Adaptif Piyasalar Teorisi: BIST-30 Endeksinin Etkinlik Analizi

Yıl 2025, Cilt: 12 Sayı: 2, 614 - 627, 29.12.2025

Ahmet Şenol , İdil Koç

https://doi.org/10.47097/piar.1804826

Öz

Bu çalışma, adaptif piyasalar hipotezi çerçevesinde Borsa İstanbul (BİST) 30 endeksinin etkinlik düzeyini incelemektedir. Bu doğrultuda, araştırmada zayıf formada etkinliğin geçerliliğini sınamak amacıyla doğrusal ve doğrusal olmayan yöntemlerden oluşan kapsamlı bir test seti uygulanmıştır. Elde edilen sonuçlar temel bileşen analizi (PCA) yöntemi ile birleştirilerek, hisse senedi piyasalarının tarihsel etkinlik eğilimini gösteren, genel anlamda piyasadaki etkinlik düzeyini yansıtan bir piyasa etkinlik endeksi oluşturulmuştur. Ampirik bulgular adaptif piyasa hipotezinin öngörüleri ile tutarlı bir şekilde, piyasada etkinliklerin zaman içinde dalgalı bir seyir izlediğini göstermektedir. Özellikle endeks, finansal krizler, jeopolitik belirsizlik, siyasi stres dönemlerinde etkinlikten uzaklaşmaktadır. Ayrıca bu sapmalar hem yurt içi hem de küresel olaylarda benzer şekilde ortaya çıkmakta, piyasa etkinliğinin çevresel koşullara duyarlılığını göstermektedir.

Anahtar Kelimeler

Adaptif Piyasalar Teorisi , Zayıf Formda Etkinlik , Etkinlik Endeksi , BİST-30 , Temel Bileşenler Analizi

Adaptive Market Theory: Efficiency Analysis of the BIST-30 Index

Öz

This study investigates the adaptive markets hypothesis for the BIST-30 index. To this end, a set of fifteen linear and nonlinear statistical tests were applied to examine whether the index exhibits weak-form efficiency. The results of these tests were then integrated through the principal component analysis method, with the aim of constructing a composite market efficiency index that captures both the historical trajectory of efficiency in the stock market and the overall state of market efficiency. The empirical findings suggest that, as broadly consistent with the adaptive markets hypothesis, market efficiency fluctuates significantly over time. In particular, the index tends to deviate from efficiency during periods of financial, geopolitical and political stress time. Moreover, such deviations are evident not only in the context of domestic shocks but also in response to global events, highlighting the sensitivity of market efficiency to both local and international volatile dynamics.

Anahtar Kelimeler

Adaptive Market Theory , Weak form Efficiency , Efficiency Index , BIST-30 , Principle Component Analysis

Kaynakça

• Başçı, E. ve Kara, H. (2011). Finansal istikrar ve para politikası. İktisat İşletme ve Finans, 26(302), 9-25.
• Box, G. E., & Pierce, D. A. (1970). Distribution of residual autocorrelations in autoregressive-integrated moving average time series models. Journal of the American statistical Association, 65(332), 1509-1526.
• Boya, C. M. (2019). From efficient markets to adaptive markets: Evidence from the French stock exchange. Research in International Business and Finance, 49, 156-165.
• Brock, W. A., Dechert, W. D., Schieinkman, J. A., (1987). A test for independence based on correlation dimension, SSRI Working Paper No. 8702, Department of Economics, University of Wisconsin, Madison, WI.
• Bucherie, A., Hultquist, C., Adamo, S., Neely, C., Ayala, F., Bazo, J., & Kruczkiewicz, A. (2022). A comparison of social vulnerability indices specific to flooding in Ecuador: Principal component analysis (PCA) and expert knowledge. International Journal of Disaster Risk Reduction, 73, 1-21.
• Choi, I. (1999). Testing the random walk hypothesis for real exchange rates. Journal of Applied Econometrics, 14(3), 293-308.
• Chordia, T., Roll, R., & Subrahmanyam, A. (2008). Liquidity and market efficiency. Journal of financial Economics, 87(2), 249-268.
• Chow, K. V., & Denning, K. C. (1993). A simple multiple variance ratio test. Journal of econometrics, 58(3), 385-401.
• Çolak, M. S., Güney, I. E., Şenol, A., & Yılmaz, M. H. (2019). Monitoring and forecasting cyclical dynamics in bank credits: Evidence from Turkish banking sector. Working Papers 1929, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
• Erer, D., Erer, E., & Güngör, S. (2023). The aggregate and sectoral time-varying market efficiency during crisis periods in Turkey: a comparative analysis with COVID-19 outbreak and the global financial crisis. Financial Innovation, 9(1), 80.
• Escanciano, J. C., & Velasco, C. (2006). Generalized spectral tests for the martingale difference hypothesis. Journal of Econometrics, 134(1), 151-185.
• Escanciano, J. C., & Lobato, I. N. (2009). An automatic portmanteau test for serial correlation. Journal of Econometrics, 151(2), 140-149.
• Fama, E. F. (1965). The behavior of stock-market prices. The journal of Business, 38(1), 34-105.
• Filmer, D., & Pritchett, L. H. (2001). Estimating wealth effects without expenditure data—or tears: an application to educational enrollments in states of India. Demography, 38(1), 115-132.
• Gaio, L. E., Stefanelli, N. O., Júnior, T. P., Bonacim, C. A. G., & Gatsios, R. C. (2022). The impact of the Russia-Ukraine conflict on market efficiency: Evidence for the developed stock market. Finance Research Letters, 50.
• Gupta, R., & Yang, J. (2011). Testing weak form efficiency in the Indian capital market. International Research Journal of Finance and Economics, 75, 108-119.
• Güllüpunar, M. D. (2023). Kamuoyu araştırmaları ve 2023 seçim sonuçları bağlamında karşılaştırmalı bir analiz. Gümüşhane Üniversitesi İletişim Fakültesi Elektronik Dergisi, 11(2), 1261-1285.
• Hiremath, G. S., & Narayan, S. (2016). Testing the adaptive market hypothesis and its determinants for the Indian stock markets. Finance Research Letters, 19, 173-180.
• Kaiser, H. F. (1974). An index of factorial simplicity. Psychometrika, 39(1), 31–36. https://doi.org/10.1007/BF02291575
• Kara, H. (2012). Küresel kriz sonrası para politikası. TCMB Çalışma Tebliği, 12(17), 1-25.
• Kim, J. H. (2006). Wild bootstrapping variance ratio tests. Economics letters, 92(1), 38-43.
• Kim, J. H., & Shamsuddin, A. (2008). Are Asian stock markets efficient? Evidence from new multiple variance ratio tests. Journal of Empirical Finance, 15(3), 518-532.
• Kim, J. H., Shamsuddin, A., & Lim, K. P. (2011). Stock return predictability and the adaptive markets hypothesis: Evidence from century-long US data. Journal of empirical finance, 18(5), 868-879.
• Kurita, T. (2021). Principal component analysis (PCA). In Computer vision: a reference guide (pp. 1013-1016). Cham: Springer International Publishing.
• Laopodis, N. T. (2009). Fiscal policy and stock market efficiency: Evidence for the United States. The quarterly Review of Economics and finance, 49(2), 633-650.
• Lim, K. P. (2007). Ranking market efficiency for stock markets: A nonlinear perspective. Physica A, 376, 445-454.
• Lim, K. P., & Brooks, R. (2011). The evolution of stock market efficiency over time: A survey of the empirical literature. Journal of economic surveys, 25(1), 69-108.
• Lim, K. P., Luo, W., & Kim, J. H. (2013). Are US stock index returns predictable? Evidence from automatic autocorrelation-based tests. Applied Economics, 45(8), 953-962.
• Ljung, G. M., & Box, G. E. (1978). On a measure of lack of fit in time series models. Biometrika, 65(2), 297-303.
• Lo, A. W., & MacKinlay, A. C. (1988). Stock market prices do not follow random walks: Evidence from a simple specification test. The review of financial studies, 1(1), 41-66.
• Lo, A. W. (2004). The adaptive markets hypothesis: Market efficiency from an evolutionary perspective. Journal of Portfolio Management, Forthcoming. https://ssrn.com/abstract=602222
• Marois, T. (2011). Emerging market bank rescues in an era of finance-led neoliberalism: A comparison of Mexico and Turkey. Review of International Political Economy, 18(2), 168-196.
• McLeod, A. I., & Li, W. K. (1983). Diagnostic checking ARMA time series models using squared‐residual autocorrelations. Journal of Time Series Analysis, 4(4), 269-273.
• Niemczak, K., & Smith, G. (2013). Middle Eastern stock markets: absolute, evolving and relative efficiency. Applied Financial Economics, 23(3), 181-198.
• Noda, A. (2016). A test of the adaptive market hypothesis using a time-varying AR model in Japan. Finance Research Letters, 17, 66-71.
• Opong, K. K., Mulholland, G., Fox, A. F., & Farahmand, K. (1999). The behaviour of some UK equity indices: An application of Hurst and BDS tests. Journal of Empirical Finance, 6(3), 267-282.
• Ozkan, O. (2021). Impact of COVID-19 on stock market efficiency: Evidence from developed countries. Research in international business and finance, 58, 101445.
• Rönkkö, M., Holmi, J., Niskanen, M., & Mättö, M. (2024). The adaptive markets hypothesis: Insights into small stock market efficiency. Applied Economics, 56(25), 3048-3062.
• Sensoy, A., & Tabak, B. M. (2015). Time-varying long term memory in the European Union stock markets. Physica A, 436, 147-158.
• Shi, H. L., Jiang, Z. Q., & Zhou, W. X. (2017). Time-varying return predictability in the Chinese stock market. Reports in Advances of Physical Sciences, 1(01).
• Simon, H. A. (1955). A behavioral model of rational choice. The Quarterly Journal of Economics, Vol. 69, No. 1, 99-118.
• Smith, G. (2012). The changing and relative efficiency of European emerging stock markets. The European Journal of Finance, 18(8), 689-708.
• Urquhart, A., & Hudson, R. (2013). Efficient or adaptive markets? Evidence from major stock markets using very long run historic data. International Review of Financial Analysis, 28, 130-142.
• Urquhart, A., Gebka, B., & Hudson, R. (2015). How exactly do markets adapt? Evidence from the moving average rule in three developed markets. Journal of International Financial Markets, Institutions and Money, 38, 127-147.
• Urquhart, A., & McGroarty, F. (2016). Are stock markets really efficient? Evidence of the adaptive market hypothesis. International Review of Financial Analysis, 47, 39-49.
• Verheyden, T., De Moor, L., & Van den Bossche, F. (2015). Towards a new framework on efficient markets. Research in International Business and Finance, 34, 294-308.
• Vyas, S., & Kumaranayake, L. (2006). Constructing socio-economic status indices: how to use principal components analysis. Health policy and planning, 21(6), 459-468.
• Wald, A., & Wolfowitz, J. (1940). On a Test Whether Two Samples are from the Same Population. The Annals of Mathematical Statistics, 11(2), 147–162.
• Wright, J. H. (2000). Alternative Variance-Ratio Tests Using Ranks and Signs. Journal of Business & Economic Statistics, 18(1), 1–9.
• Worthington, A., & Higgs, H. (2006). Weak-form market efficiency in Asian emerging and developed equity markets: Comparative tests of random walk behaviour. Accounting Research Journal, 19(1), 54-63.