fits a stochastic efficiency frontier using maximum likelihood methods. The results show that both GM technologies have very little impact on efficiency and that the tillage system is an important determinant of efficiency levels. This is despite the fact that farmers using herbicide tolerant seed have yields that were 85% higher. The cost of the seed cancels out this gain in the efficiency estimates and there is every reason to believe that these are the best farmers. The employment effects of the GM technologies are also investigated, as the RR technology is intended to be labour saving and used in conjunction with the minimum tillage method, locally known as planting without ploughing.

The goal of this article is to present the relationship between numerical optimization tools applied to investments and preference theory, using utility riskaversion functions, in the determination of optimum portfolio for the upstream sector. Some articles have already been published in Brazilian(1) and international(2) magazines and congresses. This article, however goes a little beyond the previous ones. The petroleum industry is very singular on the economy, featuring huge uncertainties associated to the return on investment. In an environment like this, it is natural to search for tools that may identify and reduce risks. Given the extensive amount of capital invested in a block for its exploration, appraisal and possible development, risk analysis finds, in this field, very extensive use. Further on this article, the Capital Asset Pricing Model (CAPM) and risk analysis techniques are going to be introduced, discussing a case applied to the petroleum exploration industry. The main feature of this article is the integration between CAPM and Risk Analysis through the Preference Theory, using utility functions and the certainty equivalent concept.

There are numerous ways to indicate the degree of banking competition across countries. Antitrust authorities rely on the structure-conduct-performance paradigm while academics prefer price mark-ups (Lerner index) or correlations of input costs with output prices (H-statistic). These measures are not always strongly correlated when contrasted across countries or positively correlated within countries over time. Frontier efficiency analysis is used to devise an alternative indicator of competition and rank European countries by their dispersion from a "competition frontier". The frontier is determined by how well payment and other costs explain variations in loan-deposit rate spread and non-interest activity revenues.

This study investigates the impact of specific behavioral biases on stock market investment decisions, focusing on overconfidence, herd behavior, availability bias, representativeness, disposition effect, loss aversion, and anchoring. Utilizing a Likert-scale survey, we measured the prevalence and intensity of these biases among a diverse group of stock market investors. Our findings reveal that certain biases, particularly overconfidence and herd behavior, significantly influence investment decisions, often leading to patterns of irrational trading and market inefficiencies. This research underscores the critical need for investors and financial advisors to recognize and mitigate the effects of these biases to enhance decision-making processes. The practical implications of our study suggest strategies for behavioral adjustments that can potentially shield investors from making suboptimal decisions driven by psychological biases. The originality of this study lies in its methodological approach and its contribution to the existing literature by quantifying how deeply embedded these biases are in the decision-making processes of individual investors. This paper not only advances the theoretical framework of behavioral finance but also provides empirical evidence that can be used to develop more effective investor education and behavioral intervention strategies.

We consider nonlinear stochastic optimization problems with probabilistic constraints. The concept of a p-efficient point of a probability distribution is used to derive equivalent problem formulations, and necessary and sufficient optimality conditions. We analyze the dual functional and its subdifferential. Two numerical methods are developed based on approximations of the p-efficient frontier. The algorithms yield an optimal solution for problems involving r-concave probability distributions. For arbitrary distributions, the algorithms provide upper and lower bounds for the optimal value and nearly optimal solutions. The operation of the methods is illustrated on a cash matching problem with a probabilistic liquidity constraint.

Index tracking seeks to minimize the unsystematic risk component by imitating the movements of a reference index. Partial index tracking only considers a subset of the stocks in the index, enabling a substantial cost reduction in comparison with full tracking. Nevertheless, when heterogeneous investment profiles are to be satisfied, traditional index tracking techniques may need different stocks to build the different portfolios. The aim of this paper is to propose a methodology that enables a fund's manager to satisfy different clients’ investment profiles but using in all cases the same subset of stocks, and considering not only one particular criterion but a compromise between several criteria. For this purpose we use a mathematical programming model that considers the tracking error variance, the excess return and the variance of the portfolio plus the curvature of the tracking frontier. The curvature is not defined for a particular portfolio, but for all the portfolios in t...

The objective of this study is to analyse the impact of capital mobility on the effectiveness of monetary policy in Mozambique between 2000 and 2023. The motivation stems from the approval of Exchange Law No. 28/2022, which establishes the principle of the progressive liberalization of foreign exchange operations, promoting greater international financial integration. In this context, it becomes crucial to understand how the liberalization of the capital account influences the Bank of Mozambique’s ability to achieve its goals. To address the research question, a monthly dataset with 288 observations was used, compiled from the Bank of Mozambique, the National Institute of Statistics, and the World Bank. The methodology is based on qualitative response econometric models – Ordinary Least Squares (OLS), Logit, and Probit – complemented by static and dynamic robustness models. The effectiveness of monetary policy is measured using two proxies: the achievement of the inflation target (a binary variable) and the proximity of real GDP to its potential level (output gap, a continuous variable). The study’s results indicate that capital mobility, measured through the capital account and financial flows, is positively associated with monetary policy effectiveness. A one percentage point increase in capital mobility is associated with a 1.9 percentage point increase in the probability of achieving the inflation target, ceteris paribus. Regarding the output gap, both the static and dynamic models confirm the main findings. These results are consistent with the theory of the impossible trinity and the monetary transmission mechanisms, while also underscoring the importance of macroprudential policies and monetary–exchange rate coordination in the face of external risks.

In this paper we use Bayesian methods to characterize and adjust for two potential biases in data envelopment analysis, the first from decision-making units (DMUs) that may be misclassified as efficient, and the second related to the curse of dimensionality (COD). We propose a theoretically appropriate triangular prior distribution for the proportion of misclassified DMUs and use it to derive the concordant posterior distribution. Simulation analysis suggests that a triangular prior may outperform an ignorance prior in small samples where COD-biases are most likely to exist. An application applies the model to data from the Turkish electric industry.

This study establishes a novel mathematical framework for stochastic maintenance optimization in production systems by integrating Markov decision processes (MDPs) with convex programming theory. We develop a Z-transformation-based dual-space decomposition method to reconstruct MDPs into a solvable linear programming form, resolving the inherent instability of traditional models caused by uncertain initial conditions and non-stationary state transitions. The proposed approach introduces three mathematical innovations: (i) a spectral clustering mechanism that reduces state-space dimensionality while preserving Markovian properties, (ii) a Lagrangian dual formulation with adaptive penalty functions to handle operational constraints, and (iii) a warm start algorithm accelerating convergence in high-dimensional convex optimization. Theoretical analysis proves that the derived policy achieves stability in probabilistic transitions through martingale convergence arguments, demonstrating structural invariance to initial distributions. Experimental validations on production processes reveal that our model reduces long-term maintenance costs by 36.17% compared to Monte Carlo simulations (1500 vs. 2350 average cost) and improves computational efficiency by 14.29% over Q-learning methods. Sensitivity analyses confirm robustness across Weibull-distributed failure regimes (shape parameter 𝛽∈
[1.2, 4.8]) and varying resource constraints.

The perception of people at large towards any insurance product is need for everyone but it is seldom kept on priority. Insurance holds a considerable importance in layman's life as it caters the financial security needs contributing to social welfare. Insurance plays the vital role in social welfare as it is recognised by the government for providing tax benefits in India. The changing life style in this era has resulted into increased risk of life and in addition spending habits have also been influenced. Under this situation, Insurance for life cover and inculcating habit of saving out of disposable income has proved to be an effective and trustworthy instrument. But being nonpriority commodity from the many people's perception, Insurance is sold using aggressive marketing techniques or is it made mandatory in some schemes, due governmental interference. Since Insurance hedges risk, emotions of the buyers are associated with it. It was found that emotions arising out of fear and risk have significant influence on decision making process. These emotions are called as behavioural biases and comes under the domain of behavioural finance. There are many behavioural biases which are studied. This paper aims to study two such behavioural biases viz.. Framing bias and Mental Accounting bias which have significant influence on decision making process while making any investment in insurance.

Otto-von-Guericke-Universität Magdeburg, frank.werner@ovgu.de In a resource-constrained scheduling problem, one wishes to schedule the jobs in such a way that the given resource constraints are fulfilled and a given objective function attains its optimal value. In this paper, we deal with single machine schedul-ing problems with a non-renewable resource, such problems are also referred to as financial schedul-ing problems. The research in the area of scheduling problems with a non-renewable resource is rather limited. In [1], some polynomially bounded algorithms are presented for scheduling problems with precedence constraints (not restricted to single machine prob-lems). Some results for preemptive scheduling of independent jobs on unrelated parallel machines have been presented in [2]. Toker et al. [3] have shown that the problem of minimizing the makespan with a unit supply of a resource at each time period is polynomially solvable. Janiak et al. [4, 5] have considered single mac...

There are segments in society that are deprived and have low incomes across the globe, particularly in developing countries , where a dual financial system exists, consisting of both formal and informal sectors, either equally or differently depending on each country. Formal financial systems systematically isolate individuals with low incomes for several reasons, including their limited ability to provide guarantees to secure loans against any risk, as well as their limited legal access, resulting in relatively high transaction costs . The inefficiency and weakness of the formal and informal financial system in countries such as India has resulted in inadequate absorption of the poor, leading to the creation of alternative methods to meet the requirements of poor households (Sinha & Pandey, 2019). One alternative is access to credit through microfinance and credit associations, which are covered by social and solidarity financing, thereby reducing the burden of poverty and ensuring greater protection for borrowers and lenders than traditional financial transactions do. These alternatives have proven successful in developing countries, leading to the adoption of the concept of microfinance to achieve maximum growth and support it through relevant government programs and policies in all related activities . In India, microcredit is facilitated through various institutional mechanisms, such as cooperatives, joint liability groups, and SHGs by enabling the rural poor to access financial resources that were previously out of reach . These institutions are committed to flexibility, transparency, and democratic self-governance, as well as adherence to ethics, solidarity, and informal credit. In the self-help group model, women empowerment through fostering their collective engagement has been one of the primary objectives, in addition to its provision of assistance to underprivileged groups in attaining credit access . Achieving the objectives of a self-help group is a challenging task, as it operates as a social institution with a development approach that consistently strives to maintain financial sustainability, empowering women and communication among its beneficiaries. As a result, many self-help groups have not achieved the desired level of success due to a range of issues, including the lack of clear structural organisation, active participation and accountability Abstract Over the past decades, social and solidarity finance initiatives have gained significant importance, particularly in South-East countries such as India, especially for poor women. These initiatives are often linked to social empowerment through collective action and institutions. The women self-help group (SHG) as an institution is designed to empower women through a wider range of initiatives such as savings, credit, micro-insurance, micro-justice and other microfinance '+' social activities including education and health. However, the existing body of knowledge has not significantly covered the empirical based efficiency of SHG in empowering women with scientific measurement tool. The Data Envelopment Analysis (DEA) tool was employed in this paper as an appropriate tool to measure the efficiency of SHGs in women empowerment. Women empowerment with socio-economic and human dimensions has been considered as the output of this tool. On the other side, the CRS Input-Oriented Model of DEA used inputs such as: setting vision, mission and bylaw preparation; exposure and training; governance; building social capital; market linkage; social networking; and engagement with other development schemes. The data was collected through a structured interview schedule from 62 self-help groups in the Mayurbhanj district of Odisha, and data analysis was done through STATA software. The findings confirmed that 30 out of 62 SHGs were relatively more efficient in empowering women. The remaining 32 SHGs were operating below the required efficiency level. Therefore, it can be concluded that the efficiency of SHGs is significantly depends on the functioning of the facilitating activities (considered as inputs in this paper) as mentioned above.

A well-known problem of using radial projection in Data Envelopment Analysis (DEA) is that the solution may be only weakly efficient -not necessarily efficient. Our aim is to overcome this drawback by developing a lexicographic approach to projecting radially any unit onto the efficient frontier -not only onto the weakly efficient frontier. The approach is based on the idea to apply radial projection by stepwise dropping component(s) from the radial projection vector until the efficient frontier is reached. The approach has two main difference compared to the traditional approach: 1) the target unit on the efficient frontier is found in the spirit of radial projection and 2) the (in)efficiency score is not necessarily the same for all controllable variables. A numerical illustration and an empirical example are used to demonstrate the approach.

O presente artigo tem como proposito analisar a eficiencia tecnica e os retornos a escala na producao agropecuaria dos municipios do Estado de Mato Grosso (MT), Brasil, identificando aqueles que utilizam da maneira mais otima possivel os recursos disponiveis em seus territorios. Para esse fim e empregada uma Analise Envoltoria de Dados – DEA, com o proposito de obter um melhor panorama da eficiencia tecnica e de escala realizando uso de um mapa de georeferenciamento. Os resultados evidenciam que o Estado de Mato Grosso conta com 21 municipios que se podem considerar Benchmarks , quanto os retornos constantes de escala, ja em relacao aos retornos variaveis de escala os municipios considerados eficientes tecnicamente aumentam para 33. Do mesmo modo, se identificou a quantidade de municipios que operam em retornos crescentes ou decrescentes de escala, o qual permite sugerir o aumento ou a diminuicao da producao.

Modern portfolio theory introduced by Markowitz in 1952 is the most popular portfolio optimization framework established based on the trade-off between risk and return as an operation research model. The main shortcoming of applying Markowitz portfolio optimization in practice is that the obtained optimal weights are really sensitive to the embedded uncertainty in return series of stocks. In this paper, it is demonstrated how using a new methodology of time series clustering as a remedy can lead to a more robust and accurate portfolio in terms of the gap between mean variance efficient frontier obtained from the optimization model and the one observed in reality. In this regard, two similarity measures, the autocorrelation coefficients and the weighted dynamic time warping, are used in an innovative way to construct the desired portfolio optimization model. Moreover, the effectiveness of proposed approach is investigated in two different market conditions: semi-realistic and full-realistic. In the first one, it is assumed that the forecasted and realized stocks mean returns are the same; however, these returns are not necessarily equal in the second market conditions. Finally, a database of stock prices from the literature is utilized to show the robustness and accuracy of the proposed approach in empirical results in comparison with applied similarity measures in previous researches.

This paper discusses a methodology to assess the performances of tourism management of local governments when economic and environmental aspects are considered as equally relevant. In particular, the focus is on the comparison and efficiency assessment of Italian municipalities located on the costal areas. In order to assess the efficiency status of the considered management units, Data Envelopment Analysis (DEA), a methodology for evaluating the relative efficiency of decision making units, is applied. The efficiency index measure used in DEA analysis accounts for both environmental and economic features correlated to the tourism industry. Further, potential managerial improvements for those areas resulting far from the efficiency frontier can be investigated.

Data envelopment analysis (DEA) is a common non-parametric frontier analysis method. The multiplier framework of DEA allows flexibility in the selection of endogenous input and output weights of decision making units (DMUs) as to cautiously measure their efficiency. The calculation of DEA scores requires the solution of one linear program per DMU and generates an individual set of endogenous weights (multipliers) for each performance dimension. Given the large number of DMUs in real applications, the computational and conceptual complexities are considerable with weights that are potentially zero-valued or incommensurable across units. In this paper, we propose a twophase algorithm to address these two problems. In the first step, we define an ideal DMU (IDMU) which is a hypothetical DMU consuming the least inputs to secure the most outputs. In the second step, we use the IDMU in a LP model with a small number of constraints to determine a common set of weights (CSW). In the final step of the process, we calculate the efficiency of the DMUs with the obtained CSW. The proposed model is applied to a numerical example and to a case study using panel data from 286 Danish district heating plants to illustrate the applicability of the proposed method.

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This paper presents a critical history of the environmental Kuznets curve (EKC). The EKC proposes that indicators of environmental degradation first rise, and then fall with increasing income per capita. Recent evidence shows however, that developing countries are addressing environmental issues, sometimes adopting developed country standards with a short time lag and sometimes performing better than some wealthy countries, and that the EKC results have a very flimsy statistical foundation. A new generation of decomposition and efficient frontier models can help disentangle the true relations between development and the environment and may lead to the demise of the classic EKC.

This study employs a stochastic frontier technique to estimate managerial efficiency levels in the hotel industry. The only prior efficiency study in this sector employed a linear-programming technique termed data envelopment analysis (DEA). That study found the hotel industry to be operating at a 89% efficiency level. The stochastic frontier approach overcomes many of the potential statistical limitations of DEA and allows for additional insights on efficiency in the hotel market. The average efficiency measures for the hotel industry estimated by the stochastic frontier approach are high and consistent with the results obtained using DEA. In particular, average efficiency was estimated at 89.4%, with the most and least efficient hotels operating at a 92.1% and a 84.3% efficiency level, respectively.

Wydatki na opiekę zdrowotną w Polsce w 2010 roku wyniosły 98 845 mln zł (6,98% PKB), z czego środki publiczne stanowiły 72,2% ogółu wydatków, a prywatne 27,8%. W strukturze wydatków publicznych 88,4% stanowiły wydatki NFZ. W strukturze dostawców usług opieki zdrowotnej 35,4% wydatków bieżących przeznaczone było na funkcjonowanie szpitali i były to w 96,5% środki publiczne 1 . Efektywność funkcjonowania opieki zdrowotnej powinna być w centrum uwagi decydentów zajmujących się organizacją jej funkcjonowania. Zainteresowanie pomiarem efektywności ochrony zdrowia na świecie wynika ze zwiększających się kosztów utrzymania tych systemów 2 . Nieefektywność występuje wtedy, gdy dostawca usług medycznych wykorzystuje relatywnie większą liczbę nakładów w porównaniu z dostawcą, leczącym podobną liczbę pacjentów o podobnej strukturze przypadków, ale zużywającym mniej nakładów 3 . W systemie opieki zdrowotnej bada się dwa typy efektywności: tę związaną z działaniami medycznymi i tę związaną z zarządzaniem. Efektywność działań medycznych wynika z decyzji podejmowanych przez lekarza w zakresie wykorzystania zasobów potrzebnych do osiągnięcia stałej jakości wyleczonych pacjentów. Efektywność zarządzania wymaga zastosowania w praktyce zasad mi-1

We address the multi-period portfolio optimization problem with the constant rebalancing strategy. This problem is formulated as a polynomial optimization problem (POP) by using a mean-variance criterion. In order to solve the POPs of high degree, we develop a cutting-plane algorithm based on semidefinite programming. Our algorithm can solve problems that can not be handled by any of known polynomial optimization solvers.

Este artículo aborda tres aspectos de la sostenibilidad de la extracción de petróleo en Colombia para el período 1998 - 2003: i) los precios que reflejan la escasez de este recurso natural no renovable; ii) el valor del capital petróleo para el período analizado y, finalmente, utilizando la metodología del Valor del Capital Natural de Mäler (2001) iii) la sostenibilidad

The mean-variance (MV) portfolio optimization targets higher return for investment period despite the unknown stochastic behavior of the future asset returns. That is why a risk is explicitly considering, quantified by algebraic characteristics of volatilities and co-variances. A new probabilistic definition of portfolio risk is the Value at Risk (VaR). The paper makes explicit inclusion and minimization of VaR as a quantitative measure of financial sustainability of a portfolio problem. Thus, the portfolio weights as problem solutions will respect not only the MV requirements for risk and return, but also the additional minimization of risk defined by VaR level. The portfolio problem is defined in a new, bi-level form. The upper level minimizes and evaluates the VaR value. The lower level evaluates the optimal assets weights by minimizing portfolio risk and maximizing the return in MV form. The bi-level model allows to have extended set of portfolio solutions with the portfolio wei...

The optimal resource allocation of sets of securities, available in the financial market can be done by solving a multi- criterion optimization task, aimed at maximization of portfolio return and minimization of portfolio risk. Here is proposed the utilization of hierarchical coordination for solving the bi-level optimization problem, which formalizes the investment process. A two-level hierarchical approach for solving the portfolio opti- mization problem is applied where the optimal Sharp ratio of risk versus return is solved at the upper level and as a result is determined by the investor's preferences for taking risk on the basis of objective considerations. The optimal portfolio is evalu- ated at the lower level. based on both optimization and probability theory. The investor's goal is to maximize the return and to minimize the risk of the investment decisions. The investor's return is formalized as the mean value of a random behaved function of the portfolio securi...