Evaluation of Greek construction companies’ securities using UTADIS method

The evaluation of stocks and the selection of the ‘best’ ones is an important step in the process of constructing an optimal portfolio. This study proposes the multicriteria method UTADIS (UTilités Additives DIScriminantes) for the sorting of stocks in categories incorporating, not only quantitative meas - ures, but also the knowledge as well as the preferences of experts. The study illustrates the application of the method on the construction industry stocks in Athens Stock Exchange, using the financial characteristics of the companies. The model developed is evaluated according to its usefulness in a decision process. Further research and the application of the method in other indus - tries’ stocks can establish the method as an important tool in stock evaluation and the relative decision making process.peer-reviewe

La recherche sociale appliquee et la productivite en Grece, 1961-1971

[Δε διατίθεται περίληψη][No abstract available

Impact of auditor tenure on audit quality: European evidence

This study examines the relationship of auditor tenure and audit quality in four European countries, namely Germany, France, Italy and Spain, with the innovative GMM (Generalized Methods of Moments) model during the period from 2005 to 2013.Two GMM methods are used with two alternative definitions of crisis – the main and the robustness method. The results agree regardless of the fact that some of the control variables are excluded in the robustness test.The results support the finding that in Spain, there is an impact of auditors’ long-term tenure on discretionary accruals, affecting auditors’ quality and independence indirectly. In addition, the crisis affected Germany and France as far as the change in negative and positive values of GDP is concerned. In this respect, the crisis affected the above two countries when the years before and after the crisis are considered as a robustness check. The results contain important implications for accountant regulators and policy makers

Evaluation of empirical attributes for credit risk forecasting from numerical data

In this research, the authors proposed a new method to evaluate borrowers’ credit risk and quality of financial statements information provided. They use qualitative and quantitative criteria to measure the quality and the reliability of its credit customers. Under this statement, the authors evaluate 35 features that are empirically utilized for forecasting the borrowers’ credit behavior of a Greek Bank. These features are initially selected according to universally accepted criteria. A set of historical data was collected and an extensive data analysis is performed by using non parametric models. Our analysis revealed that building simplified model by using only three out of the thirty five initially selected features one can achieve the same or slightly better forecasting accuracy when compared to the one achieved by the model uses all the initial features. Also, experimentally verified claim that universally accepted criteria can’t be globally used to achieve optimal results is discussed

Defense Extensions for Website Fingerprinting Attacks on Nginx Web Server

Το Website Fingerprinting είναι μια προσπάθεια αναγνώρισης της σελίδας που επισκέπτεται κάποιος υπό ανώνυμη και κρυπτογραφημένη δικτυακή κίνηση. Παρόλο που αυτού του είδους η επίθεση μπορεί να μην είναι ιδιαίτερα αποτελεσματική στον παγκόσμιο ιστό, στο δίκτυο του tor, οι ιστοσελίδες μπορούν να αναγνωριστούν με ακρίβεια 90% περισσότερο από τις κανονικές ιστοσελίδες του παγκόσμιου ιστού. Προκειμένου να το αντιμετωπίσουμε αυτό, έχουμε αναπτύξει το ALPaCA το οποίο αρχικά προτάθηκε από τους Giovanni Cherubin, Jamie Hayes, Marc Juarez και σημαίνει “Application Layer Padding Concerns Adversaries”. Το ALPaCA είναι ένας μηχανισμός άμυνας από την πλευρά του εξυπηρετητή το οποίο αποκρύπτει το πραγματικό μέγεθος του περιεχομένου μιας ιστοσελίδας, αλλάζοντας τα μεγέθη των διαφορετικών στοιχείων της που αποστέλλονται στον πελάτη ή προσθέτοντας νέα εικονικά στοιχεία. Ο κώδικας της πτυχιακής βρίσκεται στον ακόλουθο σύνδεσμο: https://github.com/LefterisDs/ngx_http_alpaca_moduleWebsite Fingerprinting is an attempt to identify a website, visited in anonymized and encrypted network traffic. Whilst this type of attack might not be very effective on the wide web, on the tor network, the websites can be distinguished with an accuracy of 90% more than regular sites. To deal with this, we have developed ALPaCA, which was originally proposed by Giovanni Cherubin, Jamie Hayes, Marc Juarez, and stands for “Application Layer Padding Concerns Adversaries”. This is a server-side defense mechanism that obscures the real content size of a website by changing the sizes of different objects sent to the client or by adding fake new ones. The code of this thesis can be found at the following link: https://github.com/LefterisDs/ngx_http_alpaca_modul

IRIS: a DSS for multiple criteria sorting problems

This paper presents Interactive Robustness analysis and parameters' Inference for multicriteria Sorting problems (IRIS), a Decision Support System (DSS) designed to sort actions (projects, candidates, alternatives, clients, etc.) described by their performances on multiple criteria into an ordered set of categories defined a priori. It is based on the ELECTRE TRI sorting method, but does not require the decision maker (DM) to indicate precise values for all of the method's parameters. More realistically, the software expects the DM to indicate some constraints that these parameters should respect, including sorting examples that the program should reproduce. If the constraints indicated by the DM do not contradict each other (i.e. form a consistent system), then IRIS infers a combination of parameter values that reproduces all the sorting examples, indicating also the range of possible assignments of actions to categories that would be possible without violating any of the stated constraints. If the constraints are contradictory (i.e. form an inconsistent system), then IRIS suggests a combination of parameter values that minimizes an error function and identifies alternative ways to restore the system's consistency by removing some constraints. Copyright © 2005 John Wiley & Sons, Ltd

Monitoring credit risk in the social economy sector by means of a binary goal programming model

The final publication is available at Springer via http://dx.doi.org/10.1007/s11628-012-0173-7Monitoring the credit risk of firms in the social economy sector presents a considerable challenge, since it is difficult to calculate ratings with traditional methods such as logit or discriminant analysis, due to the relatively small number of firms in the sector and the low default rate among cooperatives. This paper intro- duces a goal programming model to overcome such constraints and to successfully manage credit risk using economic and financial information, as well as expert advice. After introducing the model, its application to a set of Spanish cooperative societies is described.García García, F.; Guijarro Martínez, F.; Moya Clemente, I. (2013). Monitoring credit risk in the social economy sector by means of a binary goal programming model. Service Business. 7(3):483-495. doi:10.1007/s11628-012-0173-7S48349573Alfares H, Duffuaa S (2009) Assigning cardinal weights in multi-criteria decision making based on ordinal rankings. J Multicriteria Decis Anal 15:125–133Altman EI (1968) Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. J Financ 23:589–609Altman EI, Hadelman RG, Narayanan P (1977) Zeta analysis: a new model to identify bankruptcy risk of corporations. J Bank Financ 1:29–54Andenmatten A (1995) Evaluation du risque de défaillance des emetteurs d’obligations: Une approche par l’aide multicritère á la décision. Presses Polytechniques et Univertitaires Romandes, LausanneBeaver WH (1966) Financial ratios as predictors of failure. J Account Res 4:71–111Boritz JE, Kennedey DB (1995) Effectiveness of neural network types for prediction of business failure. Expert Syst Appl 9:503–512Bottomley P, Doyle J, Green R (2000) Testing the reliability of weight elicitation methods: direct rating versus point allocation. J Mark Res 37:508–513Casey M, McGee V, Stinkey C (1986) Discriminating between reorganized and liquidated firms in bankruptcy. Account Rev 61:249–262Cruz S, Gonzalez T, Perez C (2010) Marketing capabilities, stakeholders’ satisfaction, and performance. Serv Bus 4:209–223Díaz M, Marcuello C (2010) Impacto económico de las cooperativas. La generación de empleo en las sociedades cooperativas y su relación con el PIB. CIRIEC 67:23–44Dimitras AI, Zopounidis C, Hurson C (1995) A multicriteria decision aid method for the assessment of business failure risk. Found Comput Decis Sci 20:99–112Dimitras AI, Slowinski R, Susmaga R, Zopounidis C (1999) Business failure prediction using rough sets. Eur J Oper Res 114:263–280Elmer PJ, Borowski DM (1988) An expert system approach to financial analysis: the case of S&L bankruptcy. Financ Manage 17:66–76Frydman H, Altman EI, Kao DL (1985) Introducing recursive partitioning for financial classification: the case of financial distress. J Financ 40:269–291García F, Guijarro F, Moya I (2008) La valoración de empresas agroalimentarias: una extensión de los modelos factoriales. Rev Estud Agro-Soc 217:155–181Gupta MC, Huefner RJ (1972) A cluster analysis study of financial ratios and industry characteristics. J Account Res 10:77–95Jensen RE (1971) A cluster analysis study of financial performance of selected firms. Account Rev 16:35–56Juliá J (2011) Social economy: a responsible people-oriented economy. Serv Bus 5:173–175Keasey K, Mcguinnes P, Short H (1990) Multilogit approach to predicting corporate failure: further analysis and the issue of signal consistency. Omega-Int J Manage S 18:85–94Li H, Adeli H, Sun J, Han JG (2011) Hybridizing principles of TOPSIS with case-based reasoning for business failure prediction. Comput Oper Res 38:409–419Luoma M, Laitinen EK (1991) Survival analysis as a tool for firm failure prediction. Omega-Int J Manage S 19:673–678March I, Yagüe RM (2009) Desempeño en empresas de economía social. Un modelo para su medición. CIRIEC 64:105–131Martin D (1977) Early warning of bank failure: a logit regression approach. J Bank Financ 1:249–276Mateos A, Marín M, Marí S, Seguí E (2011) Los modelos de predicción del fracaso empresarial y su aplicabilidad en cooperativas agrarias. CIRIEC 70:179–208McKee T (2000) Developing a bankruptcy prediction model via rough sets theory. Int J Intell Syst Account Finan Manage 9:159–173Messier WF, Hansen JV (1988) Inducing rules for expert system development: an example using default and bankruptcy data. Manage Sci 34:1403–1415Ohlson JA (1980) Financial ratios and the probabilistic prediction of bankruptcy. J Account Res 18:109–131Peel MJ (1987) Timeliness of private firm reports predicting corporate failure. Invest Anal J 83:23–27Saaty TL (1980) The analytic hierarchy process. McGraw-Hill, New YorkScapens RW, Ryan RJ, Flecher L (1981) Explaining corporate failure: a catastrophe theory approach. J Bus Finan Account 8:1–26Skogsvik R (1990) Current cost accounting ratios as predictors of business failures: the Swedish case. J Bus Finan Account 17:137–160Slowinski R, Zopounidis C (1995) Application of the rough set approach to evaluation of bankruptcy risk. Int J Intell Syst Account Finan Manage 4:24–41Vranas AS (1992) The significance of financial characteristics in predicting business failure: an analysis in the Greek context. Found Comput Decis Sci 17:257–275Westgaard S, Wijst N (2001) Default probabilities in a corporate bank portfolio: a logistic model approach. Eur J Oper Res 135:338–349Wilson RL, Sharda R (1994) Bankruptcy prediction using neuronal networks. Decis Support Syst 11:545–557Zavgren CV (1985) Assessing the vulnerability to failure of American industrial firms. A logistic analysis. J Bus Financ Account 12:19–45Zmijewski M (1984) Methodological issues related to the estimation of financial distress prediction models. Studies on Current Econometric Issues in Accounting Research. J Account Res 22:59–86Zopounidis C, Doumpos M (2002) Multicriteria classification and sorting methods: a literature review. Eur J Oper Res 138:229–24

Linkages between financial development, financial instability, financial liberalisation and economic growth in Africa

In the aftermath of the 2008 global financial crisis, the implications of financial liberalisation for stability and economic growth has come under increased scrutiny. One strand of literature posits a positive relationship between financial liberalisation and economic growth and development. However, others emphasise the link between financial liberalisation is intrinsically associated with financial instability which may be harmful to economic growth and development. This study assesses linkages between financial instability, financial liberalisation, financial development and economic growth in 41 African countries for the period 1985-2010. The results suggest that financial development and financial liberalisation have positive effects on financial instability. The findings also reveal that economic growth reduces financial instability and the magnitude of reduction is higher in the pre-liberalisation period compared to post-liberalisation period