Whales And Retail Attention: Dual Channels of Bitcoin Return Dynamics

Öz

This study examines how whale transactions and investor attention affect Bitcoin returns. An event-study framework with forward cumulative abnormal returns over 1, 7, 14, and 28 days is applied using 2,647 daily observations from January 2018 to March 2025. Data are obtained from on-chain statistics for the top 100 non-custodial wallets and normalized Google Trends. Whale activity generates statistically and economically significant effects, with event-day returns exceeding non-event days by 0.79% (7 days), 1.66% (14 days), and 2.44% (28 days). Attention shocks adjust more slowly, showing no immediate impact but return increases of 1.76% after 14 days and 2.36% after 28 days. Overall, Bitcoin price formation operates through two channels: large-holder order flow and retail-driven attention.

Anahtar Kelimeler

• Bitcoin
• Whale transactions
• Investor attention

Destekleyen Kurum

The author declares that this research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Etik Beyan

This study does not involve any human participants, animals, or personal data. All data used in the analysis are obtained from publicly available sources. Therefore, ethical committee approval is not required.

Balinalar ve Perakende Yatırımcı Dikkati: Bitcoin Getiri Dinamiklerinde İkili Kanallar

Öz

Bu çalışma, balina işlemlerinin ve yatırımcı dikkatinin Bitcoin getirileri üzerindeki etkilerini incelemektedir. 2018 Ocak–2025 Mart dönemine ait 2.647 günlük gözlem kullanılarak, 1, 7, 14 ve 28 gün sonrası ileriye dönük kümülatif anormal getiriler üzerinden bir olay çalışması yöntemi uygulanmıştır. Veriler, ilk 100 saklama dışı cüzdana ait zincir üstü istatistikler ile normalize edilmiş Google Trends verilerinden elde edilmiştir. Balina faaliyetlerinin ekonomik ve istatistiksel olarak anlamlı etkiler ürettiği, olay günlerinde getirilerin sırasıyla %0,79 (7 gün), %1,66 (14 gün) ve %2,44 (28 gün) daha yüksek olduğu tespit edilmiştir. Dikkat şokları anlık bir etki göstermemekte, daha gecikmeli biçimde 14 ve 28 gün ufuklarında sırasıyla %1,76 ve %2,36 oranında artışlara yol açmaktadır. Bulgular, Bitcoin fiyat oluşumunun büyük yatırımcı işlemleri ve perakende yatırımcı dikkati olmak üzere iki kanaldan gerçekleştiğini göstermektedir.

Anahtar Kelimeler

• Bitcoin
• Balina işlemleri
• Yatırımcı dikkati

Destekleyen Kurum

Bu araştırma, kamu, ticari veya kâr amacı gütmeyen herhangi bir kurumdan mali destek almamıştır.

Etik Beyan

Bu çalışma insan katılımcılar, hayvanlar veya kişisel veri içermemektedir. Çalışmada kullanılan tüm veriler herkese açık ve ikincil veri kaynaklarından elde edilmiştir. Bu nedenle etik kurul onayına ihtiyaç duyulmamaktadır.

Kaynakça

1. Azamjon, M., Sattarov, O., & Cho, J. (2023). Forecasting Bitcoin volatility through on-chain and Whale-Alert tweet analysis using the Q-learning algorithm. IEEE Access, 11, 108092–108103. https://doi.org/10.1109/ACCESS.2023.3317899
2. Baur, D. G., & Dimpfl, T. (2021). The volatility of Bitcoin and its role as a medium of exchange and a store of value. Empirical Economics, 61, 2663–2683. https://doi.org/10.1007/s00181-020-01990-5
3. BitInfoCharts. (2025). Top 100 richest Bitcoin addresses. Retrieved March 31, 2025, from https://bitinfocharts.com/top-100-richest-bitcoin-addresses.html
4. Bleher, J., & Dimpfl, T. (2019). Today I got a million, tomorrow I don't know: On the predictability of cryptocurrencies by means of Google search volume. International Review of Financial Analysis, 63, 147–159. https://doi.org/10.1016/j.irfa.2019.03.003
5. Bodnaruk, A., & Östberg, P. (2009). Does investor recognition predict returns? Journal of Financial Economics, 91(2), 208–226. https://doi.org/10.1016/j.jfineco.2008.01.006
6. Bouoiyour, J., Selmi, R., & Tiwari, A. K. (2015). Is Bitcoin business income or speculative foolery? New ideas through an improved frequency domain analysis. Annals of Financial Economics, 10(1), Article 1550002. https://doi.org/10.1142/S2010495215500025
7. Brandvold, M., Molnár, P., Vagstad, K., & Valstad, O. C. A. (2015). Price discovery on Bitcoin exchanges. Journal of International Financial Markets, Institutions and Money, 36, 18–35. https://doi.org/10.1016/j.intfin.2015.02.010
8. Campbell, J. Y., Lo, A. W., & MacKinlay, A. C. (1997). The econometrics of financial markets. Princeton University Press.

9. Cheah, E.-T., & Fry, J. (2015). Speculative bubbles in Bitcoin markets? An empirical investigation into the fundamental value of Bitcoin. Economics Letters, 130, 32–36. https://doi.org/10.1016/j.econlet.2015.02.029
10. Conti, M., Kumar, E. S., Lal, C., & Ruj, S. (2018). A survey on security and privacy issues of Bitcoin. IEEE Communications Surveys & Tutorials, 20(4), 3416–3452. https://doi.org/10.1109/COMST.2018.2842460
11. Cretarola, A., & Figà-Talamanca, G. (2021). Detecting bubbles in Bitcoin price dynamics via market exuberance. Annals of Operations Research, 299(1–2), 459–479. https://doi.org/10.1007/s10479-019-03321-z
12. Da, Z., Engelberg, J., & Gao, P. (2011). In search of attention. The Journal of Finance, 66(5), 1461–1499. https://doi.org/10.1111/j.1540-6261.2011.01679.x
13. Dastgir, S., Demir, E., Downing, G., Gozgor, G., & Lau, C. K. M. (2019). The causal relationship between Bitcoin attention and Bitcoin returns: Evidence from the Copula-based Granger causality test. Finance Research Letters, 28, 160–164. https://doi.org/10.1016/j.frl.2018.04.019
14. Dulupçu, M. A., Yiyit, M., & Genç, A. G. (2017). Dijital ekonominin yükselen yüzü: Bitcoin'in değeri ile bilinirliği arasındaki ilişkinin analizi. Süleyman Demirel Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 22(4), 2241–2256.
15. Feng, W., Wang, Y., & Zhang, Z. (2018). Informed trading in the Bitcoin market. Finance Research Letters, 26, 63–70. https://doi.org/10.1016/j.frl.2017.11.009
16. Foster, F. D., & Viswanathan, S. (1996). Strategic trading when agents forecast the forecasts of others. The Journal of Finance, 51(4), 1437–1478. https://doi.org/10.1111/j.1540-6261.1996.tb04075.x
17. Garcia, D., Tessone, C. J., Mavrodiev, P., & Perony, N. (2014). The digital traces of bubbles: Feedback cycles between socio-economic signals in the Bitcoin economy. Journal of the Royal Society Interface, 11(99), 20140623. https://doi.org/10.1098/rsif.2014.0623
18. Glaser, F., Zimmermann, K., Haferkorn, M., Weber, M. C., & Siering, M. (2014). Bitcoin: Asset or currency? Revealing users' hidden intentions. In Proceedings of the 22nd European Conference on Information Systems (ECIS 2014). https://ssrn.com/abstract=2425247
19. Grossman, S. J., & Stiglitz, J. E. (1980). On the impossibility of informationally efficient markets. American Economic Review, 70(3), 393–408.
20. Herremans, D., & Low, K. W. (2025). Forecasting Bitcoin volatility spikes from whale transactions and CryptoQuant data using Synthesizer Transformer models. IEEE Access, 13, 117788–117807. https://doi.org/10.1109/ACCESS.2025.3584243
21. Kapar, B., & Olmo, J. (2021). Analysis of Bitcoin prices using market and sentiment variables. The World Economy, 44(1), 45–63. https://doi.org/10.1111/twec.13020
22. Kim, G., Shin, D.-H., Choi, J. G., & Lim, S. (2022). A deep learning-based cryptocurrency price prediction model that uses on-chain data. IEEE Access, 10, 56232–56248. https://doi.org/10.1109/ACCESS.2022.3177888
23. Kothari, S. P., & Warner, J. B. (2007). Econometrics of event studies. In B. E. Eckbo (Ed.), Handbook of corporate finance: Empirical corporate finance (Vol. 1, pp. 3–36). Elsevier. https://doi.org/10.1016/B978-0-444-53265-7.50015-9
24. Kristoufek, L. (2013). Bitcoin meets Google Trends and Wikipedia: Quantifying the relationship between phenomena of the Internet era. Scientific Reports, 3, 3415. https://doi.org/10.1038/srep03415
25. Kristoufek, L. (2015). What are the main drivers of the Bitcoin price? Evidence from wavelet coherence analysis. PLoS ONE, 10(4), e0123923. https://doi.org/10.1371/journal.pone.0123923
26. Kyle, A. S. (1985). Continuous auctions and insider trading. Econometrica, 53(6), 1315–1335. https://doi.org/10.2307/1913210
27. Long, S., Xie, Y., Zhou, Z., Lucey, B. M., & Urquhart, A. (2025). From whales to waves: Social media sentiment, volatility, and whales in cryptocurrency markets. The British Accounting Review, Article 101682. Advance online publication. https://doi.org/10.1016/j.bar.2025.101682
28. Mai, F., Shan, Z., Bai, Q., Wang, X., & Chiang, R. H. L. (2018). How does social media impact Bitcoin value? A test of the silent majority hypothesis. Journal of Management Information Systems, 35(1), 19–52. https://doi.org/10.1080/07421222.2018.1440774
29. Makarov, I., & Schoar, A. (2020). Trading and arbitrage in cryptocurrency markets. Journal of Financial Economics, 135(2), 293–319. https://doi.org/10.1016/j.jfineco.2019.07.001
30. Merton, R. C. (1987). A simple model of capital market equilibrium with incomplete information. The Journal of Finance, 42(3), 483–510. https://doi.org/10.1111/j.1540-6261.1987.tb04565.x
31. Mittal, A., Dhiman, V., Singh, A., & Prakash, C. (2019). Short-term Bitcoin price fluctuation prediction using social media and web search data. In 2019 12th International Conference on Contemporary Computing (IC3) (pp. 1–6). IEEE. https://doi.org/10.1109/IC3.2019.8844899
32. Nakamoto, S. (2008). Bitcoin: A peer-to-peer electronic cash system. https://bitcoin.org/bitcoin.pdf
33. Nasir, M. A., Huynh, T. L. D., Nguyen, S. P., & Duong, D. (2019). Forecasting cryptocurrency returns and volume using search engines. Financial Innovation, 5(1), Article 2. https://doi.org/10.1186/s40854-018-0119-8
34. Polasik, M., Piotrowska, A. I., Wisniewski, T. P., Kotkowski, R., & Lightfoot, G. (2015). Price fluctuations and the use of Bitcoin: An empirical inquiry. International Journal of Electronic Commerce, 20(1), 9–49. https://doi.org/10.1080/10864415.2016.1061413
35. Saggu, A. (2022). The intraday Bitcoin response to Tether minting and burning events: Asymmetry, investor sentiment, and "Whale Alerts" on Twitter. Finance Research Letters, 49, Article 103096. https://doi.org/10.1016/j.frl.2022.103096
36. Shen, D., & Shi, G. (2025). The role of whale investors in the Bitcoin market. Research in International Business and Finance, 78, Article 103008. https://doi.org/10.1016/j.ribaf.2025.103008
37. Urquhart, A. (2018). What causes the attention of Bitcoin? Economics Letters, 166, 40–44. https://doi.org/10.1016/j.econlet.2018.02.017
38. Uzun, M. (2024). The examination of the relationship between Bitcoin (BTC) trading volume in Türkiye and Google Trends data on Bitcoin searches in Google search engine. Fiscaoeconomia, 8(2), 720–738. https://doi.org/10.25295/fsecon.1420143
39. Yıldırım, Ç. (2020). Google Trends "Bitcoin" aramaları ile Bitcoin/USD fiyatları arasındaki ilişkinin analizi: ARDL sınır testi. Bilgi Ekonomisi ve Yönetimi Dergisi, 15(2), 99–113.