Test of The Weak Form Efficient Market Hypothesis for The Istanbul Stock Exchange By Markov Chains Methodology

Yıl 2005, Cilt: 14 Sayı: 1, 333 - 342, 01.06.2005

Öğr.gör.dr. Süleyman Bilgin Kılıç

Öz

In this study Markov chain methodology is used to test whether or not the daily returns of the Istanbul Stock Exchange ISE 100 index follows a martingale random walk process If the Weak Form Efficient Market Hypothesis EMH holds in any stock market stocks prices or returns follow a random walk process The random walk theory asserts that price movements will not follow any patterns or trends and that past price movements cannot be used to predict future price movements hence technical analysis is no use

Anahtar Kelimeler

-

TEST OF THE WEAK FORM EFFICIENT MARKET HYPOTHESIS FOR THE ISTANBUL STOCK EXCHANGE BY MARKOV CHAINS METHODOLOGY

Öz

Bu çalışma İstanbul Menkul Kıymetler Borsası 100 endeksine ait günlük getirilerinin
rassal yürüyüş gösterip göstermediği Markov zincirleri yöntemi ile test edilmektedir.
Eğer bir piyasada zayıf formda etkinlik hipotezi geçerli ise hisse senedi getirileri rassal
yürüyüş özelliği gösterecektir. Rassal yürüyüş teorisi hisse senedi getirilerinin tarihsel
fiyat verileriyle tahmin edilemeyeceğini öngörür. Böylece rassal yürüyüş özelliği
gösteren bir piyasada tarihsel fiyat verilerine dayanılarak gerçekleştirilen teknik analiz
yöntemleri geçersiz olacaktır.

Anahtar Kelimeler

xx

Kaynakça

• Canbaş, S., Düzakın, H. and Kılıç S.B., 2002. Fundamental and macroeconomic information for common stock valuation: The Turkish case. Yapı Kredi Economic Review, Vol. 13, No. 1.
• Driffill, J., and Sola, M., 1998. Intrinsic bubbles and regime-switching. Journal of Monetary Economics, Vol. 42 Issue 2, p357.
• Eugene F.F., 1965. Random Walks in Stock Market Prices, Financial Analysts Journal, September/October.
• Hamilton, J.D., 1989. A new approach to the economic analysis of nonstationary time series and the business cycle, Econometrica 57, 357-384.
• Kanas, A., 2003, Non-linear Forecasts of Stock Returns. Journal of Forecasting, Vol. 22 Issue 4, p 299.
• Kılıç, S.B., 1997. İMKB’de Zayıf Etkinlik ve Rassal Yürüyüş”, III. Ulusal Ekonometri ve İstatistik Sempozyumu Dergisi, 29-30 Mayıs, 1997, Uludağ Üniversitesi, Bursa.
• Los, C.A.., 1998. Nonparametric Efficiency Testing of Asian Stock Markets Using Weekly Data. Yale School of Management's Economics Research Network, p1, 30p.
• McQueen, G., and Thorley, S., 1991. Are Stock Returns Predictable? A Test Using Markov Chains. Journal of Finance, Vol. 46 Issue 1, p239.
• Mills, T.C. and Jordanov, J.V., 2003. The size effect and the random walk hypothesis: evidence from the London Stock Exchange using Markov Chains. Applied Financial Economics, Vol. 13.
• Muradoğlu, G. and K. Metin., 1997. "Efficiency of the Turkish Stock Exchange with respect to Monetary Variables : A Cointegration Analysis", European Journal of Operational Research, Vol. 90, No. 3, p 566-575.
• Neal, R.M., 1993. Probabilistic inference using Markov chain Monte Carlo methods. Technical Report CRG-TR-93-1, Department of Computer Science, University of Toronto.
• Radford M.N., 1993. Probabilistic Inference Using Markov Chain Monte Carlo Methods, Technical Report CRG-TR-93-1, Department of Computer Science, University of Toronto, 25 September 1993.
• Ryan, T.M., 1973. Security Prices As Markov Processes. Journal of Financial & Quantitative Analysis, Vol. 8 Issue 1, p17, 20p.
• Takaki H., 2004. A discrete-time model of high-frequency stock returns. Quantitative Finance, Vol. 4 Issue 2, p140.