ENDÜSTRİ SEKTÖRLERİNİN EKONOFİZİK AÇIDAN KÜMELENME ANALİZİ: TÜRKİYE UYGULAMASI

Öz

Bu çalışma ekonofizik bakış açısıyla Türkiye'deki endüstriyel sektörlerin banka kredilerine göre kümelenmesini analiz etmektedir. 2010/6- 2016/06 dönemleri arasında banka kredisi kullanımı gerçekleştiren sektörlerin davranışlarını, ağ teorisine dayalı olarak benzer profilli olan endüstri gruplarını tanımlayan kümeleme metodolojisini kullanarak incelemektedir. Bu çalışmanın temel amacı bankacılık sektörünün farklı endüstriler üzerinde nasıl etki yarattığını ve gelişmiş sektörler kurduğunu anlamaya çalışmaktır. Sektör sınıflandırmasını bir karşılaştırma unsuru olarak ele alıp, farklı yöntemlerin bu sınıflandırmayı nasıl etkilediğini değerlendirirmek amacıyla iki kümeleme yönteminden yararlanılmıştır: K-Ortalamalar Kümelenme Yöntemi ve Bulanık C-Ortalamalar Yöntemi. 

Anahtar Kelimeler

• Ekonofizik,Bankacılık Sektörü,Kümeleme Analizi,K-Ortalamalar,Kümelenme Yöntemi

A CLUSTERING ANALYSIS OF TURKISH INDUSTRIAL SECTORS UNDER PERSPECTIVE OF ECONOPHYSICS

Öz

This paper analyzes industrial sectors in Turkey through clustering sectors according to bank credits under perspective of econophysics. We study the behavior of the industries which take bank credits during the period of 2010/06–2016/06 based on network theory, using clustering methodology that identifies groups of industry with similar profiles. The fundamental aim of industry analysis is to figure out how the banking sector of Turkey makes impacts on different industries and establish enhanced sectors. By taking the sector classification as a benchmark partition, we evaluate how the different methods affect this classification. We utilized from two clustering methods: K-means Clustering and Fuzzy C- means Clustering. 

Anahtar Kelimeler

• Banking sector,Cluster analysis,Econophysics,K-means clustering

Kaynakça

1. A. Dionisio, R. Menezes, D. Mendes, An Econophysics approach to analyze uncertainty in financial markets: An application to the Portuguese stock market, The European Physical Journal B 50 (1) (2005) 161-164.
2. Bachelier, L., (1900) The theory of Speculation, Gauthier-Villars
3. Brida, J. G., ve Risso, W. A. (2010). Dynamics and structure of the 30 largest North American companies. Comput Econ. 35, 85–99.
4. Bowles, S., ve Gintis, H. (1975). The problem with human capital theory- a marxian critique. The American Economic Review. 65 (2), 74–82.
5. Carnot, Sadi; Thurston, Robert Henry (editor and translator) (1890).
6. Derman, E. (2002) The Perception of Time, Risk and Return During Periods of Speculation.
7. Einstein, A. (1956) “Investigations on the Brownian Movement”, New York, Dover.
8. Faggiolo, G., Reyes, J., ve Schiavo, S. (2010). The evolution of the world trade web: a weighted-network analysis. Journal of Evolutionary Economics. 20 (4), 479-514.

9. Fricke, D., ve Lux, T. (2014). Core-periphery structure in the overnight money market: Evidence from the e-mid trading platform. Computational Economics. 45, 359-395.
10. Gallegati, M. & Keen, S. & Lux, T. & Ormerod, P. (2006). Worrying trends in econophysics, Physica A 370, 1–6.
11. Georgescu-Roegen, N.: The entropy law and the economic process. Cambridge, Mass. Harvard Univ. Press, 1974.
12. Goodwin, R. M. (1947). Dynamical coupling with especial reference to markets having production lags. Econometrica. 15 (3), 181-204.
13. Grabner, C., Heinrich, T., ve Kudic, M. (2016). Structuration processes in complex dynamic systems- an overview and reassessment. https://mpra.ub.uni-muenchen.de/69095/ Accessed: 30 September 2016.
14. Keen, S. (2003). Standing on the toes of pygmies: why econophysics must be careful of the economic foundations on which it builds, Physica A. 324, 108-116.
15. Mantegna, R.N. , Stanley, H.E. (2000), Introduction to Econophysics: Correlations and Complexity in Finance, Cambridge University Press.
16. Merton, R., Scholes B., (1972) The Valuation of Options Contracts and a Test of Market Efficiency, Journal of Finance, Vol. 27, No:2
17. Mimkes, J. (2006) Econophysics and Sociophysics: Trends and Perspectives.
18. Rousseeuw, P. J. (1987). Silhouettes: A graphical aid to the interpretation and validation of cluster analysis. Computational and Applied Mathematics. 20, 53–65.
19. Schinckus, Christophe. "Economic uncertainty and econophysics."Physica A: Statistical Mechanics and its Applications 388.20 (2009): 4415-4423.
20. Simon, H. A. (1953). Notes on the observation and measurement of political power. The Journal of Politics. 15 (4), 500-516.
21. Spanulescu, I., ve Gheorghiu, A. (2016). An econophysics approach and model for the Keynes’s multiplier of investments. Hyperion International Journal of Econophysics & New Economy. 9 (1), 7-18.
22. Stanley, H. & Amaral, L. & Gopikrishnan, P. & Lee, Y. & Liu, Y. (1999). Econophysics: Can physicists contribute to the science of economics? Physica A 269, 156–169.
23. The New Palgrave Dictionary of Economics: Econophysics. (2008). http://www.dictionaryofeconomics.com/ Accessed : 16 September 2016.
24. Velmurugan, T. (2014). Performance based analysis between K-Means and Fuzzy C-Means clustering algorithms for connection oriented telecommunication data. Applied Soft Computing. 19, 134-146.