Pengaruh Google Trend dan Variabel Makroekonomi Terhadap Harga, Return, dan Volume Perdagangan Bitcoin

Dewi Indriyani(1*), Berto Usman(2),

(1) Universitas Bengkulu
(2) Universitas Bengkulu
(*) Corresponding Author




DOI: https://doi.org/10.26858/jekpend.v7i1.56193

Abstract


This research aims to understand whether Google searches can wield significant influence on Bitcoin prices, returns, and trading volume, thereby capturing investors' attention towards the Bitcoin cryptocurrency. Additionally, Bitcoin returns signify profits or losses arising from Bitcoin investments, while Bitcoin trading volume serves as an indicator of liquidity and market activity. The research methodology involves the analysis of historical Google Search Volume (GSV) data related to Bitcoin keywords, along with price, return, and trading volume data over a specific period. The subject of this research is Bitcoin, and the analytical method employed is a time series data regression model. The results of this research reveal that Google Trends have a positive and significant impact on Bitcoin. However, this impact does not always translate into an immediate change in Bitcoin returns. Furthermore, an increased interest in favorable information about a stock can attract buying interest, likely manifested in a rise in Bitcoin trading volume.


Keywords


Cryptocurrency; Google Search Volume

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References


Abraham, J., Higdon, D., Nelson, J., Ibarra, J., Abraham, J. ;, Higdon, D. ;, Nelson, J. ;, & Nelson, J. (2018). Cryptocurrency Price Prediction Using Tweet Volumes and Sentiment Analysis. In SMU Data Science Review (Vol. 1, Issue 3). https://scholar.smu.edu/datasciencereviewAvailableat:https://scholar.smu.edu/datasciencereview/vol1/iss3/1http://digitalrepository.smu.edu.

Arratia, A., & López-Barrantes, A. X. (2021). Do Google Trends forecast bitcoins? Stylized facts and statistical evidence. Journal of Banking and Financial Technology. https://doi.org/10.1007/s42786-021-00027-4

Aslanidis, N., Bariviera, A. F., & López, Ó. G. (2022). The link between cryptocurrencies and Google Trends attention. Finance Research Letters, 47. https://doi.org/10.1016/j.frl.2021.102654

Bańbura, M., Belousova, I., Bodnár, K., & Tóth, M. B. (2023). Working Paper Series Nowcasting employment in the euro area No 2815. https://doi.org/10.2866/634513

Bank, M., Larch, M., & Peter, G. (2011). Google search volume and its influence on liquidity and returns of German stocks. Financial Markets and Portfolio Management, 25(3), 239–264. https://doi.org/10.1007/s11408-011-0165-y

Barber, B. M., & 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. https://doi.org/10.1093/rfs/hhm079

Bijl, L., Kringhaug, G., Molnár, P., & Sandvik, E. (2016). Google searches and stock returns. International Review of Financial Analysis, 45, 150–156. https://doi.org/10.1016/j.irfa.2016.03.015

Challet, D., & Bel Hadj Ayed, A. (2013). Predicting Financial Markets with Google Trends and Not so Random Keywords. SSRN Electronic Journal, 1–9. https://doi.org/10.2139/ssrn.2310621

Chen, S. (2011). Google Search Volume: Influence and Indication for the Dutch Stock Market.

Da, Z., Engelberg, J., & Gao, P. (2011). In Search of Attention. Journal of Finance, 66(5), 1461–1499. https://doi.org/10.1111/j.1540-6261.2011.01679.x

Dash, S., Shakyawar, S. K., Sharma, M., & Kaushik, S. (2019). Big data in healthcare: management, analysis and future prospects. Journal of Big Data, 6(1). https://doi.org/10.1186/s40537-019-0217-0

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

Fadhel, R., Adrianto, F., & Alfarisi, M. F. (2022). Analisis Sentimen Investor terhadap kinerja saham syariah di Indonesia selama masa pandemi Covid-19. Owner, 6(4), 3579–3591. https://doi.org/10.33395/owner.v6i4.1183

Fink, C., & Johann, T. (2012). May I Have Your Attention, Please: The Market Microstructure of Investor Attention. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.2139313

Joseph, K., Babajide Wintoki, M., & Zhang, Z. (2011). Forecasting abnormal stock returns and trading volume using investor sentiment: Evidence from online search. International Journal of Forecasting, 27(4), 1116–1127. https://doi.org/10.1016/j.ijforecast.2010.11.001

Khan, M. A., Hernandez, J. A., & Shahzad, S. J. H. (2020). Time and frequency relationship between household investors’ sentiment index and US industry stock returns. Finance Research Letters, 36, 101318. https://doi.org/10.1016/j.frl.2019.101318

Kristoufek, L. (2013). BitCoin meets Google Trends and Wikipedia: Quantifying the relationship between phenomena of the Internet era. Scientific Reports, 3, 1–7. https://doi.org/10.1038/srep03415

Liu, Y., & Tsyvinski, A. (2021). Risks and returns of cryptocurrency. Review of Financial Studies, 34(6), 2689–2727. https://doi.org/10.1093/rfs/hhaa113

Livaic, T., & Perisic, A. (2019). What can Google Tell us about Bitcoin Trading Volume in Croatia? Evidence from the Online Marketplace Localbitcoins. Interdisciplinary Description of Complex Systems, 17(4), 707–715. https://doi.org/10.7906/indecs.17.4.2

Lyócsa, Š., Molnár, P., Plíhal, T., & Širaňová, M. (2020). Impact of macroeconomic news, regulation and hacking exchange markets on the volatility of bitcoin. Journal of Economic Dynamics and Control, 119. https://doi.org/10.1016/j.jedc.2020.103980

Padhila, P. H., Cholissodin, I., & Adikara, P. P. (2022). Prediksi Harga Bitcoin berdasarkan Data Historis Harian dan Google Trend Index menggunakan Algoritme Extreme Learning Machine (Vol. 6, Issue 7). http://j-ptiik.ub.ac.id

Pattiruhu, J. R., Ferdinandus, S. J., Seleky, R., & Wenno, M. (2022). Pengaruh Asimetri Informasi, Ukuran Perusahaan dan Kepemilikan Manajerial terhadap Praktik Manajemen Laba pada Perusahaan Manufaktur di BEI. Jurnal Pendidikan Dan Konseling, 4(6), 4487–4497.

Paulus, R. N., Kananlua, S., & Usman, B. (2015). The Effect of Google Trend as Determinant of Return and Liquidity in Indonesia Stock Exchange (Kesan Google Trend sebagai Penentu Pulangan dan Kecairan di Bursa Saham Indonesia). In Jurnal Pengurusan (Vol. 45).

Preis, T., Moat, H. S., & Eugene Stanley, H. (2013). Quantifying trading behavior in financial markets using google trends. Scientific Reports, 3. https://doi.org/10.1038/srep01684

Preis, T., Reith, D., & Stanley, H. E. (2010). Complex dynamics of our economic life on different scales: Insights from search engine query data. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 368(1933), 5707–5719. https://doi.org/10.1098/rsta.2010.0284

Rustyawati, D., & Artikel, R. (2021). Cryptocurrency: Sejarah dan Perkembangannya INFO ARTIKEL ABSTRAK. In JIB-Jurnal Perbankan Syariah.

Schilling, L., & Uhlig, H. (2019). Some simple bitcoin economics. Journal of Monetary Economics, 106, 16–26. https://doi.org/10.1016/j.jmoneco.2019.07.002

Syamsiah, N. O. (2017). Kajian atas cryptocurrency sebagai alat pembayaran di Indonesia. In ijns.org Indonesian Journal on Networking and Security (Vol. 6). Online.

Szetela, B., Mentel, G., Bilan, Y., & Mentel, U. (2021). The relationship between trend and volume on the bitcoin market. Eurasian Economic Review, 11(1), 25–42. https://doi.org/10.1007/s40822-021-00166-5

Usman, B., Afandy, C., & Zoraya, I. (2022). PERHATIAN INVESTOR DAN LIKUIDITAS SAHAM PERUSAHAAN PUBLIK DI BURSA EFEK INDONESIA. Jurnal Riset Manajemen Sains Indonesia (JRMSI) |, 13(1), 2301–8313. https://doi.org/10.21009/JRMSI

Usman, B., & Tandelilin, E. (2014). INTERNET SEARCH TRAFFIC AND ITS INFLUENCE ON LIQUIDITY AND RETURNS OF INDONESIA STOCKS: AN EMPIRICAL STUDY. In Journal of Indonesian Economy and Business (Vol. 29, Issue 3). http://www.goo

Yoshinaga, C., & Rocco, F. (2020). Investor attention: Can google search volumes predict stock returns? Brazilian Business Review, 17(5), 523–539. https://doi.org/10.15728/bbr.2020.17.5.3

Yue, S., & Uc, X. (2014). Stock price forecasting using information from Yahoo finance and Google Trend. UC Brekley, 1–22.


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