Abstract

Bu çalışmanın amacı, 1992-1999 döneminde Türkiye hisse senedi piyasasındaki oynaklığı sektör düzeyinde incelemektir. Sektörler birbirinden farklı özellikler gösterdiğinden, her bir sektörün oynaklığı ayrı ayrı analiz edilmiştir. Firmalar, İMKB’nin sektör sınıflandırmasına uygun olarak 15 sektörde toplanmıştır. Her bir sektör için oynaklık serileri oluşturulmuştur. Elde edilen bulgulara göre, Kimya, Bankacılık ve Metal eşya, makina gibi büyük endüstürilerde oynaklık eğilimi daha fazladır. Örneklemizdeki büyük sectörlerden ikisinde, Kimya ve Bankacılık sektörlerinde endüstri betaları 1.0’den büyük, diğer sektörlerin betaları ise önemli ölçüde düşük bulunmuştur. Bu çalışmada oynaklık serilerinin zaman serileri analizleri de yapılmıştır. Bulgularımız, Gıda, Yatırım ortaklıkları, Demir-Çelik ve Sigorta sektörlerinin pozitif trend, Metal eşya, makina sektörünün ise negatif trende sahip olduğunu göstermiştir. İmalat sektörünün oynaklık serilerinin devresel hareketleri de analiz edilmiştir. Bu sektöre ait oynaklık serilerinin , sektörün gelecekteki büyüme hızını tahminleme gücüne sahip olmadığı sonucuna ulaşılmıştır

VOLATILITY IN THE TURKISH STOCK MARKET: AN INDUSTRY-LEVEL ANALYSIS

Abstract

This paper examines the volatility of Turkish stock market at the industry level over the period 19921999. Since the nature and composition of the industries are not the same, we study the volatility of each industry separately. Individual firms are aggregated into 15 industries according to the industry classification of ISE. The volatility series at the level of each industry are constructed. The results indicate that large industries, such as, Chemical, Banking, and Metal products, machinery, tend to have high-level volatility. The results also indicate that two of the large industries in our sample, Chemicals and Banking, have an industry-beta higher than 1.0. Other industries, however, have a substantially low industry beta. The time series behavior of volatility series is also analyzed. The results suggest that Food, Investment Trust, Ferrous Metals and Insurance industries exhibit significant positive trend and Metal products, machinery exhibit significant negative trend. The cyclical behavior of volatility series in industries belong to manufacture sector is also checked. The results indicate that the volatility series have no forecasting power for future output growth in that industry.

References

1. Black, F. (1976): “Studies of Stock Price Volatility Changes” Proceedings of the 1976 Meetings of the Business and Economic Statistics Section”, American Statistical Association, 177-181.
2. Bollerslev, T., R. F. Engle, and J.M. Wooldridge (1988): “A Capital Asset Pricing Model with Time Varying Covariances”, Journal of Political Economy, 96, 116-131.
3. Campbell, J.Y. (1991): “A Variance Decomposition for Stock Returns”, Economic Journal, 101, 157-179.
4. Campbell, J.Y., M. Lettau, B.G. Malkiel, and Y. Xu (2001): “Have Individual Stocks Become More Volatile? An Empirical Exploration of Idiosyncratic Risk”, Journal of Finance, 56(1), 1-43.
5. Campbell, J.Y., A.W. Lo, and A.C. Mackinlay (1997): The Econometrics of Financial Markets, Princeton University Press, Princeton, NJ.
6. Christie, A. A. (1982): “The Stochastic Behavior of Common Stock Variances: Value, Leverage, And Interest Rate Effects”, Journal of Financial Economics, 10, 407-432.
7. Duffee, G.R. (1995): “Stock Returns and Volatility: A Firm-Level Analysis”, Journal of Financial Economics, 37, 399-420.
8. Durukan, B. (1999): “Istanbul Menkul Kıymetler Borsasında Makroekonomik Değişkenlerin Hisse Senedi Fiyatlarına Etkisi“, IMKB Dergisi, 1, 69-87.

9. Güneş, H. and B. Saltoğlu (1998): “IMKB Getiri Volatilitesinin Makroekonomik Konjonkür Bağlamında irdelenmesi”, IMKB Dergisi.
10. Engle, Robert F. and G.G.J. Lee (1993): “Long run Volatility Forecasting for Individual Stocks in One factor Model”, unpublished paper, University of California at San Diego.
11. Harris, R.D. and C.C. Kucukozmen (2001): “The empirical distribution of stock returns: evidence from an emerging European market.” Applied Economics Letters, 8, 367-371.
12. Heston, S. L. and K.G. Rouwenhorst (1994): “Does Industrial Structure Explain the Benefits of International Diversification?” Journal of Financial Economics, 36, 3-27.
13. Kıymaz, H. (1997): “The Long Run Performance of Turkish Industrial IPOs: 1990-1995” ISE Review, 1, 26-43.
14. Kıymaz, H. (2001): “The effects of stock market rumors on stock prices: evidence from an emerging market.” Journal of Multinational Financial Management, 11, 105-115.
15. Kıymaz, H. (2002): “The stock market rumors and stock prices: a test of price pressure and size effect in an emerging market” Applied Financial Economics, 12, 469-474.
16. Kıymaz, H. (2003): “Estimation of foreign exchange exposure: an emerging market application” Journal of Multinational Financial Management, 13, 71-84.
17. Leahy, J.V., T.M. Whited (1996): “The Effect of Uncertainty on Investment: Some Stylize Facts”, Journal of Money, Credit and Banking, 28, 64-83.
18. Loungani, P., M.Rush and W. Tave (1990): “Stock Market Dispersion and Unemployment” Journal of Monetary Economics, 25, 367-388.
19. Newey, W. and K. D. West (1994): “Automatic Lag Selection in Covariance Matrix Estimation”, Review of Economic Studies, 61, 631-654.
20. Roll, R. (1992): “Industrial Structure and the Comparative Behavior of International Stock Market Indices”, Journal of Finance, 47, 3-42.
21. Schwert, G.W. (1989): “Why Does Stock Market Volatility Change Over Time?”, Journal of Finance, 44, 1115-1153.
22. Yilmaz, M. K. (1997): “Stock market volatility and its term structure: empirical evidence from the Turkish market”, ISE Review, 1, 43-69.