Journals / Finans Politik ve Ekonomik Yorumlar Dergisi / 2014 / Cilt: 51 - Sayı: 587

The relationship between trading volume and return volatility: A test of mixed distribution hypothesis for index futures on Turkish derivatives exchange

İşlem hacmi ve getiri volatilitesi arasındaki ilişkiler: Türk vadeli işlem piyasalarındaki endeks sözleşmeler için dağılım karışımı hipotezinin testi

Pages
83–93
DOI
—
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Research results show that when the trading volume was added as an explanatory variable to the conditional variance equation, the GARCH affect in return volatility decreased.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The aim of this paper is to investigate the dynamic relationships between trading volume and return volatility in Turkish derivatives exchange.
📊
Key Findings & Data:Research results show that when the trading volume was added as an explanatory variable to the conditional variance equation, the GARCH affect in return volatility decreased.
💡
Conclusion & Impact:This result can be interpreted as futures market presents proofs supporting mixture of distribution hypothesis.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

The aim of this paper is to investigate the dynamic relationships between trading volume and return volatility in Turkish derivatives exchange. In this study, whether trading volume has any effect or not on return volatility is determined by EGARCH model. Research results show that when the trading volume was added as an explanatory variable to the conditional variance equation, the GARCH affect in return volatility decreased. For this reason, it was proven that the trading volume can be used as an indicator for return volatility. Furthermore, Granger causality test results proved that there is no lead-lag relations between these variables. This result can be interpreted as futures market presents proofs supporting mixture of distribution hypothesis.

Özet

Bu çalışmanın amacı, Türk vadeli işlem piyasalarında işlem hacmi ve getiri volatilitesi arasındaki dinamik ilişkileri ortaya koymaktır. Çalışmada işlem hacminin getiri volatilitesi üzerinde herhangi bir etkisinin olup olmadığı EGARCH modeli tarafından açıklanmıştır. Araştırma sonuçlarına göre işlem hacmi, koşullu varyans denklemine açıklayıcı değişken olarak ilave edildiğinde getiri volatilitesi üzerindeki GARCH kalıcılığı azalmıştır. Bu sebepten işlem hacminin getiri volatilitesini açıklamakta bir gösterge olarak kullanılabileceği kanıtlanmıştır. Granger nedensellik test sonuçları göstermektedir ki iki değişken arasında herhangi bir öncülardıl ilişki söz konusu değildir. Bu sonuç vadeli piyasaların dağılım karışımı hipotezini destekler kanıtlar sunduğunu göstermektedir.

🔖

Cite This Article

ÇELİK, İ. (2014). The relationship between trading volume and return volatility: A test of mixed distribution hypothesis for index futures on Turkish derivatives exchange. Finans Politik ve Ekonomik Yorumlar Dergisi, Cilt: 51 - Sayı: 587, 83–93. https://ajindex.com/articles/210162

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (15)

  1. BOLLERSLEV, Tim; (1986), “Generalized Autoregressive Conditional Hteroscedasticity”, Journal of Econometrics, vol. 31, Issue. 3, 307-327
  2. CHEN, Gongmeng, FIRTH, Michael, and XIN, Yu; (2004), “The Price-Volume Relationship in China’s Commodity Futures Markets”, The Chinese Economy, vol. 37, 87-122
  3. CLARK, Peter K.; (1973), “A Subordinated Stochastic Process Model with Finite Variance for Speculative Prices”, Econometrica, 41(1), 135-155
  4. COPELAND, Thomas E.; (1977), “A Probability Model of Asset Trading”, Journal of Financial and Quantitative Analysis, 12, 563-578
  5. ÇUKUR, Sadık, GÜMRAH, Ümit ve GÜMRAH ÜSTÜN, Meltem; (2012), “İstanbul Menkul Kıymetler Borsasında Hisse Senedi Getirileri ve İşlem Hacmi İlişkisi”, Niğde Üniversitesi İİBF Dergisi, Cilt. 5, Sayı. 1, 20-35
  6. ENGLE, Robert F.; (1982) “Autoregressive Conditional Hteroscedasticity with Estimates of the Variance of United Kingdom Inflation”, Econometrica, vol. 50, no. 4, 987-1008
  7. FLOROS, Christos and VOUGAS, Degiannakis V.; (2007) “Trading Volume and Returns Relationship in Greek Stock Index Futures Market: GARCH vs. GMM”, International Research Journal of Finance and Economics (12), ISSN:1450- 2887, 98-115
  8. FUNG, Hung Gay, PATTERSON, Gary A.; (1999), “The Dynamic Relationship of Volatility, Volume and Market Depth in Currency Futures Markets”, Journal of International Financial Markets, Institutions and Money 9, 33-59
  9. GIRMA, Paul Berhanu and MOUGOUE, Mbodja; (2002), “An Empirical Examination Of The Relation Between Futures Spreads Volatility, Volume, and Open Interest”, The Journal of Futures Markets, Vol. 22, No. 11, 1083–1102
  10. GRAMMATIKOS, Theoharry, SAUNDERS, Anthony; (1986), “Future Price Variability: A Test of Maturity and Volume Effects”, Journal of Business, 59, 313-330
  11. GWILYM, Owain Ap, McMILLAN, David and SPEIGHT, Alan; (1999), “The Intraday Relationship Between Volume and Volatility in LIFFE Futures Markets”, Applied Financial Economics, 9:6, 593-604
  12. HADSELL, Lester; (2006) “A TARCH Examination of the Return Volatility–Volume Relationship in Electricity Futures”,Applied Financial Economics, 16:12, 893-901
  13. HOLMES, Phil and TOMSETT, Mark; (2004), “Information and Noise in U.K. Futures Markets”, The Journal of Futures Markets, Vol. 24, No. 8, 17–1731
  14. KALAYCI, Şeref, DEMİR, Yusuf. ve GÖK, İbrahim Yaşar; (2010), “Getiri Volatilitesi-İşlem Hacmi İlişkisi: Vadeli İşlem ve Opsiyon Borsası Üzerinde Ampirik Bir Uygulama”, Akdeniz İİBF Dergisi (20), 104-120
  15. KARPOFF, Jonathan M.; (1987), “The Relation Between