Financial Assessment of Banks and Financial Institutes in Stock Exchange by Means of an Enhanced Two stage DEA Model
Subject Areas : Financial Mathematics
1 - Department of Mathematics, College of Science, Arak Branch, Islamic Azad University, Arak, Iran
P. O. Box: 38135/567
Keywords:
Abstract :
[1] Ramezanian, R., A. Peymanfar, and S.B. Ebrahimi 2019 An integrated framework of genetic network programming and multi-layer perceptron neural network for prediction of daily stock return: An application in Tehran stock exchange market Applied Soft Computing 82: 105551.
[2] Jalilvand, A., M.R. Noroozabad, and J. Switzer 2018 Informed and uninformed investors in Iran: Evidence from the Tehran Stock Exchange Journal of Economics and Business 95: 47-58.
[3] Shahrestani, P. and M. Rafei 2020 The impact of oil price shocks on Tehran Stock Exchange returns: Application of the Markov switching vector autoregressive models Resources Policy 65: 101579.
[4] Khoshroo, A., M. Izadikhah, and A. Emrouznejad 2018 Improving energy efficiency considering reduction of CO2 emission of turnip production: A novel data envelopment analysis model with undesirable output approach Journal of Cleaner Production 187: 605-615.
[5] Tone, K., M. Toloo, and M. Izadikhah 2020 A modified slacks-based measure of efficiency in data envelopment analysis European Journal of Operational Research 287: 560-571.
[6] Sherman, H.D. and F. Gold 1985 Bank branch operating efficiency Journal of Banking and Finance 9: 297-315.
[7] Ohsato, S. and M. Takahashi 2015 Management Efficiency in Japanese Regional Banks: A Network DEA Procedia - Social and Behavioral Sciences 172: 511-518.
[8] Herrera-Restrepo, O., et al. 2016 Bank branch operational performance: A robust multivariate and clustering approach Expert Systems with Applications 50: 107-119.
[9] Diallo, B. 2017 Bank efficiency and industry growth during financial crises Economic Modelling.
[10] Zhu, N., et al. 2019 Ranking Chinese commercial banks based on their expected impact on structural efficiency Omega 102049.
[11] Aliakbarpoor, Z. and M. Izadikhah 2012 Evaluation and ranking DMUs in the presence of both undesirable and ordinal factors in data envelopment analysis Int. J. Autom. Comput. 9: 609-615.
[12] Izadikhah, M. and R. Farzipoor Saen 2015 A new data envelopment analysis method for ranking decision making units: an application in industrial parks Expert Systems 32: 598-608.
[13] Charnes, A., W.W. Cooper, and E. Rhodes 1978 Measuring the efficiency of decision making units European Journal of Operational Research 2: 429-444.
[14] Izadikhah, M. and R. Farzipoor Saen 2016 Evaluating sustainability of supply chains by two-stage range directional measure in the presence of negative data Transportation Research Part D: Transport and Environment 49: 110-126.
[15] Izadikhah, M. and R. Farzipoor Saen 2016 A new preference voting method for sustainable location planning using geographic information system and data envelopment analysis Journal of Cleaner Production 137: 1347-1367.
[16] Cooper, W.W., et al. 2011 BAM: A Bounded Adjusted Measure of Efficiency for use with Bounded Additive Models Journal of Productivity Analysis 35: 85-94.
[17] Kao, C. and S.-N. Hwang 2008 Efficiency decomposition in two-stage data envelopment analysis: An application to non-life insurance companies in Taiwan European Journal of Operational Research 185: 418-429.
[18] Li, Y., et al. 2012 DEA models for extended two-stage network structures Omega 40: 611–618.
[19] Avkiran, N.K. 2015 An illustration of dynamic network DEA in commercial banking including robustness tests Omega 55: 141-150.
[20] Sánchez-González, C., J.L. Sarto, and L. Vicente 2017 The efficiency of mutual fund companies: Evidence from an innovative network SBM approach Omega 71: 114-128.
[21] Tavana, M., et al. 2018 A new dynamic range directional measure for two-stage data envelopment analysis models with negative data Computers & Industrial Engineering 115: 427-448.
[22] Yin, P., et al. 2019 A DEA-based two-stage network approach for hotel performance analysis: An internal cooperation perspective Omega In press.
[23] Avkiran, N.K. 2006 Developing foreign bank efficiency models for DEA grounded in finance theory Socio-Economic Planning Sciences 40: 275-296.
[24] Toloo, M. and A. Kresta 2014 Finding the best asset financing alternative: A DEA–WEO approach Measurement 55: 288-294.
[25] Chang, Y.-T., et al. 2016 Passenger facility charge vs. airport improvement program funds: A dynamic network DEA analysis for U.S. airport financing Transportation Research Part E: Logistics and Transportation Review 88: 76-93.
[26] Esfandiar, M., M. Saremi, and H. Jahangiri Nia 2018 Assessment of the efficiency of banks accepted in Tehran Stock Exchange using the data envelopment analysis technique %J Advances in Mathematical Finance and Applications 3: 1-11.
[27] Izadikhah, M. 2018 Improving the Banks Shareholder Long Term Values by Using Data Envelopment Analysis Model %J Advances in Mathematical Finance and Applications 3: 27-41.
[28] Goyal, J., et al. 2019 Efficiency and technology gaps in Indian banking sector: Application of meta-frontier directional distance function DEA approach The Journal of Finance and Data Science 5: 156-172.
[29] Peykani, P., et al. 2019 Fuzzy Data Envelopment Analysis Approach for Ranking of Stocks with an Application to Tehran Stock Exchange %J Advances in Mathematical Finance and Applications 4: 31-43.
[30] Wasiaturrahma, et al. 2020 Financial performance of rural banks in Indonesia: A two-stage DEA approach Heliyon 6: e04390.
[31] Mohsin, M., et al. 2020 Developing Low Carbon Finance Index: Evidence From Developed and Developing Economies Finance Research Letters 101520.
[32] Henriques, I.C., et al. 2020 Two-stage DEA in banks: Terminological controversies and future directions Expert Systems with Applications 161: 113632.
[33] Shuai, S. and Z. Fan 2020 Modeling the role of environmental regulations in regional green economy efficiency of China: Empirical evidence from super efficiency DEA-Tobit model Journal of Environmental Management 261: 110227.
[34] Li, H., X. Zhu, and J. Chen 2020 Total factor waste gas treatment efficiency of China’s iron and steel enterprises and its influencing factors: An empirical analysis based on the four-stage SBM-DEA model Ecological Indicators 119: 106812.
[35] Wanke, P., et al. 2020 Dynamic network DEA and SFA models for accounting and financial indicators with an analysis of super-efficiency in stochastic frontiers: An efficiency comparison in OECD banking International Review of Economics & Finance 69: 456-468.
[36] Cooper, W., K. Park, and J. Pastor 1999 RAM: A Range Adjusted Measure of Inefficiency for Use with Additive Models, and Relations to Other Models and Measures in DEA Journal of Productivity Analysis 11: 5-42.
[37] Pastor, J.T., et al. 2015 An enhanced BAM for unbounded or partially bounded CRS additive models Omega 56: 16-24.
[38] Rashidi, K. and R. Farzipoor Saen 2015 Measuring eco-efficiency based on green indicators and potentials in energy saving and undesirable output abatement Energy Economics 50: 18-26.
[39] Haghighi, H.Z. and M. Rostamy-Malkhalifeh 2017 A bounded adjusted measure of efficiency for evaluating environmental performance International Journal of Environment and Waste Management 19: 148-163.
[40] Qin, Q., et al. 2018 Unified energy efficiency in China's coastal areas: A virtual frontier-based global bounded adjusted measure Journal of Cleaner Production 186: 229-240.
[41] Ebrahimnejad, A., et al. 2014 A three-stage Data Envelopment Analysis model with application to banking industry Measurement 49: 308-319.
[42] Kleindorfer, P.R., H.C. Kunreuther, and P.J.H. Schoemaker 1993 Decision Sciences: An Integrative Perspective New York: Cambridge University Press.
[43] Saaty, T.L. 2006 Rank from comparisons and from ratings in the analytic hierarchy/network processes European Journal of Operational Research 168: 557-570.
[44] Jahangoshai Rezaee, M., M. Jozmaleki, and M. Valipour 2018 Integrating dynamic fuzzy C-means, data envelopment analysis and artificial neural network to online prediction performance of companies in stock exchange Physica A: Statistical Mechanics and its Applications 489: 78-93.
[45] Rezaie, K., et al. 2013 Efficiency appraisal and ranking of decision-making units using data envelopment analysis in fuzzy environment: a case study of Tehran stock exchange Neural Computing and Applications 23: 1-17.
[46] Mohtashami, A. and B.M. Ghiasvand 2020 Z-ERM DEA integrated approach for evaluation of banks & financial institutes in stock exchange Expert Systems with Applications 147: 113218.
[47] Izadikhah, M., Khoshroo, A., Energy management in crop production using a novel Fuzzy Data Envelopment Analysis model, RAIRO - Operations Research, 2017, 52 (2), P. 595 – 617, Doi: 10.1051/ro/2017082
[48] Sudarsanam, P.S. and R.J. Taffler 1995 Financial ratio proportionality and inter-temporal stability: An empirical analysis Journal of Banking & Finance 19: 45-60.
[49] Izadikhah, M., Using goal programming method to solve DEA problems with value judgments, Yugoslav Journal of Operations Research, 2016, 24 (2), P. 267 – 282, Doi: 10.2298/YJOR121221015I
[50] Lewellen, J. 2004 Predicting returns with financial ratios Journal of Financial Economics 74: 209-235.
[51] Dibachi, H., Behzadi. MH, Izadikhah, M., Stochastic Modified MAJ Model for Measuring the Efficiency and Ranking of DMUs, Indian Journal of Science and Technology, 2015, 8 (8), P. 549–555, Doi: 10.17485/ijst/2015/v8iS8/71505
[52] Arnold, T., et al. 2019 Linear Smoothers. A Computational Approach to Statistical Learning London, United Kingdom: Taylor & Francis Ltd.