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YÜKSEK FREKANSLI İŞLEMLER SONRASI BORSA İSTANBUL'DA PİYASA ETKİNLİĞİNİN TEST EDİLMESİ

Yıl 2022, , 100 - 119, 30.06.2022
https://doi.org/10.17218/hititsbd.1107939

Öz

Yüksek frekanslı işlemlerin sermaye piyasalarında kullanımıyla birlikte yatırım ortamı değişmiş, yüksek frekanslı işlemlerin piyasa etkinliğinin tespitine ilişkin çalışmalarda araştırılması önem kazanmıştır. Yüksek frekanslı işlemlerin, kullanıldıkları piyasalarda hız ve teknoloji avantajları nedeniyle piyasa etkinliğini etkiledikleri ve kısa zaman aralıklarında zayıf formda piyasa etkinliğinin reddedilmesine yol açtıkları gözlemlenmiştir. Borsa İstanbul’un BISTECH sistemine geçmesiyle 2016 yılından itibaren yüksek frekanslı işlemler Türkiye piyasalarında kullanılmaya başlanmıştır. Bu çalışmada yüksek frekanslı işlemler dikkate alınarak, etkin piyasa hipotezinin Borsa İstanbul’daki geçerliliği sınanmıştır. Zayıf formda piyasa etkinliğinin tespiti için literatüre benzer bir şekilde varyans oranı testi kullanılarak rassal yürüyüş hipotezi test edilmiştir. Veri seti olarak Borsa İstanbul’un temel göstergesi olan BIST100 endeksinin 05/02/2019 ve 05/02/2020 dönemleri arasındaki dakikalık getirileri kullanılmıştır. Borsa İstanbul’un dakikalık zaman dilimlerinde zayıf formda etkin olmadığı gözlemlenmiştir. Yüksek frekanslı işlemlerin kullanıldığı Borsa İstanbul’da rassal yürüyüşün olmadığı, durağanlığın mevcut olduğu tespit edilmiştir. Bu sonuç Borsa İstanbul’da yüksek frekanslı işlemler kullanılarak piyasanın üzerinde getiri elde etmenin mümkün olduğunu ifade etmektedir.

Kaynakça

  • Bachelier, L. (1900). Théorie de la spéculation. Annales Scientifiques de l’École Normale Supérieure, 3(17), 21-86.
  • Baron, M., Brogaard, J., Hagströmer, B. ve Kirilenko, A. (2017). Risk and return in high-frequency trading. Journal of Financial and Quantitative Analysis (JFQA), 54(3), 993-1024.
  • Bektur Ç. ve Aydın M. (2019). Borsa İstanbul ve alt endekslerinde zayıf formda piyasa etkinliğinin analizi: Fourier yaklaşımı. Akademik İncelemeler Dergisi, 14(2), 56-76.
  • Benos, E. ve Sagade, S. (2013). High-frequency trading behaviour and its impact on market quality: Evidence from the UK equity market. Bank of England Working Papers, doi:10.2139/ssrn.2184302
  • Biasis B. ve Foucault T. (2014). Hft and market quality. Bankers, Markets ve Investors, 128(1), 5-19
  • Borsa İstanbul. (2016). Yüksek frekanslı işlemler (yfi) kullanıcılarının emir / işlem oranı yöntemi ile ücretlendirilmesi bilgi notu. Erişim adresi: https://www.borsaistanbul.com/files/emir-islem-orani-(otr)-bilgi-notu.pdf
  • Borsa İstanbul. (2019). Pay piyasasında algoritmik işlemler ve bıstech ptrm/işlem öncesi risk yönetimi prosedürü. Erişim adresi: https://www.borsaistanbul.com/files/bistech-islem-oncesi-risk-yonetimi-uygulamasi-ptrm-ortak-kullanici kilavuzuDEEEF07DE906E889C8281560.pdf
  • 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. doi: 10.1016/j.ribaf.2019.03.005
  • Brogaard, J., Hendershott, T. ve Riordan, R. (2014). High frequency trading and price discovery. Review Financial Study 27(8), 2267–2306.
  • Blocher, J., Cooper, R., Seddon, J. ve Van Vliet, B. (2016). Phantom liquidity and high-frequency quoting. Journal of Trading 11(3), 6–15. doi: 10.3905/jot.2016.11.3.006
  • Buguk, C. ve Brorsen, B.W. (2003). Testing weak-form market efficiency: Evidence from the Istanbul stock exchange. International Review of Financial Analysis, 12(5), 579-590. doi: 10.1016/S1057-5219(03)00065-6
  • Butler, M. ve Kazakov, D. (2012). Testing implications of the adaptive market hypothesis via computational intelligence. 2012 IEEE Conference on Computational Intelligence for Financial Engineering ve Economics (CIFER). doi: 10.1109/CIFEr.2012.6327799
  • Campbell J.Y., Lo, A.W. ve MacKinlay C. (1997). The econometrics of financial markets. New Jersey, Princeton: Princeton University Press.
  • Ertaş, F.C. ve Özkan O. (2018). Piyasa etkinliği açısından adaptif piyasa hipotezinin test edilmesi: Türkiye ve ABD hisse senedi piyasaları örneği. Finans Politik ve Ekonomik Yorumlar Dergisi, 55(642), 23-40.
  • European Central Bank. (2019). Competition among high-frequency traders, and market quality, Central Bank Working Paper Series. Erişim adresi: https://www.ecb.europa.eu/pub/pdf/scpwps/ecb.wp2290~b5fec3a181.en.pdf
  • Eyüboğlu, K. ve Eyüboğlu, S. (2020). Borsa İstanbul endekslerinde adaptif piyasa hipotezinin geçerliliğinin test edilmesi. Journal of Yaşar University, 15(59), 642-654.
  • Fama E.F. (1970). Efficient capital markets: A review of theory and empirical work. The Journal of Finance, 25(2), 383-417. doi:10.1111/J.1540- 6261.1970.TB00518.X
  • Fama, E.F. (1965). Random walks in stock market prices. Financial Analysts Journal, 51(1), 75-80.
  • Fama, E.F. (1965). The behavior of stock-market prices. The Journal of Business, 38(1), 34-105. doi:10.1086/294743
  • Fama, E.F. ve French, K.R. (1988). Dividend yields and expected stock returns. Journal of Financial Economics, 22(1), 3-25. doi:10.1016/0304- 405X(88)90020-7
  • Gemici, E. ve Polat, M. (2018). MIST borsalarında rassal yürüyüş hipotezi. Eskişehir Osmangazi Üniversitesi İktisadi ve İdari Bilimler Dergisi, 13(1), 129- 142. doi: 10.17153/oguiibf.344882
  • Gomber, P., Arndt, B., Lutat, M. ve Uhle, T. (2011). High-frequency trading. SRRN Electronic Journal. doi: 10.2139/ssrn.1858626
  • Gümüş, G. ve Bektur, Ç. (2019). Etkin piyasa hipotezi ve davranışsal finans modelleri: BİST-100 endeksinde anomali testi. Uluslararası Ekonomik Araştırmalar Dergisi, 5(2), 59-69.
  • Hagströmer, B. ve Nordén, L. (2013). The diversity of high frequency traders. Journal Finance and Marketing, 16(4), 741–770.
  • Hasbrouck J. ve Saar G. (2013). Low-latency trading. Journal of Financial Markets, 16(4), 646-679.
  • International Organization of Securities Commissions. (2011). Regulatory issues raised by the impact of technological changes on market integrity and efficiency consultation report. Erişim adresi: https://www.iosco.org/library/pubdocs/pdf/IOSCOPD354.pdf
  • Kim, J. H., Shamsuddin, A. ve Lim, K.P. (2011). Stock return predictability and the adaptive markets hypothesis: Evidence from century-long U.S. data. Journal of Empirical Finance, 18(5), 868-879. doi: 10.1016/j.jempfin.2011.08.002
  • Leone, V. ve Kwabi, F. (2019). High frequency trading, price discovery and market efficiency in the FTSE100. Economics Letters, 181, 174-177. doi: 10.1016/j.econlet.2019.05.022
  • Lo, A.W. (2004). The adaptive markets hypothesis: Market efficiency from an evolutionary perspective. Journal of Portfolio Management, 5(30), 15- 29. doi:10.3905/jpm.2004.442611
  • Lo, A.W. (2012). Adaptive markets and the new world order. Financial Analysts Journal, 68(2), 18–29.
  • Lo, A.W. ve MacKinlay, 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.
  • Mobarek, A. ve Keasey, K. (2000). Weak-form market efficiency of an emerging market: Evidence from Dhaka stock market of Bangladesh. Paper Presented at the ENBS Conference Held in Oslo, Oslo.
  • Özdemir, Z.A. (2008). Efficient market hypothesis: Evidence from a small open economy. Applied Economics, 40(5), 633-641. doi: 10.1080/00036840600722315
  • Samuelson, P.A. (1965). Proof that properly anticipated prices fluctuate randomly. Industrial Management Review, 6(2), 41-49.
  • Securities Exchange Commission. (2010). Report of the staffs of the CFTC and SEC to the joint advisory committee on emerging regulatory issues. Erişim adresi: https://www.sec.gov/spotlight/sec-cftcjointcommittee/021811-report.pdf
  • Securities and Exchange Commission. (2014). Equity market structure literature review part II: High frequency trading. Erişim adresi: https://www.sec.gov/marketstructure/research/hft_lit_review_march_2014.pdf
  • Simon, H. (1955). A behavioral model of rational choice. Quarterly Journal of Economics, 69(1), 99-118.
  • Shorter, G. ve Miller, R.S. (2014). Dark pools in equity trading: Policy concerns and recent developments. Congressional Research Service. Erişim adresi: https://fas.org/sgp/crs/misc/R43739.pdf
  • Tanrıöver, B. ve Çöllü, D.A. (2015). Türkiye’de yatırımcıların öngörü performanslarının rassal yürüyüş modeli çerçevesinde analizi. Business and Economics Research Journal, 6(2), 127-139.
  • Uğurlu, E. (2009). Kesikli seçim modelleri. İstanbul Aydın Üniversitesi Ekonomi ve Finans Bölümü Ders Notları, kitapçık 1. doi: 10.13140/rg.2.1.3262.2561
  • Vanstone, B. ve Hahn, T. (2015). Data characteristics for high-frequency trading systems. Greg N. Gregoriou (Ed.), Handbook of High Frequency Trading (s. 47-57). London: Academic Press.
  • Ye, M., Yao, C. ve Gai, J. (2013). The externalities of high frequency trading. SSRN Electronic Journal. doi: 10.2139/ssrn.2066839

Testing Market Efficiency In Borsa Istanbul After High Frequency Trading

Yıl 2022, , 100 - 119, 30.06.2022
https://doi.org/10.17218/hititsbd.1107939

Öz

With the use of high-frequency trading (hereafter HFT ) in capital markets, the investment environment has changed, and it has become important to investigate HFT studies on market efficiency. It has been observed that HFT affect market efficiency due to speed and technology advantages in the markets in which they are used, and lead to the rejection of weak form market activity in short time intervals. With Borsa İstanbul's transition to the BISTECH system, HFT have been used in Turkish markets since 2016. In this study, the validity of the efficient market hypothesis in Borsa Istanbul was tested by considering HFT. In order to determine the weak form market efficiency, the random walk hypothesis was tested by using the variance ratio test, similar to the literature. As the data set, the minute returns of the BIST100 index, which is the main indicator of Borsa Istanbul, between the periods 05/02/2019 and 05/02/2020 were used. It has been observed that Borsa Istanbul is not active in weak form in minute timeframes. It has been determined that there is no random walk and stationarity in Borsa Istanbul, where HFT are used. This result indicates that it is possible to obtain returns above the market by using HFT in Borsa Istanbul.

Kaynakça

  • Bachelier, L. (1900). Théorie de la spéculation. Annales Scientifiques de l’École Normale Supérieure, 3(17), 21-86.
  • Baron, M., Brogaard, J., Hagströmer, B. ve Kirilenko, A. (2017). Risk and return in high-frequency trading. Journal of Financial and Quantitative Analysis (JFQA), 54(3), 993-1024.
  • Bektur Ç. ve Aydın M. (2019). Borsa İstanbul ve alt endekslerinde zayıf formda piyasa etkinliğinin analizi: Fourier yaklaşımı. Akademik İncelemeler Dergisi, 14(2), 56-76.
  • Benos, E. ve Sagade, S. (2013). High-frequency trading behaviour and its impact on market quality: Evidence from the UK equity market. Bank of England Working Papers, doi:10.2139/ssrn.2184302
  • Biasis B. ve Foucault T. (2014). Hft and market quality. Bankers, Markets ve Investors, 128(1), 5-19
  • Borsa İstanbul. (2016). Yüksek frekanslı işlemler (yfi) kullanıcılarının emir / işlem oranı yöntemi ile ücretlendirilmesi bilgi notu. Erişim adresi: https://www.borsaistanbul.com/files/emir-islem-orani-(otr)-bilgi-notu.pdf
  • Borsa İstanbul. (2019). Pay piyasasında algoritmik işlemler ve bıstech ptrm/işlem öncesi risk yönetimi prosedürü. Erişim adresi: https://www.borsaistanbul.com/files/bistech-islem-oncesi-risk-yonetimi-uygulamasi-ptrm-ortak-kullanici kilavuzuDEEEF07DE906E889C8281560.pdf
  • 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. doi: 10.1016/j.ribaf.2019.03.005
  • Brogaard, J., Hendershott, T. ve Riordan, R. (2014). High frequency trading and price discovery. Review Financial Study 27(8), 2267–2306.
  • Blocher, J., Cooper, R., Seddon, J. ve Van Vliet, B. (2016). Phantom liquidity and high-frequency quoting. Journal of Trading 11(3), 6–15. doi: 10.3905/jot.2016.11.3.006
  • Buguk, C. ve Brorsen, B.W. (2003). Testing weak-form market efficiency: Evidence from the Istanbul stock exchange. International Review of Financial Analysis, 12(5), 579-590. doi: 10.1016/S1057-5219(03)00065-6
  • Butler, M. ve Kazakov, D. (2012). Testing implications of the adaptive market hypothesis via computational intelligence. 2012 IEEE Conference on Computational Intelligence for Financial Engineering ve Economics (CIFER). doi: 10.1109/CIFEr.2012.6327799
  • Campbell J.Y., Lo, A.W. ve MacKinlay C. (1997). The econometrics of financial markets. New Jersey, Princeton: Princeton University Press.
  • Ertaş, F.C. ve Özkan O. (2018). Piyasa etkinliği açısından adaptif piyasa hipotezinin test edilmesi: Türkiye ve ABD hisse senedi piyasaları örneği. Finans Politik ve Ekonomik Yorumlar Dergisi, 55(642), 23-40.
  • European Central Bank. (2019). Competition among high-frequency traders, and market quality, Central Bank Working Paper Series. Erişim adresi: https://www.ecb.europa.eu/pub/pdf/scpwps/ecb.wp2290~b5fec3a181.en.pdf
  • Eyüboğlu, K. ve Eyüboğlu, S. (2020). Borsa İstanbul endekslerinde adaptif piyasa hipotezinin geçerliliğinin test edilmesi. Journal of Yaşar University, 15(59), 642-654.
  • Fama E.F. (1970). Efficient capital markets: A review of theory and empirical work. The Journal of Finance, 25(2), 383-417. doi:10.1111/J.1540- 6261.1970.TB00518.X
  • Fama, E.F. (1965). Random walks in stock market prices. Financial Analysts Journal, 51(1), 75-80.
  • Fama, E.F. (1965). The behavior of stock-market prices. The Journal of Business, 38(1), 34-105. doi:10.1086/294743
  • Fama, E.F. ve French, K.R. (1988). Dividend yields and expected stock returns. Journal of Financial Economics, 22(1), 3-25. doi:10.1016/0304- 405X(88)90020-7
  • Gemici, E. ve Polat, M. (2018). MIST borsalarında rassal yürüyüş hipotezi. Eskişehir Osmangazi Üniversitesi İktisadi ve İdari Bilimler Dergisi, 13(1), 129- 142. doi: 10.17153/oguiibf.344882
  • Gomber, P., Arndt, B., Lutat, M. ve Uhle, T. (2011). High-frequency trading. SRRN Electronic Journal. doi: 10.2139/ssrn.1858626
  • Gümüş, G. ve Bektur, Ç. (2019). Etkin piyasa hipotezi ve davranışsal finans modelleri: BİST-100 endeksinde anomali testi. Uluslararası Ekonomik Araştırmalar Dergisi, 5(2), 59-69.
  • Hagströmer, B. ve Nordén, L. (2013). The diversity of high frequency traders. Journal Finance and Marketing, 16(4), 741–770.
  • Hasbrouck J. ve Saar G. (2013). Low-latency trading. Journal of Financial Markets, 16(4), 646-679.
  • International Organization of Securities Commissions. (2011). Regulatory issues raised by the impact of technological changes on market integrity and efficiency consultation report. Erişim adresi: https://www.iosco.org/library/pubdocs/pdf/IOSCOPD354.pdf
  • Kim, J. H., Shamsuddin, A. ve Lim, K.P. (2011). Stock return predictability and the adaptive markets hypothesis: Evidence from century-long U.S. data. Journal of Empirical Finance, 18(5), 868-879. doi: 10.1016/j.jempfin.2011.08.002
  • Leone, V. ve Kwabi, F. (2019). High frequency trading, price discovery and market efficiency in the FTSE100. Economics Letters, 181, 174-177. doi: 10.1016/j.econlet.2019.05.022
  • Lo, A.W. (2004). The adaptive markets hypothesis: Market efficiency from an evolutionary perspective. Journal of Portfolio Management, 5(30), 15- 29. doi:10.3905/jpm.2004.442611
  • Lo, A.W. (2012). Adaptive markets and the new world order. Financial Analysts Journal, 68(2), 18–29.
  • Lo, A.W. ve MacKinlay, 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.
  • Mobarek, A. ve Keasey, K. (2000). Weak-form market efficiency of an emerging market: Evidence from Dhaka stock market of Bangladesh. Paper Presented at the ENBS Conference Held in Oslo, Oslo.
  • Özdemir, Z.A. (2008). Efficient market hypothesis: Evidence from a small open economy. Applied Economics, 40(5), 633-641. doi: 10.1080/00036840600722315
  • Samuelson, P.A. (1965). Proof that properly anticipated prices fluctuate randomly. Industrial Management Review, 6(2), 41-49.
  • Securities Exchange Commission. (2010). Report of the staffs of the CFTC and SEC to the joint advisory committee on emerging regulatory issues. Erişim adresi: https://www.sec.gov/spotlight/sec-cftcjointcommittee/021811-report.pdf
  • Securities and Exchange Commission. (2014). Equity market structure literature review part II: High frequency trading. Erişim adresi: https://www.sec.gov/marketstructure/research/hft_lit_review_march_2014.pdf
  • Simon, H. (1955). A behavioral model of rational choice. Quarterly Journal of Economics, 69(1), 99-118.
  • Shorter, G. ve Miller, R.S. (2014). Dark pools in equity trading: Policy concerns and recent developments. Congressional Research Service. Erişim adresi: https://fas.org/sgp/crs/misc/R43739.pdf
  • Tanrıöver, B. ve Çöllü, D.A. (2015). Türkiye’de yatırımcıların öngörü performanslarının rassal yürüyüş modeli çerçevesinde analizi. Business and Economics Research Journal, 6(2), 127-139.
  • Uğurlu, E. (2009). Kesikli seçim modelleri. İstanbul Aydın Üniversitesi Ekonomi ve Finans Bölümü Ders Notları, kitapçık 1. doi: 10.13140/rg.2.1.3262.2561
  • Vanstone, B. ve Hahn, T. (2015). Data characteristics for high-frequency trading systems. Greg N. Gregoriou (Ed.), Handbook of High Frequency Trading (s. 47-57). London: Academic Press.
  • Ye, M., Yao, C. ve Gai, J. (2013). The externalities of high frequency trading. SSRN Electronic Journal. doi: 10.2139/ssrn.2066839
Toplam 42 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Bölüm Makaleler
Yazarlar

Çağrı Kaan Yalçın 0000-0001-8725-6559

Yasin Erdem Çevik 0000-0003-3684-6668

Cihan Tanrıöven 0000-0003-0192-7628

Yayımlanma Tarihi 30 Haziran 2022
Gönderilme Tarihi 23 Nisan 2022
Yayımlandığı Sayı Yıl 2022

Kaynak Göster

APA Yalçın, Ç. K., Çevik, Y. E., & Tanrıöven, C. (2022). YÜKSEK FREKANSLI İŞLEMLER SONRASI BORSA İSTANBUL’DA PİYASA ETKİNLİĞİNİN TEST EDİLMESİ. Hitit Sosyal Bilimler Dergisi, 15(1), 100-119. https://doi.org/10.17218/hititsbd.1107939
                                                     Hitit Sosyal Bilimler Dergisi  Creative Commons Atıf-GayriTicari 4.0 Uluslararası Lisansı (CC BY NC) ile lisanslanmıştır.