EXAMINING RELATIONSHIP BETWEEN COMPOSITE LEADING INDICATORS AND BORSA ISTANBUL SECTOR INDICES

Year 2017, , 860 - 866, 30.06.2017

Sinem Eyuboglu Kemal Eyuboglu

https://doi.org/10.17261/Pressacademia.2017.666

Abstract

The prediction of fluctuations in economic activity
has become even more important, especially after the crises experienced in
recent years. In order to make such a prediction, economic and financial
indicators are needed. The Composite Leading Indicators (BONC) published by
Central Bank of the Republic of Turkey is useful in predicting the
macroeconomic contraction or expansion.  In this study, it is tested whether there
is a relationship between Composite Leading Indicators Index and 12 Borsa
Istanbul sector indices returns.  Unit root test results show that sector
indices are stationary at the first differences and the BONC is at level.  Thus long term relationship between each
sector indices and the BONC is examined by Boundary Test. The findings show that there is a long term and relationship
between BONC and all the sector indices in the study. Also it has been
determined that positive change in the BONC has a statistically significant and
positive effect on XUTEK and XGMYO in the long term. The short term
relationship is also found between all sector indices and BONC. In addition, it
is determined that increase in BONC affects all sector indices positively in
the short term. These results
indicated that investors take into account the BONC without distinguishing the
sector when investing to stocks and that BONC is an important indicator for
stock returns.

Keywords

Composite leading indicators, Borsa Istanbul, bound test, ARDL models, sector indices

References

• Demirhan, A. A., (2014). Ekonomik faaliyet için bileşik öncü göstergeler endeksi’nde (MBÖNCÜ-SÜE) yöntemsel değişim. TCMB Ekonomi Notları, s. 1-9.
• Gülhan, Ü., Kaya A., Güngör, B., (2012). Bileşik öncü göstergeler ve borsa endeksi ilişkisinin uluslararasi boyutta incelenmesine yönelik bir araştırma. Dokuz Eylül Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, vol. 27, no. 3, s. 1-27.
• Hacıhasanoğlu, E. ve Soytaş, U., (2011). Bileşik öncü göstergeler ve sektörel endeksler arasindaki ilişki. Dokuz Eylül Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, vol. 26, no. 1, s. 79-91.
• OECD System of Composite Leading Indicators (2012). http://www.oecd.org/std/leading-indicators/41629509.Pdf, 10.09.2016.
• Pesaran, M. H., (1997). The role of economic theory in modelling the long run. The Economic Journal, vol. 107 no. 440, p. 178-191.
• Pesaran, M. H., Y. Shin, Smith, R. J., (2001). Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics vol. 16, p. 289-326.
• Phillips, P. C., Perron, P., (1988). Testing for a unit root in time series regression, Biometrika, vol. 75, no. 2, p. 335-346.
• Sharma, G. D., Mahendru, M., (2010). Impact of macro-economic variables on stock prices in India. Global Journal of Management and Business Research, vol. 10, no. 7, p. 1-18.
• Toda, H. Y., Yamamoto, T., (1995). Statistical inference in vector auto regressions with possibly integrated process. Journal of Econometrics, vol. 66, p. 225-250.
• Topcu, E., (2014). Bileşik öncü göstergeler ile hisse senedi piyasalari arasindaki ilişki: Türkiye örneği. AKÜ İİBF Dergisi, vol. 16, no. 1, p. 167176.
• Topcu, M., Ünlü, U., (2013). Do investors consider composite leading indicators? Time series evidence from emerging countries. Theoretical and Applied Economics, vol. 20, no. 9, p. 51-62.