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FUZZY ECONOMIC REVIEW

ISSN (print) 1136-0593 · ISSN (online) 2445-4192

DISCOUNT RATES FOR STARTUPS: THE ENTREPRENEUR’S PERSPECTIVE

Samuel Mongrut. Universidad del Pacifico, Perú. Universidad Autónoma de Nuevo León, México. Email: mongrut_sa@up.edu.pe

Vivian Cruz. Universidad EIA, Colombia. Email: vivian.cruz@eia.edu.co

So far, the estimation of required returns (discount rates) for non-diversified entrepreneurs has remained a mystery. Mongrut and Ramirez (2006) made a contribution to this area by deriving the required return’s lower bound for a non-diversified entrepreneur. However, they used a quadratic utility function, which is the same as the one used to derive the Capital Asset Pricing Model (CAPM) that faces several restrictions. In this research one extends the previous work by deriving equations of required returns using a Hyperbolic Absolute Risk Aversion (HARA) utility function that includes the general quadratic and the logarithmic forms as special cases. Furthermore, we focus our attention not only in the startup characteristics, but also in the characteristics of the entrepreneur. Hence, we derive our equations assuming an entrepreneur with the lowest risk-aversion coefficient that invests almost all his capital in his startup and whose level of wealth approaches to zero. After simulating our equations, we find that required returns (discount rates) ranges between 21% and 56% (with general quadratic preferences) and between 12% and 49% (with logarithmic preferences) at 90% level of confidence with median values of 38% and 22%, respectively. These magnitudes and variations are consistent with required returns declared by entrepreneurs.

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OPTIMIZATION OF K-MEANS WITH SIMULATED ANNEALING HEURISTICS

Ivan O. Cruz-Ruiz. Universidad Autónoma Metropolitana Unidad Iztapalapa, Av. San Rafael Atlixco 186, 09340, Ciudad de México, México. Email: iocr@xanum.uam.mx

Pedro Lara-Velázquez. Universidad Nacional Autónoma de México, C.U., Coyoacán, 04510, Ciudad de México, México. plara@xanum.uam.mx

Eric A. Rincón-García. Universidad Nacional Autónoma de México, C.U., Coyoacán, 04510, Ciudad de México, México. rincon@xanum.uam.mx

Miguel A. Gutiérrez-Andrade. Universidad Nacional Autónoma de México, C.U., Coyoacán, 04510, Ciudad de México, México. gamma@xanum.uam.mx

Sergio G. de-los-Cobos-Silva. Universidad Nacional Autónoma de México, C.U., Coyoacán, 04510, Ciudad de México, México. cobos@xanum.uam.mx

Roman A. Mora-Gutiérrez. Universidad Autónoma Metropolitana Unidad Azcapotzalco, Av. San Pablo Xalpa 180, 02200, Ciudad de México, México. mgra@correo.azc.uam.mx

Carlos A. Hernández-Nava. Universidad Autónoma Metropolitana Unidad Iztapalapa, Av. San Rafael Atlixco 186, 09340, Ciudad de México, México. Email: cahn@xanum.uam.mx

The classification algorithm known as k-means is widely used in different branches of artificial intelligence. Its main objective is to find the k centroids that can repre-sent clusters of information. While this algorithm is reliable, it is not always possi-ble to find the optimal centroids that represent the data set. In this work, different metaheuristic techniques were applied in which the problem of finding the initial centroids was solved, and a novel hybrid algorithm is presented that finds better centroids than those found by the standard k-means algorithm. The new approach improves the classification of the information contained in the tested databases.

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PUBLIC MANAGEMENT FACTORS THAT AFFECT THE EFFICIENT USE OF FINANCIAL RESOURCES IN THE MUNICIPALITIES OF THE MONTERREY METROPOLITAN AREA FUZZY REGRESSION ANALYSIS

Alberto G. Villarreal-Flores. Universidad Autónoma de Nuevo León, Facultad de Contaduría Pública y Administración, Av. Universidad S/N Col. Ciudad Universitaria, Monterrey, México. Email: albertovf19@gmail.com

María M. Carrera-Sánchez. Universidad Autónoma de Nuevo León, Facultad de Contaduría Pública y Administración, Av. Universidad S/N Col. Ciudad Universitaria, Monterrey, México. Email: ma-galy_carrera@hotmail.com

Luis A. Villarreal Villarreal. Universidad Autónoma de Nuevo León, Facultad de Contaduría Pública y Administración, Av. Universidad S/N Col. Ciudad Universitaria, Monterrey, México. Email: lvillvill@hotmail.com

Silverio Tamez-Garza. Universidad Autónoma de Nuevo León, Facultad de Contaduría Pública y Administración, Av. Universidad S/N Col. Ciudad Universitaria, Monterrey, México. Email: drsilveriotamez@gmail.com

Public servants and normal citizens often have criticized public systems because of inefficiency, corruption, poor quality systems, financial and human resources ineffectiveness. As well, governments worldwide, including Mexico, face moments of profound questioning and reconfiguration while academics, public administrators and citizens have debated about the effectiveness in meeting the demands and needs of society. Therefore, different attempts are identified to achieve better results in municipal administrations. This research analyzes the effects of factors such as internal control, accountability, transparency, ethical conduct of public servants and oversight and tax inspection on financial efficiency, in municipalities of the Metropolitan Area of Monterrey. An updated literature review was done and later a statistical analysis based on a questionnaire, which was to be administered to 47 public servants, by using the main components methods to obtain the uncorrelated factors that can be included in the fuzzy regression analysis. Estimated to calculate the efficiency of financial courses, which led to the results of this study that determined that there is a significant positive relationship between the internal control and oversight variables in financial efficiency.

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GENERALIZED METRICS IN CLASSIFIERS

Carlos A. Hernández Nava. Universidad Autónoma Metropolitana Unidad Iztapalapa, Av. San Rafael Atlixco 186, 09340, Ciudad de México, México. Email: cahn@xanum.uam.mx

Pedro Lara-Velázquez. Universidad Autónoma Metropolitana Unidad Iztapalapa, Av. San Rafael Atlixco 186, 09340, Ciudad de México, México. Email: plara@xanum.uam.mx

Hérica Sánchez-Larios. Universidad Nacional Autónoma de México, C.U., Coyoacán, 04510, Ciudad de México, México. Email: herica.sanchez@ciencias.unam.mx

Eric A. Rincón-García. Universidad Autónoma Metropolitana Unidad Iztapalapa, Av. San Rafael Atlixco 186, 09340, Ciudad de México, México. Email: rincon@xanum.uam.mx

Miguel A. Gutiérrez-Andrade. Universidad Autónoma Metropolitana Unidad Iztapalapa, Av. San Rafael Atlixco 186, 09340, Ciudad de México, México. Email: gamma@xanum.uam.mx

Sergio G de-los-Cobos-Silva. Universidad Autónoma Metropolitana Unidad Iztapalapa, Av. San Rafael Atlixco 186, 09340, Ciudad de México, México. Email: cobos@xanum.uam.mx

Roman A. Mora-Gutiérrez. Universidad Autónoma Metropolitana Unidad Azcapotzalco, Av. San Pablo Xalpa 180, 02200, Ciudad de México, México. Email: mgra@xanum.uam.mx

Ivan O. Cruz-Ruiz. Universidad Autónoma Metropolitana Unidad Iztapalapa, Av. San Rafael Atlixco 186, 09340, Ciudad de México, México. Email: iocr@xanum.uam.mx

Euclidean distance and squared Euclidean distance are the most commonly used metrics in research using classifier systems, but it does not mean that they are the ones with which the best results are obtained. In this work, a set of well-known instances are classified using the higher-order Minkowski distance, first with integer values, then with values in hundredths around p = 1, and finally, experiments were conducted with a linear combination of metrics, that is, a hybrid, all of the above in order to observe the behavior of two different classifiers with various metrics and the accuracy they achieve for each database.

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CHILDCARE LINGUISTIC INDEX FOR ARGENTINA

Daniela Goyheix. Universidad de Buenos Aires. Facultad de Ciencias Económicas. Instituto Interdisciplinario de Economía Política de Buenos Aires (IIEP - BAIRES). Ciudad de Buenos Aires, Argentina. E-mail: danielagoyheix@economicas.uba.ar

María José Fernandez. Universidad de Buenos Aires. Facultad de Ciencias Económicas. CONICET. Instituto Interdisci-plinario de Economía Política de Buenos Aires (IIEP - BAIRES). Ciudad de Buenos Aires, Ar-gentina. E-mail: mariajfernandez@economicas.uba.ar

The circumstances in which children are born and their material and intellectual resources determine their abilities and the extent to which they will be able to develop their human potential. Government policies cannot address all the issues that lead to development gaps, but they can provide resources to disadvantaged families to help create nurturing environments for children. This paper proposes a childcare measure that facilitates the analysis of household environmental quality. The indicator synthesizes the level of compliance with good parenting practices associated with the development of essential cognitive and socio-emotional abilities. The purpose is to identify the different degrees of childcare, to assess child living conditions and to contribute to a more efficient use of public funds. We use a linguistic-mathematical model based on the fuzzy sets theory to define a multidimensional linguistic index of childcare. The index encompasses different measures associated with child upbringing with an emphasis on nutritional and health conditions. Remarkably, most of the children in the sample are exposed to mean or high-quality childcare. However, the number of children that evidence very high-quality childcare is low.

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INSOLVENCY PREDICTION FROM FUZZY CLASSIFICATION AND FINANCIAL PROJECTION

Fabian Castiblanco. Universidad La Gran Colombia. Faculty of Economic and Business Sciences. Bogotá DC, Colombia. fabianalberto.castiblanco@ugc.edu.co

Deisy Nohemí Sánchez Villamil. Universidad Cooperativa de Colombia. Faculty of Public Accounting. Bogotá DC, Colombia. deisy.sanchezv@campusucc.edu.co

Yuly Andrea Franco Gómez. Universitaria Agustiniana. Faculty of Economic and Administrative Sciences. Bogotá DC, Colombia. yuly.franco@uniagustiniana.edu.co

This paper proposes a benchmark method based on fuzzy set theory and the c-means fuzzy classification algorithm to detect and forecast business insolvency. The method consists of a set of steps to compare the results obtained in a fuzzy classification process with the projected accounting information. The central aspect of the method is the comparison between the current and future situation of a conglomerate of companies based on a specific set of financial ratios. The future situation is established from the macroeconomic projections of local and foreign analysts. To validate the effectiveness and precision of our proposal, its application is carried out in a specific economic sector of Colombia and the results are compared with the Altman Z2 model.

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INVESTMENT PORTFOLIO SELECTION PROCESS USING DISTANCE OPERATORS

Victor G. Alfaro-García. Universidad Michoacana de San Nicolas de Hidalgo, Facultad de Contaduría y Ciencias Administrativas. Morelia, México. E-Mail: victor.alfaro@umich.mx

Ernesto León-Castro. Faculty of Economics and Administrative Sciences, Universidad Católica de la Santísima Concepción. Concepción. Chile. E-Mail: eleon@ucsc.cl

Fabio Blanco-Mesa. Universidad Pedagógica y Tecnológica de Colombia, Facultad de Ciencias Económicas y Administrativas. Boyacá, Colombia. E-Mail: fabio.blanco01@uptc.edu.co

This paper presents applications of computational intelligence tools in investment decision making processes. The aim is to build effective stock portfolios, for diverse risk-oriented individuals, including both, objective and subjective inputs. The proposed methods include the analysis of 5 different stock shares from companies that are in the Nasdaq 100 index, namely: Microsoft, Amazon.com Inc, MercadoLibre Inc, Intel Corporation and Facebook Inc using the ordered weighted average distance (OWAD) operator, the ordered weighted averaging adequacy coefficient (OWAAC) operator and the ordered weighted averaging index of maximum and minimum level (OWAIMAM) operator. Results show that a risk seeking investor would prefer stocks that display the behavior of the analyzed dataset of Amazon and a conservative investor would prefer Intel. The main advantage of the proposed methods is introducing multiple objective and subjective data in a single formulation that includes risk aversion, aptitude, expectations, and investment inputs, providing a wider representation of options and scenarios.

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A FUZZY MODEL FOR TRADE WAR. AN ANALYSIS OF THE TRADE RELATIONS BETWEEN CHINA-USA AND CHINA-BRAZIL

Carmen Lozano. Universidad La Salle México, Vicerrectoría de Investigación, México. E-mail: carmen.lozano@lasalle.mx

Jesús Macías-Durán. CINVESTAV-IPN México. Ciudad de México. E-mail: macias@math.cinvestav.mx

Cesaire Chiatchoua. Escuela Superior de Economía, Instituto Politécnico Nacional. Mexico City. Mexico E-mail: cchiatchoua@ipn.mx

Trade relations between commerce powers nowadays are crucial in the international economic scene. This has been observed since the entry of China into the World Trade Organization (WTO) in 2001, along with the political changes that have arisen in the United States (USA) during the last decade. The objective of this work is to propose a deterministic model about trade relations between two economic powers with the use of fuzzy logic. This model is also applied to the commerce relation between China with USA and Brazil. The main results show that the model described correctly the exports of these nations and the qualitative methods employed here are adequate to pursue this kind of analyses. Finally, this analysis contributes to the field of international trade by providing a method that combines a qualitative tool and a deterministic model, to study the trade relationship between the USA and Brazil with China.

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