Adaptif Piyasa Hipotezi ve Getiri Öngörülebilirliği: Borsa İstanbul İçin Bir Gizli Markov Modeli Uygulaması
Yıl 2021,
, 31 - 58, 28.04.2021
Hasan Arda Burhan
,
Eylem Acar
Öz
Adaptif piyasa hipotezi (APH) güncel finansal literatürde belirgin bir ilgi görmektedir. Bu durum APH’nin yine finansal literatürde sıklıkla araştırma konusu olan etkin piyasa hipotezine bir alternatif olarak ortaya çıkmış olması ile bağlantılıdır. Bu doğrultuda çalışmada, ilk olarak Borsa İstanbul hisse senedi piyasası BIST100 endeksi için APH, getiri öngörülebilirliğinin test edilmesi yoluyla incelenmiştir. Bu bağlamda Ocak 1988 - Aralık 2017 arası günlük kapanış fiyatı verilerine otomatik portmanteau ve genelleştirilmiş spektral (GS) testleri uygulanmıştır. Analizin devamında bu testlerin sonuçları, getiri öngörülebilirliği sağlayan dönemleri incelemek için bir gizli Markov model (GMM) uygulamasında kullanılmıştır. Sonuçlara göre Borsa İstanbul’un APH'ne güçlü bir şekilde uyum sağladığı görülmüştür. Ek olarak, GMM uygulamasının sonuçları, endeksin belirleyicileri ile ilgili olarak da periyodik öngörülebilirliği doğrulamıştır.
Kaynakça
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- Campbell, J.Y. & A.W. Lo & A.C. MacKinlay (1997), The Econometrics of Financial Markets, Princeton University Press, New Jersey, USA.
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Adaptive Market Hypothesis and Return Predictability: A Hidden Markov Model Application in Borsa Istanbul
Yıl 2021,
, 31 - 58, 28.04.2021
Hasan Arda Burhan
,
Eylem Acar
Öz
The adaptive market hypothesis (AMH) has recently attracted significant interest in the financial literature. The AMH has started to be considered an alternative to the efficient market hypothesis. In this respect, this study, first of all, examines the AMH for the BIST100 index of Turkey’s Borsa Istanbul stock exchange market by testing the return predictability. The applications are performed via automatic portmanteau and the generalized spectral (GS) tests using daily closing price data between January 1988 and December 2017. Secondly, the results of these tests are utilized for a hidden Markov model (HMM) application to examine the periods that yield return predictability. According to the results, it is observed that there is strong evidence for the validity of AMH within the scope of Borsa Istanbul’s BIST100. Additionally, the results of the HMM application confirm the periodic predictability regarding the determinants of the index.
Kaynakça
- Aga, M. & B. Kocaman (2011), “Efficient Market Hypothesis and Emerging Capital Markets: Empirical Evidence from Istanbul Stock Exchange”, Journal of Financial Markets Research, 3, 44-57.
- Al-Khazali, O. & A. Mirzaei (2017), “Stock Market Anomalies, Market Efficiency, and The Adaptive Market Hypothesis: Evidence from Islamic Stock Indices”, Journal of International Financial Markets, Institutions & Money, 51, 190-208.
- Alvarez-Ramirez, J. & E. Rodriguez & G. Espinosa-Paredes (2012), “Is The US Stock Market Becoming Weakly Efficient Over Time? Evidence from 80-Year-Long Data”, Physica A, 391, 5643-5647.
- Balaban, E. & H. Baturalp & K. Kunter (1996), Stock Market Efficiency in a Developing Economy: Evidence from Turkey, Central Bank of Republic of Turkey, Ankara, Türkiye.
- Bhar, R. & S. Hamori (2004), Hidden Markov Models: Applications to Financial Economics, Kluwer Academic Publishers, Dordrecht, Netherlands.
- Boratav, K. (2013), Türkiye İktisat Tarihi 1908-2015, İmge Kitabevi Yayınları, İstanbul, Türkiye.
- 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.
- Buguk, C. & B.W. Brorsen (2003), “Testing Weak-Form Market Efficiency: Evidence from the Istanbul Stock Exchange”, International Review of Financial Analysis, 12, 579-590.
- Butler, M. & D. Kazakov (2012), “Testing Implications of the Adaptive Market Hypothesis Via Computational Intelligence”, IEEE Conference on Computational Intelligence for Financial Engineering & Economics, 1-8.
- Campbell, J.Y. & A.W. Lo & A.C. MacKinlay (1997), The Econometrics of Financial Markets, Princeton University Press, New Jersey, USA.
- Charles, A. & O. Darné & J.H. Kim (2012), “Exchange-Rate Return Predictability and The Adaptive Markets Hypothesis: Evidence from Major Foreign Exchange Rates”, Journal of International Money and Finance, 31, 1607-1626.
- Charles, A. & O. Darné & J.H. Kim (2017), “Adaptive Markets Hypothesis for Islamic Stock Indices: Evidence from Dow Jones Size and Sector-Indices”, International Economics, 151, 100-112.
- Ching, W.K. & X. Huang & M.K. Ng & T.K. Siu (2013), Markov Chains: Models, Algorithms and Applications, Springer, New York, USA.
- Dağlıoğlu, C. & G. Kıral (2018), “Hisse Senedi Piyasa Fiyatlarının Saklı Markov Modeli ile Tahmin Edilmesi: Türkiye Örneği”, Uluslararası Ekonomi ve Yenilik Dergisi, 4(1), 61-75.
- Dias, J.G. & J.K. Vermunt & S. Ramos (2015), “Clustering Financial Time Series: New Insights from an Extended Hidden Markov Model”, European Journal of Operational Research, 243(3), 852-864.
- Dionne, G. & S.S. Hassani (2015), “Hidden Markov regimes in operational loss data: Application to the recent financial crisis”, Journal of Operational Risk, 1-40.
- Elliott, R.J. & W.C. Hunter & B.M. Jamieson (1998), “Drift and Volatility Estimation in Discrete Time”, Journal of Economic Dynamics and Control, 22(2), 209-218.
- Ertaş, F.C. & O. Özkan (2018), “Piyasa Etkinliği Açısından Adaptif Piyasa Hipotezinin Test Edilmesi: Türkiye ve ABD Hisse Senedi Piyasaları Örneği”, Finans Politik & Ekonomik Yorumlar, 642, 23-40.
- Escanciano, J.C. & C. Velasco (2006), “Generalized Spectral Tests for the Martingale Difference Hypothesis”, Journal of Econometrics, 134(1), 151-185.
- Escanciano, J.C. & I.N. Lobato (2009), “An Automatic Portmanteau Test for Serial Correlation”, Journal of Econometrics, 151(2), 140-149.
- Eyüpoğlu, K. & S. Eyüpoğlu (2020), “Borsa İstanbul Endekslerinde Adaptif Piyasa Hipotezinin Geçerliliğinin Test Edilmesi”, Journal of Yasar University, 15(59), 642-654.
- Fama, E.F. (1965), “The Behavior of Stock-Market Prices”, The Journal of Business, 38(1), 34-105.
- Fama, E.F. (1970), “Efficient Capital Markets: A Review of the Theory and Empirical Work”, Journal of Finance, 25(2), 383-417.
- Farmer, J.D. & A.W. Lo (1999), “Frontiers of Finance: Evolution and Efficient Markets”, Proceedings of the National Academy of Sciences of the United States of America, 96, 9991-9992.
- Ghazani, M.M. & M.K. Araghi (2014), “Evaluation of the Adaptive Market Hypothesis as an Evolutionary Perspective on Market Efficiency: Evidence from the Tehran Stock Exchange”, Research in International Business and Finance, 32, 50-59.
- Ghazani, M.M. & S.B. Ebrahimi (2019), “Testing the Adaptive Market Hypothesis as an Evolutionary Perspective on Market Efficiency: Evidence from The Crude Oil Prices”, Finance Research Letters, 30, 60-68.
- Grossman, S.J. & J.E. Stiglitz (1980), “On the Impossibility of Informationally Efficient Markets”, The American Economic Review, 70(3), 393-408.
- Gyamfi, E.N. (2018), “Adaptive Market Hypothesis: Evidence from the Ghanaian Stock Market”, Journal of African Business, 19(2), 195-209.
- Hatiboğlu, Z. & M. Aysan (1994), Türkiye Ekonomisinde 1994 Bunalımı, Beta Basım Yayım, İstanbul, Türkiye.
- Hiremath, G.S. & J. Kumari (2014), “Stock Returns Predictability and the Adaptive Market Hypothesis in Emerging Markets: Evidence from India”, SpringerPlus, 3(428), 1-14.
- Hiremath, G.S. & S. Narayan (2016), “Testing the Adaptive Market Hypothesis and Its Determinants for the Indian Stock Markets”, Finance Research Letters, 19, 173-180.
- Huang, M. & Y. Huang & K. He (2019), “Estimation and testing nonhomogeneity of hidden Markov model with application in financial time series”, Statistics and Its Interface, 12(2), 215-225.
- Ibe, O.C. (2013), Markov Processes for Stochastic Modelling, Elsevier, Massachusetts, USA.
- Ito, M. & A. Noda & T. Wada (2014), “International Stock Market Efficiency: A Non-Bayesian Time-Varying Model Approach”, Applied Economics, 43(23), 2744-2754.
- Ito, M. & A. Noda & T. Wada (2016), “The Evolution of Stock Market Efficiency in the US: A Non-Bayesian Time-Varying Model Approach”, Applied Economics, 48(7), 621-635.
- Kahraman, D. & M. Erkan (2005), “İstanbul Menkul Kıymetler Borsası’nda Tesadüfi Yürüyüş Testi”, Yönetim ve Ekonomi, 12(1), 11-19.
- Khuntia, S. & J.K. Pattanayak (2018), “Adaptive Market Hypothesis and Evolving Predictability of Bitcoin”. Economic Letters, 167, 26-28.
- Khursheed, A. & M. Naeem & S. Ahmed & F. Mustafa (2020), “Adaptive Market Hypothesis: An Empirical Analysis of Time-Varying Market Efficiency of Cryptocurrencies”, Cogent Economics & Finance, 8(1), 1719574.
- Kılıç, Y. & M.F. Buğan (2016), “The Efficient Market Hypothesis: Evidence from Turkey”, International Journal of Academic Research in Business and Social Sciences, 6(10), 262-272.
- Kim, J.H. & A. Shamsuddin & K.-P. Lim (2011), “Stock Return Predictability and the Adaptive Market Hypothesis: Evidence from Century-Long U.S. Data”, Journal of Empirical Finance, 18, 868-879.
- Kołatka, M. (2020), “Testing the Adaptive Market Hypothesis on the WIG Stock Index: 1994-2019”, Research Papers of Wroclaw University of Economics and Business, 64(1), 131-142.
- Langrock, R. & I.L. MacDonald & W. Zucchini (2012), “Some Nonstandard Stochastic Volatility Models and Their Estimation Using Structured Hidden Markov Models”, Journal of Empirical Finance, 19(1), 147-161.
- Lazăr, D. & A. Todea & D. Filip (2012), “Martingale Difference Hypothesis and Financial Crisis: Empirical Evidence from European Emerging Foreign Exchange Markets”, Economic Systems, 36, 338-350.
- Lekhal, E. & A. El Oubani (2020), “Does the Adaptive Market Hypothesis Explain the Evolution of Emerging Markets Efficiency? Evidence from the Moroccan Financial Market”, Heliyon, 6(7), e04429, 1-12.
- Li, N. (2016), Hidden Markov model and financial application, The University of Texas in Austin, Austin, USA.
Lim, K.-P. & R.D. Brooks (2006), The Evolving and Relative Efficiencies of Stock Markets: Empirical Evidence from Rolling Bicorrelation Test Statistics, <https://ssrn.com/abstract=931071/>, 13.02.2019.
- Lim, K.-P. & W. Luo & J.H. Kim (2013), “Are US Stock Index Returns Predictable? Evidence from Automatic Autocorrelation-Based Tests”, Applied Economics, 45(8), 953-962.
- Lim, K.-P. (2007), “Ranking Market Efficiency for Stock Markets: A Nonlinear Perspective”, Physica A, 376, 445-454.
- Lin, S.-K. & S.-Y. Wang & P.-L. Tsai (2009), “Application of Hidden Markov Switching Moving Average Model in the Stock Markets: Theory and Empirical Evidence”, International Review of Economics & Finance, 18(2), 306-317.
- Lo, A.W. & A.C. MacKinlay (1999), A Non-Random Walk Down Wall Street, Princeton University Press, New Jersey, USA.
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