Abstract
Purpose- The purpose of this study is to determine the short-term impact of various types of investors on each other. Secondly, it tries to understand whether COVID-19 had a significant change in the relationship between these investors.
Methodology- Based on the transactions data, the study classifies investor groups such as fast and slow traders, domestic and foreign investors, bank-based and non-bank based brokers. Then, it employs a panel vector autoregression model in order to find any reciprocal relation.
Findings- The analysis reveals that, with the start of the pandemic, the impact of intraday returns on investors and the response of slow foreign investors to market returns did not change very much. On the other hand, the response of other investors such as retail/professional or fast/slow domestic investors as well as fast foreign investors significantly altered.
Conclusion- Based upon the empirical analysis, it may be concluded that different types of investors have positive or negative impact on each other and investor behavior has been seriously affected by COVID-19.
References
- Arellano, M., and Bover, O. (1995). Another look at the instrumental variable estimation of error-components models. Journal of Econometrics, 68(1), 29-51.
- Barber, B.M., and Odean, T. (2008). All that glitters: The effect of attention and news on the buying behavior of individual and institutional investors. Review of Financial Studies, 21(2), 785-818.
- Bekiros, S., Jlassi, M., Lucey, B., Naoui, K., and Uddin, G.S. (2017). Herding behavior, market sentiment and volatility: Will the bubble resume? North American Journal of Economics and Finance, 42, 107-131.
- Choe, H., Kho, B.C., and Stulz, R.M. (1999). Do foreign investors destabilize stock markets? The Korean experience in 1997. Journal of Financial Economics, 54(2), 227-264.
- Coval, J.D. and Moskowitz, T.J. (1999). Home bias at home: Local equity preference in domestic portfolios. Journal of Finance, 54(6), 2045-2073.
- Dvorak, T. (2005). Do domestic investors have an information advantage? Evidence from Indonesia. Journal of Finance, 60(2), 817-839.
- Griffin, J.M., Harris, J.H., and Topaloglu, S. (2003). The dynamics of institutional and individual trading. Journal of Finance, 58(6), 2285-2320.
- Grinblatt, M. and Keloharju, M. (2000). The investment behavior and performance of various investor types: a study of Finland’s unique data set. Journal of Financial Economics, 55(1), 43-67.
- Hasbrouck, J. (2018). High-Frequency Quoting: Short-Term Volatility in Bids and Offers. Journal of Financial and Quantitative Analysis, 53(2), 613-641.
- Kirilenko, A., Kyle, A.S., Samadi, M., and Tuzun, T. (2017). The flash crash: High-frequency trading in an electronic market. Journal of Finance, 72(3), 967-998.
- Kumar, A. and Lee, C.M. (2006). Retail investor sentiment and return comovements. Journal of Finance, 61(5), 2451-2486
Abstract
References
- Arellano, M., and Bover, O. (1995). Another look at the instrumental variable estimation of error-components models. Journal of Econometrics, 68(1), 29-51.
- Barber, B.M., and Odean, T. (2008). All that glitters: The effect of attention and news on the buying behavior of individual and institutional investors. Review of Financial Studies, 21(2), 785-818.
- Bekiros, S., Jlassi, M., Lucey, B., Naoui, K., and Uddin, G.S. (2017). Herding behavior, market sentiment and volatility: Will the bubble resume? North American Journal of Economics and Finance, 42, 107-131.
- Choe, H., Kho, B.C., and Stulz, R.M. (1999). Do foreign investors destabilize stock markets? The Korean experience in 1997. Journal of Financial Economics, 54(2), 227-264.
- Coval, J.D. and Moskowitz, T.J. (1999). Home bias at home: Local equity preference in domestic portfolios. Journal of Finance, 54(6), 2045-2073.
- Dvorak, T. (2005). Do domestic investors have an information advantage? Evidence from Indonesia. Journal of Finance, 60(2), 817-839.
- Griffin, J.M., Harris, J.H., and Topaloglu, S. (2003). The dynamics of institutional and individual trading. Journal of Finance, 58(6), 2285-2320.
- Grinblatt, M. and Keloharju, M. (2000). The investment behavior and performance of various investor types: a study of Finland’s unique data set. Journal of Financial Economics, 55(1), 43-67.
- Hasbrouck, J. (2018). High-Frequency Quoting: Short-Term Volatility in Bids and Offers. Journal of Financial and Quantitative Analysis, 53(2), 613-641.
- Kirilenko, A., Kyle, A.S., Samadi, M., and Tuzun, T. (2017). The flash crash: High-frequency trading in an electronic market. Journal of Finance, 72(3), 967-998.
- Kumar, A. and Lee, C.M. (2006). Retail investor sentiment and return comovements. Journal of Finance, 61(5), 2451-2486
Details
| Primary Language | English |
|---|---|
| Subjects | Finance, Business Administration |
| Journal Section | Articles |
| Authors | |
| Publication Date | July 30, 2021 |
| Published in Issue | Year 2021 Volume: 13 Issue: 1 |
Cite
PressAcademia Procedia (PAP) publishes proceedings of conferences, seminars and symposiums. PressAcademia Procedia aims to provide a source for academic researchers, practitioners and policy makers in the area of social and behavioral sciences, and engineering.
PressAcademia Procedia invites academic conferences for publishing their proceedings with a review of editorial board. Since PressAcademia Procedia is an double blind peer-reviewed open-access book, the manuscripts presented in the conferences can easily be reached by numerous researchers. Hence, PressAcademia Procedia increases the value of your conference for your participants.
PressAcademia Procedia provides an ISBN for each Conference Proceeding Book and a DOI number for each manuscript published in this book.
PressAcademia Procedia is currently indexed by DRJI, J-Gate, International Scientific Indexing, ISRA, Root Indexing, SOBIAD, Scope, EuroPub, Journal Factor Indexing and InfoBase Indexing.
Please contact to procedia@pressacademia.org for your conference proceedings.