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MINT PİYASALARINDA HİSSE SENEDİ PİYASA OYNAKLIĞI VE İŞLEM HACMİ: COVİD 19 PANDEMİ DÖNEMİNDEN BULGULAR

Year 2023, Volume: 10 Issue: 1, 39 - 48, 02.01.2023

Abstract

Çalışmada hisse senedi getiri oynaklığı ve işlem hacmi arasındaki ilişki araştırılmıştır. Yükselen piyasalar kapsamında MINT ülkeleri 11.03.2020 – 28.04.2022 Covid 19 pandemi dönemi kapsamında analiz edilmiştir. İşlem hacminin eş zamanlı ve bir dönem geçmiş dönemi dahil edilerek getiriler üzerindeki asimetrik ilişkileri ortaya koymak için EGARCH(1,1) model tahminleri yapılmıştır. Türkiye ve Endonezya için yapılan model tahmini sonuçları getiri oynaklığında asimetrik bir etkinin olduğunu gösterirken; Meksika ve Nijerya model tahmin sonuçlarında oynaklık üzerinde asimetrik bir etkinin olduğu görülmemektedir. Türkiye ve Endonezya sonuçları Karışık Dağılımlar Hipotezinin geçerliliğini desteklemektedir. Çalışmanın sonuçları portföy yönetimi, araştırmacılar, risk yönetimi ve yatırımcılar için faydalı bulgular sunmaktadır.

References

  • Adenomon, M. O., Maijamaa, B., & John, D. O. (2022). The effects of Covid-19 outbreak on the Nigerian Stock Exchange performance: Evidence from GARCH Models. Journal of Statistical Modeling & Analytics (JOSMA), 4(1), 25-38.
  • Ahmed, R. I., Zhao, G., & Habiba, U. (2022). Dynamics of return linkages and asymmetric volatility spillovers among Asian emerging stock markets. The Chinese Economy, 55(2), 156-167.
  • Aydın, R., Polat, İ. H., Alpagut, S., & Lögün, A. (2021). Cross-Country Analysis of the Impact of Covid-19 on Share Markets. Journal of Applied Economics and Business Research JAEBR, 11(2), 80-89.
  • Azevedo, A., Karim, M., Gregoriou, A., & Rhodes, M. (2014). Stock price and volume effects associated with changes in the composition of the FTSE Bursa Malaysian KLCI. Journal of International Financial Markets, Institutions and Money, 28, 20-35. Bhowmik, R., & Wang, S. (2020). Stock market volatility and return analysis: A systematic literature review. Entropy, 22(5), 1-18.
  • Brooks, C. (2014). Introductory econometrics for finance (3th ed.). United Kingdom: Cambridge university press.
  • Chan, B. S. F., Cheng, A. C. H., & Ma, A. K. C. (2018). Stock market volatility and trading volume: A special case in Hong Kong with stock connect turnover. Journal of Risk and Financial Management, 11(4), 1-17.
  • Chen, S. S. (2012). Revisiting the empirical linkages between stock returns and trading volume. Journal of Banking & Finance, 36(6), 1781-1788.
  • Chocholatá, M. (2011). Trading volume and volatility of stock returns: Evidence from some European and Asian stock markets. Metody Ilościowe w Badaniach Ekonomicznych, 12(1), 27-36.
  • Christiana, A. M., Setiana, E., & Mamduch, M. (2016). The empirical relationship between stock return and trading volume based on stock market cycles. The Indonesian Capital Market Review, 8(1), 46-57.
  • Clark, P. (1973). A subordinated stochastic process model with finite variances for speculative prices. Econometrica, 41(1), 135–155.
  • Copeland, T.E. (1976). A model for asset trading under the assumption of sequential information arrival. Journal of Finance, 31(4), 1149–1168.
  • Darrat, A. F., Zhong, M., & Cheng, L. T. (2007). Intraday volume and volatility relations with and without public news. Journal of Banking & Finance, 31(9), 2711-2729.
  • Darwish, M. (2012). Testing the contemporaneous and causal relationship between trading volume and return in the palestine exchange. International Journal of Economics and Finance, 4(4), 182-192.
  • Do, A., Powell, R., Yong, J., & Singh, A. (2020). Time-varying asymmetric volatility spillover between global markets and China's A, B and H-shares using EGARCH and DCC-EGARCH models. The North American Journal of Economics and Finance, 54, 1-26.
  • Ejem, C. A., Ogbonna, G. U., & Ezirim, C. B. (2018). The relationshıp between stock market return and conditional variance (volatility) in the Nıgerian stock market from 1999-2016. International Journal of Business & Economics Perspectives, 13(1), 89-106.
  • Emenike, K. O., & Opara, C. C. (2014). The relationship between stock returns volatility and trading volume in Nigeria. Verslo Sistemos ir Ekonomika, 4(2), 115-125.
  • Fakhfekh, M., Jeribi, A., & Ben Salem, M. (2021). Volatility dynamics of the Tunisian stock market before and during the COVID‐19 outbreak: Evidence from the GARCH family models. International Journal of Finance & Economics., 1-14. https://doi.org/10.1002/ijfe.2499
  • Huang, J., Wang, Y., Fan, Y., & Li, H. (2022). Gauging the effect of investor overconfidence on trading volume from the perspective of the relationship between lagged stock returns and current trading volume. International Finance, 25(1), 103-123.
  • Kao, Y. S., Chuang, H. L., & Ku, Y. C. (2020). The empirical linkages among market returns, return volatility, and trading volume: Evidence from the S&P 500 VIX Futures. The North American Journal of Economics and Finance, 54, 1-12.
  • Karpoff, J. M. (1987). The relation between price changes and trading volume: A survey. Journal of Financial and quantitative Analysis, 22(1), 109-126.
  • Kuhe, D. A., Chiawa, M. A., Nwaosu, S. C., & Ikughur, J. A. (2019). Modeling Volatility of Asset and Volume of Trade Returns in the Nigerian Stock Market in the Presence of Random Level Shifts. Asian Journal of Probability and Statistics, 3(2), 1-25.
  • Mubarik, F., & Javid, A. (2009). Relationship between stock return, trading volume and volatility: Evidence from Pakistani stock market, Asia Pacific Journal of Finance and Banking Research, 3(3), 1-17.
  • Mushinada, V. N. C., & Veluri, V. S. S. (2020). Self-attribution, overconfidence and dynamic market volatility in Indian stock market. Global Business Review, 21(4), 970-989.
  • Naik, P. K., & Padhi, P. (2015). Stock market volatility and equity trading volume: Empirical examination from Brazil, Russia, India and China (BRIC). Global Business Review, 16(5S), 28S-45S.
  • Naik, P. K., Gupta, R., & Padhi, P. (2018). The Relationship between Stock Market Volatility and Trading Volume: Evidence from South Africa. The Journal of Developing Areas, 52(1), 99-114.
  • Nelson, D. B. (1991). Conditional heteroscedasticity in asset returns: A new approach. Econometrica, 59, 347–370.
  • Özdemir, L., Ercan, O. Z. E. N., Grima, S., & Romānova, I. (2021). Determining the Return Volatility of Major Stock Markets Before and During the COVID-19 Pandemic by Applying the EGARCH Model. Scientific Annals of Economics and Business, 68(4), 405-419.
  • Rakshit, B., & Neog, Y. (2021). Effects of the COVID-19 pandemic on stock market returns and volatilities: evidence from selected emerging economies. Studies in Economics and Finance. 1-23. https://doi.org/10.1108/SEF-09-2020-0389
  • Tai, C. S. (2007). Market integration and contagion: Evidence from Asian emerging stock and foreign exchange markets. Emerging markets review, 8(4), 264-283.
  • Temiz Dinç, D., & Akdoğan, E. C. (2019). Renewable energy production, energy consumption and sustainable economic growth in Turkey: A VECM approach. Sustainability, 11(5), 1-14.
  • Umar, M., Mirza, N., Rizvi, S. K. A., & Furqan, M. (2021). Asymmetric volatility structure of equity returns: Evidence from an emerging market. The Quarterly Review of Economics and Finance. https://doi.org/10.1016/j.qref.2021.04.016.
  • Vidanage, T. N., Carmignani, F., & Singh, T. (2017). Predictability of return volatility across different emerging capital markets: Evidence from Asia. South Asian Journal of Macroeconomics and Public Finance, 6(2), 157-177.
  • Vo, X. V., & Tran, T. T. A. (2020). Modelling volatility spillovers from the US equity market to ASEAN stock markets. Pacific-Basin Finance Journal, 59, 1-8.
  • Wang, P., Wang, P., & Liu, A. (2005). Stock return volatility and trading volume: Evidence from the Chinese Stock Market. Journal of Chinese Economic and Business Studies, 3(1), 39-54.
  • Yıldırım, D., & Çelik, A. K. (2020). Stock market volatility and structural breaks: An empirical analysis of fragile five countries using GARCH and EGARCH models. Journal of Applied Economics and Business Research, 10(3), 148-163.

STOCK MARKET VOLATILITY AND TRADING VOLUME IN MINT MARKETS: EVIDENCE FROM COVID 19 PANDEMIC PERİOD

Year 2023, Volume: 10 Issue: 1, 39 - 48, 02.01.2023

Abstract

The study examines the relationship between stock return volatility and trading volume. MINT countries are analysed within the scope of the Covid 19 pandemic period from 11.03.2020 to 28.04.2022. EGARCH(1,1) model estimations reveal the asymmetrical effects on the returns by including the contemporaneous and lagged trading volumes. While the model estimation results show that there is an asymmetric effect in return volatility for Turkey and Indonesia stock markets, there does not appear to be an asymmetric effect on volatility for Mexico and Nigeria stock markets. The results support the validity of the Mixture of Distribution Hypothesis for Turkey and Indonesia. The study results provide useful findings for portfolio managers, researchers and investors.

References

  • Adenomon, M. O., Maijamaa, B., & John, D. O. (2022). The effects of Covid-19 outbreak on the Nigerian Stock Exchange performance: Evidence from GARCH Models. Journal of Statistical Modeling & Analytics (JOSMA), 4(1), 25-38.
  • Ahmed, R. I., Zhao, G., & Habiba, U. (2022). Dynamics of return linkages and asymmetric volatility spillovers among Asian emerging stock markets. The Chinese Economy, 55(2), 156-167.
  • Aydın, R., Polat, İ. H., Alpagut, S., & Lögün, A. (2021). Cross-Country Analysis of the Impact of Covid-19 on Share Markets. Journal of Applied Economics and Business Research JAEBR, 11(2), 80-89.
  • Azevedo, A., Karim, M., Gregoriou, A., & Rhodes, M. (2014). Stock price and volume effects associated with changes in the composition of the FTSE Bursa Malaysian KLCI. Journal of International Financial Markets, Institutions and Money, 28, 20-35. Bhowmik, R., & Wang, S. (2020). Stock market volatility and return analysis: A systematic literature review. Entropy, 22(5), 1-18.
  • Brooks, C. (2014). Introductory econometrics for finance (3th ed.). United Kingdom: Cambridge university press.
  • Chan, B. S. F., Cheng, A. C. H., & Ma, A. K. C. (2018). Stock market volatility and trading volume: A special case in Hong Kong with stock connect turnover. Journal of Risk and Financial Management, 11(4), 1-17.
  • Chen, S. S. (2012). Revisiting the empirical linkages between stock returns and trading volume. Journal of Banking & Finance, 36(6), 1781-1788.
  • Chocholatá, M. (2011). Trading volume and volatility of stock returns: Evidence from some European and Asian stock markets. Metody Ilościowe w Badaniach Ekonomicznych, 12(1), 27-36.
  • Christiana, A. M., Setiana, E., & Mamduch, M. (2016). The empirical relationship between stock return and trading volume based on stock market cycles. The Indonesian Capital Market Review, 8(1), 46-57.
  • Clark, P. (1973). A subordinated stochastic process model with finite variances for speculative prices. Econometrica, 41(1), 135–155.
  • Copeland, T.E. (1976). A model for asset trading under the assumption of sequential information arrival. Journal of Finance, 31(4), 1149–1168.
  • Darrat, A. F., Zhong, M., & Cheng, L. T. (2007). Intraday volume and volatility relations with and without public news. Journal of Banking & Finance, 31(9), 2711-2729.
  • Darwish, M. (2012). Testing the contemporaneous and causal relationship between trading volume and return in the palestine exchange. International Journal of Economics and Finance, 4(4), 182-192.
  • Do, A., Powell, R., Yong, J., & Singh, A. (2020). Time-varying asymmetric volatility spillover between global markets and China's A, B and H-shares using EGARCH and DCC-EGARCH models. The North American Journal of Economics and Finance, 54, 1-26.
  • Ejem, C. A., Ogbonna, G. U., & Ezirim, C. B. (2018). The relationshıp between stock market return and conditional variance (volatility) in the Nıgerian stock market from 1999-2016. International Journal of Business & Economics Perspectives, 13(1), 89-106.
  • Emenike, K. O., & Opara, C. C. (2014). The relationship between stock returns volatility and trading volume in Nigeria. Verslo Sistemos ir Ekonomika, 4(2), 115-125.
  • Fakhfekh, M., Jeribi, A., & Ben Salem, M. (2021). Volatility dynamics of the Tunisian stock market before and during the COVID‐19 outbreak: Evidence from the GARCH family models. International Journal of Finance & Economics., 1-14. https://doi.org/10.1002/ijfe.2499
  • Huang, J., Wang, Y., Fan, Y., & Li, H. (2022). Gauging the effect of investor overconfidence on trading volume from the perspective of the relationship between lagged stock returns and current trading volume. International Finance, 25(1), 103-123.
  • Kao, Y. S., Chuang, H. L., & Ku, Y. C. (2020). The empirical linkages among market returns, return volatility, and trading volume: Evidence from the S&P 500 VIX Futures. The North American Journal of Economics and Finance, 54, 1-12.
  • Karpoff, J. M. (1987). The relation between price changes and trading volume: A survey. Journal of Financial and quantitative Analysis, 22(1), 109-126.
  • Kuhe, D. A., Chiawa, M. A., Nwaosu, S. C., & Ikughur, J. A. (2019). Modeling Volatility of Asset and Volume of Trade Returns in the Nigerian Stock Market in the Presence of Random Level Shifts. Asian Journal of Probability and Statistics, 3(2), 1-25.
  • Mubarik, F., & Javid, A. (2009). Relationship between stock return, trading volume and volatility: Evidence from Pakistani stock market, Asia Pacific Journal of Finance and Banking Research, 3(3), 1-17.
  • Mushinada, V. N. C., & Veluri, V. S. S. (2020). Self-attribution, overconfidence and dynamic market volatility in Indian stock market. Global Business Review, 21(4), 970-989.
  • Naik, P. K., & Padhi, P. (2015). Stock market volatility and equity trading volume: Empirical examination from Brazil, Russia, India and China (BRIC). Global Business Review, 16(5S), 28S-45S.
  • Naik, P. K., Gupta, R., & Padhi, P. (2018). The Relationship between Stock Market Volatility and Trading Volume: Evidence from South Africa. The Journal of Developing Areas, 52(1), 99-114.
  • Nelson, D. B. (1991). Conditional heteroscedasticity in asset returns: A new approach. Econometrica, 59, 347–370.
  • Özdemir, L., Ercan, O. Z. E. N., Grima, S., & Romānova, I. (2021). Determining the Return Volatility of Major Stock Markets Before and During the COVID-19 Pandemic by Applying the EGARCH Model. Scientific Annals of Economics and Business, 68(4), 405-419.
  • Rakshit, B., & Neog, Y. (2021). Effects of the COVID-19 pandemic on stock market returns and volatilities: evidence from selected emerging economies. Studies in Economics and Finance. 1-23. https://doi.org/10.1108/SEF-09-2020-0389
  • Tai, C. S. (2007). Market integration and contagion: Evidence from Asian emerging stock and foreign exchange markets. Emerging markets review, 8(4), 264-283.
  • Temiz Dinç, D., & Akdoğan, E. C. (2019). Renewable energy production, energy consumption and sustainable economic growth in Turkey: A VECM approach. Sustainability, 11(5), 1-14.
  • Umar, M., Mirza, N., Rizvi, S. K. A., & Furqan, M. (2021). Asymmetric volatility structure of equity returns: Evidence from an emerging market. The Quarterly Review of Economics and Finance. https://doi.org/10.1016/j.qref.2021.04.016.
  • Vidanage, T. N., Carmignani, F., & Singh, T. (2017). Predictability of return volatility across different emerging capital markets: Evidence from Asia. South Asian Journal of Macroeconomics and Public Finance, 6(2), 157-177.
  • Vo, X. V., & Tran, T. T. A. (2020). Modelling volatility spillovers from the US equity market to ASEAN stock markets. Pacific-Basin Finance Journal, 59, 1-8.
  • Wang, P., Wang, P., & Liu, A. (2005). Stock return volatility and trading volume: Evidence from the Chinese Stock Market. Journal of Chinese Economic and Business Studies, 3(1), 39-54.
  • Yıldırım, D., & Çelik, A. K. (2020). Stock market volatility and structural breaks: An empirical analysis of fragile five countries using GARCH and EGARCH models. Journal of Applied Economics and Business Research, 10(3), 148-163.
There are 35 citations in total.

Details

Primary Language English
Subjects Finance
Journal Section Articles
Authors

Anıl Lögün 0000-0003-2543-3964

Publication Date January 2, 2023
Submission Date May 18, 2022
Published in Issue Year 2023 Volume: 10 Issue: 1

Cite

APA Lögün, A. (2023). STOCK MARKET VOLATILITY AND TRADING VOLUME IN MINT MARKETS: EVIDENCE FROM COVID 19 PANDEMIC PERİOD. Optimum Ekonomi Ve Yönetim Bilimleri Dergisi, 10(1), 39-48.
AMA Lögün A. STOCK MARKET VOLATILITY AND TRADING VOLUME IN MINT MARKETS: EVIDENCE FROM COVID 19 PANDEMIC PERİOD. OJEMS. January 2023;10(1):39-48.
Chicago Lögün, Anıl. “STOCK MARKET VOLATILITY AND TRADING VOLUME IN MINT MARKETS: EVIDENCE FROM COVID 19 PANDEMIC PERİOD”. Optimum Ekonomi Ve Yönetim Bilimleri Dergisi 10, no. 1 (January 2023): 39-48.
EndNote Lögün A (January 1, 2023) STOCK MARKET VOLATILITY AND TRADING VOLUME IN MINT MARKETS: EVIDENCE FROM COVID 19 PANDEMIC PERİOD. Optimum Ekonomi ve Yönetim Bilimleri Dergisi 10 1 39–48.
IEEE A. Lögün, “STOCK MARKET VOLATILITY AND TRADING VOLUME IN MINT MARKETS: EVIDENCE FROM COVID 19 PANDEMIC PERİOD”, OJEMS, vol. 10, no. 1, pp. 39–48, 2023.
ISNAD Lögün, Anıl. “STOCK MARKET VOLATILITY AND TRADING VOLUME IN MINT MARKETS: EVIDENCE FROM COVID 19 PANDEMIC PERİOD”. Optimum Ekonomi ve Yönetim Bilimleri Dergisi 10/1 (January 2023), 39-48.
JAMA Lögün A. STOCK MARKET VOLATILITY AND TRADING VOLUME IN MINT MARKETS: EVIDENCE FROM COVID 19 PANDEMIC PERİOD. OJEMS. 2023;10:39–48.
MLA Lögün, Anıl. “STOCK MARKET VOLATILITY AND TRADING VOLUME IN MINT MARKETS: EVIDENCE FROM COVID 19 PANDEMIC PERİOD”. Optimum Ekonomi Ve Yönetim Bilimleri Dergisi, vol. 10, no. 1, 2023, pp. 39-48.
Vancouver Lögün A. STOCK MARKET VOLATILITY AND TRADING VOLUME IN MINT MARKETS: EVIDENCE FROM COVID 19 PANDEMIC PERİOD. OJEMS. 2023;10(1):39-48.

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