ASYMMETRIC VOLATILITY SPILLOVER FROM RETAIL TRADING OF NOISE TRADERS: EVIDENCE FROM THE GAMESTOP SHORT SQUEEZE

Year 2023, , 33 - 38, 01.02.2023

Semra Bank Zehra Abdıoglu

https://doi.org/10.17261/Pressacademia.2023.1661

Abstract

Purpose-Recently, it has been observed that social trading and social media-based stocks are very popular especially for retail investors in the financial world. However, coordinated transactions of retail investors through social platforms carry the risk of classical noise trading, and the noise-based transactions of these investors, described as irrational investors, constitute a new source of systematic risk in the market. Considering the mentioned issues, this study aims to reveal the volatility and asymmetric volatility effects of social media-based noise trading of retail investors through the recent GameStop short squeeze.
Methodology-The volatility and asymmetrical volatility spillovers from the social media-based retail transactions of the noise traders to the stock market were investigated using the EGARCH method, following Verma and Verma (2007), on the GameStop short position squeeze case.
Findings-In the study, positive and statistically significant volatility spillover coefficient representing the spillover effect of the volatility in the GME index towards the NYSE Composite index and a negative and significant asymmetry coefficient revealed that the volatility spread from the GME index to the NYSE Composite index was asymmetrical. In this context, negative shocks in the GME index have a greater impact on the volatility of the NYSE Composite index than positive shocks. In addition, the findings of the study showed that there was no asymmetric volatility spillover from the NYSE Composite index to the GME index, and that past volatility in the GME index had a greater impact on present conditional volatility than the NYSE Composite index.
Conclusion-This study determined that there was an asymmetrical volatility spillover from the GME index to the NYSE Composite index, and revealed that the social media-based retail transactions of noise traders may have not only volatility but also asymmetric volatility spillover effects in the markets.

Keywords

GameStop, meme stocks, noise traders, retail trading, social media, asymmetric volatility, Meme Hisseler, Gürültü Tacirleri, Perakende Ticaret, Sosyal Medya, Asimetrik Volatilite

GÜRÜLTÜ TACİRLERİNİN PERAKENDE İŞLEMLERİNİN ASİMETRİK VOLATİLİTE YAYILIMLARI: GAMESTOP KISA POZİSYON SIKIŞMASI ÖRNEĞİ

Abstract

Amaç-Son zamanlarda finans dünyasında özellikle perakende yatırımcılar için sosyal ticaretin ve bu kapsamda sosyal medya kaynaklı hisselerin oldukça popüler olduğu gözlenmektedir. Bununla birlikte, perakende yatırımcıların sosyal platformlar aracılığıyla gerçekleştirdikleri koordineli işlemler klasik gürültü ticareti riski taşımaktadır ve irrasyonel yatırımcılar olarak nitelendirilen bu yatırımcıların gürültüye dayalı işlemleri piyasada yeni bir sistematik risk kaynağı teşkil etmektedir. Bu çalışma, belirtilen hususları dikkate alarak, perakende yatırımcıların sosyal medya kaynaklı gürültü ticareti işlemlerinin pay piyasalarındaki volatilite ve asimetrik volatilite etkilerini yakın zamandaki GameStop kısa pozisyon sıkışması vakası üzerinden ortaya koymayı amaçlamaktadır.
Yöntem-Gürültü tacirlerinin sosyal medya kaynaklı perakende işlemlerinden pay piyasasına olan volatilite ve asimetrik volatilite yayılımları GME kısa pozisyon sıkışması vakası üzerinden,Verma ve Verma (2007) takip edilerek EGARCH yöntemi aracılığıyla araştırılmıştır.
Bulgular -Çalışmada, GME endeksindeki oynaklığın NYSE Composite endeksine doğru yayılım etkisini temsil eden pozitif ve istatistiksel olarak anlamlı oynaklık yayılımı katsayısı ile negatif ve anlamlı asimetri katsayısı GME endeksinden NYSE Composite endeksine doğru oynaklık yayılımının asimetrik olduğunu ortaya koymuştur. Buna göre; GME endeksindeki negatif şoklar NYSE Composite endeksindeki oynaklık üzerinde pozitif şoklardan daha büyük bir etkiye sahip olmaktadır. Bunun yanı sıra, çalışma bulguları NYSE Composite endeksinden GME endeksine doğru asimetrik oynaklık yayılımının gerçekleşmediğini ve GME endeksinde geçmiş dönemdeki oynaklıkların bugünkü koşullu oynaklıklar üzerinde NYSE Composite endeksine göre daha büyük bir etkiye sahip olduğunu göstermiştir.
Sonuç-Çalışma GME endeksinden NYSE Composite endeksine doğru asimetrik oynaklık yayılımının gerçekleştiğini tespit ederek, gürültü tacirlerinin sosyal medya kaynaklı perakende işlemlerinin piyasalarda yalnızca volatilite değil asimetrik volatilite yayılım etkilerinin de olabileceğini ortaya koymuştur.

Keywords

Meme Hisseler, Gürültü Tacirleri, Perakende Ticaret, Sosyal Medya, Asimetrik Volatilite

References

• Allen, F., Haas, M., Nowak, E., Pirovano, M., Tengulov, A., (2022). Squeezing Shorts Through Social Media Platforms Swiss Finance Institute Research Paper No. 21-31, https://ssrn.com/abstract=3823151 or http://dx.doi.org/10.2139/ssrn.3823151
• Aloosh, A., Choi, H.-E., Ouzan, S., (2021). Meme Stocks and Herd Behavior. https://ssrn.com/abstract=3909945 or http://dx.doi.org/10.2139/ssrn.3909945
• Aloosh, A. and Choi, H.-E., Ouzan, S., (2022). The Tail Wagging the Dog: How Do Meme Stocks Affect Market Efficiency? https://ssrn.com/abstract=3839832 or http://dx.doi.org/10.2139/ssrn.3839832
• 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. The Review of Financial Studies, 21(2), 785-818.
• Black, F., (1986). Noise. Journal of Finance, 41(3), 529-543.
• Bloomfield, R. J., O'Hara, M., Saar, G., (2007). How Noise Trading Affects Markets: An Experimental Analysis. https://ssrn.com/abstract=994379 or http://dx.doi.org/10.2139/ssrn.994379
• Brown, G.W., (1999). Volatility, sentiment, and noise traders. Financial Analysts Journal, 55(2), 82-90.
• Cooper, J., (2021). Retail Trading and Stock Volatility: The Case of Robinhood. All Graduate Plan B and other Reports. 1534. https://digitalcommons.usu.edu/gradreports/1534
• Costola, M., Iacopini, M., Santagiustina, C.R.M.A., (2021). On the “mementum” of meme stocks. Economic Letters, 207, 110021. https://doi.org/10.1016/J.ECONLET.2021.110021
• De Long, J.B., Shleifer, A., Summers, L.H., Waldmann, R.J (1989). The size and ıncidence of the losses from noise trading. Journal of Finance, 44(3) 681–696.
• De Long, J.B., Shleifer, A., Summers, L.H., Waldmann, R.J., (1990a.) Noise trader risk in financial markets. Journal of Political Economics, 98(4), 703–738.
• De Long, J.B., Shleifer, A., Summers, L.H., Waldmann, R.J (1990b). Positive feedback ınvestment strategies and destabilizing rational speculation. Journal of Finance, 45(2), 379–396.
• Dickey, D. A. ve Fuller, W. A., (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association, 74(366), 427-431.
• Koutmos, G., Booth, G.G., (1995). Asymmetries in the conditional mean and the conditional variance: evidence from nine stock markets. Journal of Economics and Business, 50, 277–290.
• Koutmos, G.G., (1998). Asymmetric volatility transmission in international stock markets. Journal of International Money and Finance, 14, 747–762.
• Kyle, A., (1985). Continuous Auctions and Insider Trading. Econometrica, 53(6), 1315-1335.
• Li, S., (2022). Spillovers between Bitcoin and Meme stocks. Finance Research Letters, 50, 103218, https://doi.org/10.1016/j.frl.2022.103218
• Nelson, D. B., (1991). Conditional heteroskedasticity in asset returns: a new approach. Econometrica, 59, 347-370.
• Ozik, G., Sadka, R., Shen, S. (2021). Flattening the ılliquidity curve: retail trading during the COVID-19 lockdown. Journal of Financial and Quantitative Analysis, 56(7), 2356-2388.
• Pagano, M. S., Sedunov, J., Velthuis, R., (2021).How did retail investors respond to the COVID-19 pandemic? The effect of Robinhood brokerage customers on market quality. Finance Research Letters, 43, 101946, https://doi.org/10.1016/j.frl.2021.101946
• Phillips, C.B. P. ve Perron, P. , (1988). Testing for a unit root in time series regressions. Biometrika, 75(2), 335-346.
• Shiller, R. J., (1984). Stock Prices and Social Dynamics, Brookings Papers on Economic Activity, 2, 457-510.
• Shiller, R. J., (1990). Speculative prices and popular models. Journal of Economic Perspective, 4, 55-65.
• Shleifer, A., Summers, L., (1990). The noise trader approach to finance. Journal of Economic Perspectives, 4(2), 19-33.
• Umar, Z., Yousaf, I., Zaremba, A., (2021). Comovements between heavily shorted stocks during a market squeeze: Lessons from the GameStop trading frenzy. Research in International Business and Finance, 58, 101453, https://doi.org/10.1016/j.ribaf.2021.101453
• Verma, R., Verma, P., (2007).Noise trading and stock market volatility, Journal of Multinational Financial Management, 17, 231–243.
• Wohlgemuth, V., Berger, E.S.C., Wenzel, M., (2016). More than just financial performance: Trusting investors in social trading. Journal of Business Research, 69, 4970–4974.
• Ye, L., Tan,Y.-M., (2021),. Noise trader risk-evidence from China’s stock market. Capital Markets Review, 29(1), 59-72.