مقایسه عملکرد شبکه عصبی مصنوعی و رگرسیون لجستیک در تحلیل تشخیص شاخصq توبین

نوع مقاله : مقاله پژوهشی

نویسندگان

1 کارشناس ارشد مدیریت، گروه مدیریت، دانشکده ادبیات و علوم انسانی، دانشگاه گیلان، رشت، ایران

2 دانشیار، گروه مدیریت، دانشکده ادبیات و علوم انسانی، دانشگاه گیلان، رشت، ایران

3 استادیار، گروه مدیریت، دانشکده ادبیات و علوم انسانی، دانشگاه گیلان، رشت، ایران

چکیده

شاخص توبین یکی از شاخص های مهم در دنیای سرمایه گذاری است که بعنوان معیاری برای ارزیابی عملکرد شرکت ها جهت تصمیم گیری برای سرمایه گذاری های صحیح به کار می رود. اما در دقت نتایج مبتنی بر این شاخص، ابهاماتی وجود دارد که پژوهشگران را بر آن داشته است تا به دنبال برآورد این شاخص از روی دیگر شاخص های مالی باشند. اما شاخص توبین یک شاخص پویاست و به علت مبتنی بودن بر قیمت بازار، ممکن است در لحظه مقدار آن تغییر کند. بنابراین استفاده از روش هایی مانند رگرسیون چندگانه که تلاش می کنند مقدار دقیق متغیر وابسته را پیش بینی کنند منطقی به نظر نمی رسد. به همین دلیل این تحقیق به منظور انجام قضاوت در مورد شاخص توبین از روی دیگر شاخص های مالی، روشهای مبتنی بر پیش بینی دقیق مانند رگرسیون خطی را مورد نقد قرار داده و به جای آن استفاده از روش های تحلیل تشخیص مانند رگرسیون لجستیک و شبکه عصبی را توصیه می کند. تحلیل تشخیص، روشی برای طبقه بندی مجموعه ای از مشاهدات به یکی از دو یا چندین گروه تعیین شده است به طوریکه مشاهدات درون هر گروه بیشترین شباهت را به یکدیگر داشته باشند. لذا این پژوهش با استفاده از اطلاعات مالی 184 شرکت پذیرفته شده در بورس اوراق بهادار تهران در سالی مالی منتهی به 29 اسفند 1393 به کمک رگرسیون لجستیک و شبکه عصبی به تحلیل تشخیص شاخص توبین پرداخته و نتایج دو تکنیک را گزارش و خروجی را تحلیل و با یکدیگر مقایسه می کند.

کلیدواژه‌ها

عنوان مقاله [English]

Compare the performance of Artificial Neural Network and Logistic Regression In Discriminant Analysis Tobin's q index

نویسندگان [English]

  • zahra safdai sorkhzoo 1
  • Mohammadrahim Ramazanian 2
  • Keikhosro Yakideh 3
1 Master of Science (MSc) in Management, Department of Management, Faculty of Literature & Humanities, Guilan University, Rasht, Iran
2 Associate Professor, Department of Management, Faculty of Literature & Humanities, Guilan University, Rasht, Iran
3 Assistant Professor, Department of Management, Faculty of Literature & Humanities, Guilan University, Rasht, Iran
چکیده [English]

Tobin index is one of the most important indices in the world of investment used as a criterion for evaluating performance of the firms to decide for the right investments. However, there are some ambiguities in the accuracy of the results based on this index that have prompted researchers to pursue estimation of this index based on the other financial indices. But Tobin index is a dynamic index and as it is based on the market price, may be changed its value at once, therefore it is not logical to be predicted using methods as multiple regression that attempt to predict precise value of depent variable. this research has reviewed methods based on the exact prediction like regression to judge about Tobin index by the other financial indices and it has recommended using discriminant analysis methods such as logistic regression and artificial nervous network. Discriminant analysis is a method to categorize a set of the observations into one of two or several determined groups, so that observations within each group can have the most similarity to each other. Therefore, this research has analyzed Tobin index discrimination using financial information of 184 accepted firms by Tehran Stock Exchange in the financial year leading to 29 of Esfand in 1393 by logistic regression and artificial nervous network and it has reported results of two techniques and has compared output of the two techniques to each other.

کلیدواژه‌ها [English]

  • Artificial Neural Networks
  • Discriminant Analysis
  • Logistic Regression
  • Tobin's q Index

مراجع

] Abdollahzadeh Droodi, H. compare the information content of cash flows, cash value added, market value added earnings to total assets book value of the Company's evaluation of company performance, Master Dissertation, Islamic Azad University Neyshabur Branch,(1388).
[2] Khabbaz, M. Compare EVA and REVA in conjunction with Tobin's q, Master Dissertation Accounting, Allameh Tabatabaei University, (1386).
[3] Goodarzi, M. Yakideh, K. Mahfoozi, Gh, Portfolio optimization by combining data envelopment analysis and decision-making Hurwicz method. Journal of  New research in decision-making, (1395), 1(4): 143-156.
[4] Asghari, J. the study of the relationship between EVA and ROA in order to evaluate the performance of companies listed on the Tehran Stock Exchange, Master's Dissertation, University of Mazandaran, (1385).
[5] Jahankhani, Ali, Sajjad, A. Application of Economic Value Added Spirit fiscal decisions, Journal of Financial Research, (1374),  Issue 5 and 6, 24-43.
[6] Shariat Panahi, Majid , The effect of ownership on the performance of managers of firms listed on the Tehran Stock Exchange, Accounting PhD dissertation, University of Allameh Tabatabai.(1374).
[7] Afhami, Mary ,Tobin's q estimate the investment in terms of financial constraints among firms listed in the Tehran Stock Exchange" Master's dissertation in economics, Allameh Tabatabaei University,(1390).
[8] Salehi, A. The impact of simple correlation between Tobin and other versions q q in evaluating the performance of firms accepted in Tehran Stock Exchange, Master's dissertation financial management, Allameh Tabatabaei University, (1380).
[9] Zeraatgary, R. Application of Tobin q and comparing it with other criteria to evaluate the performance of managers in companies listed on the Tehran Stock Exchange, Master dissertation of Accountancy, University of Shira, (1386).
[10] Azizi, H., Amirteymoori., Kordrostami, S. DEA offer a new approach for supplier selection with efficient and inefficient border despite undesirable outputs and inaccurate data. Journal of  New research in decision-making,, (1395), 1(2): 139-170
[11] Lindenberg, E. B., & Ross, S. A. Tobin's q ratio and industrial organization. Journal of business, (1981), 1-32.
[12] Chung, K. H., & Pruitt, S. W. A simple approximation of Tobin's q.Financial management, (1994), 70-74.
[13] Leewillen, W. G. & Badernet, S. G,On the Measurement of Tobins Q. Journal of Financial Economics, . (1997), 44 (1), 77-122
[14] Jahanshahloo, G, Hosseinzadeh Lotfi , F. introduction to data envelopment analysis, Volume I, textbook- unpublished, Faculty of Mathematics Teacher Training University, (1385).
[15] Warner, R. M. Applied statistics: From bivariate through multivariate techniques. Sage. (2008). 
[16] Momeni, M.statistical analyzes using SPSS, Tehran: Publication of New Book, (1386).
[17] Saeedimoghadam, M., Moazzami, M., Nabavi, S. M., & Dehghani, M. Static Switch Controller Based on Artificial Neural Network in Micro-Grid Systems. Journal of Electrical Engineering & Technology, (2014), 9(6), 1822-1831.
[18] Hagan, M. T., Demuth, H. B., Beale, M. H., & De Jesús, O.Neural network design (Vol. 20). Boston: PWS publishing company, . (1996).
[19] Novo,R,P. Financial Management (translated and adapted Jahankhani, Ali; Parsaeian, Ali), Tehran: samt Publication, (1376).
[20] Maccian, S,N., Karimi, S,M., T, K,Comparison between artificial neural network model in predicting bankruptcy procedures, logistic regression and analysis of statistical discrimination, Journal of Economic Researches,(1387), Volume II, pp. 141-16.
[21] Sueyoshi, T., & Goto, M, A use of DEA–DA to measure importance of R&D expenditure in Japanese information technology industry. Decision Support Systems, (2013), 54(2), 941-952.
[22] Jensen, Michael C. Eclipse of the public corporation. Harvard Business Review (Sept.-Oct. 1989), revised (1997).
[23] Setayesh, M, Kargarfard Jahromy, M. The Effect of Product Market Competition on Capital Structure, Journal of Financial Accounting experimental preceding studies, first year, (1390), volume 1,10-32
[24] Pourheydari,omid, Houshmand Zaferanieh, R., Sarvestani, A. (1391), "The Effect of working capital strategies on profitability and value of the company", financial management, Vulom 7, pp. 55-77.
[25] Heidarpoor, F., & Malekpoor, S. Survey the Effective Factors on Tobin's Index in Tehran Stock Exchange. World Applied Sciences Journal. (2012),18(4), 575-579.
[26] Taffler, R. J, Forecasting company failure in the UK using discriminant analysis and financial ratio data. Journal of the Royal Statistical Society. Series A (General) . (1982), 342-358.
[27] Chung, K. C., Tan, S. S., & Holdsworth, D. K, Insolvency prediction model using multivariate discriminant analysis and artificial neural network for the finance industry in New Zealand. International journal of business and management. (2008), 39(1), 19-28.
[28] Hasangholipour pour, T., Miri, S.M., &  Morowatisharifabad, A. Share market using artificial neural networks, Journal of Management research in Iran, (1386), 11(55), 1-278.
[29] Wali Pur, kh, M. Safai Qhadyklayy,A. Zine El Abidine A., &  Narjes Qh,. Assessments and forecasts stable production using multi-level approach phase composition and Artificial Neural Network, Journal of Management research in Iran, (1395). 20(1),175-201.
[30] Sueyoshi, T. DEA-discriminant analysis: methodological comparison among eight discriminant analysis approaches. European Journal of Operational Research, (2006). 169(1), 247-272.
پژوهش های نوین در تصمیم گیری
دوره 3، شماره 4
اسفند 1397
صفحه 1-28

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