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Интернет-публикации как инструмент прогнозирования на рынке криптовалют

Получена: 19.10.2023

Получена в доработанном виде: 02.11.2023

Одобрена: 16.11.2023

Доступна онлайн: 30.01.2024

Рубрика: Рынок ценных бумаг

Коды JEL: G14, G17, G39

Страницы: 72–102

https://doi.org/10.24891/fc.30.1.72

Предмет. Взаимосвязь между настроениями, вызванными новостями на профессиональном форуме CoinTelegragh и динамикой криптовалют биткоин, лайткоин и эфириум.
Цели. Оценить влияние тональности различных интернет-публикаций на волатильность криптовалют, а также предсказательную силу Google Trends и индекса неопределенности VIX в отношении криптовалют.
Методология. Использован метод кросс-квантилограмм, предобученная нейросеть VADER.
Результаты. Обнаружено, что рынок криптовалют имеет сложный компонент настроений, его цены и торговая активность определяются популярностью, эмоциями и настроениями. При этом период COVID-19 и геополитических шоков усилил это влияние.
Выводы. В период превалирования негативных новостей и публикаций рынок криптовалют сужается, объем торгов уменьшается, а интерес у интернет-пользователей снижается до минимума. Эйфория на рынке, напротив, привлекает новых неквалифицированных инвесторов, что подтверждается количеством просмотров базовой информации о криптовалютах в Википедии. Индекс Google Trends в краткосрочном периоде 1-3 дня можно использовать для прогнозирования цены закрытия биткоина, лайткоина и эфириума, в то время как индекс неопределенности фондового рынка VIX не имеет взаимосвязи с рынком криптовалют. Это означает, что криптовалюты могут быть использованы как актив-убежище при сильной волатильности фонового рынка.

Ключевые слова: индекс волатильности криптовалюты, волатильность, внимание инвесторов, биткоин

Список литературы:

1. Zhao J., Zhang T. Exploring the Time-Varying Dependence Between Bitcoin and the Global Stock Market: Evidence from a TVP-VAR Approach. Finance Research Letters, 2023, vol. 58, part A. URL: Link
2. Nekhili R., Sultan J., Bouri E. Liquidity Spillovers Between Cryptocurrency and Foreign Exchange Markets. The North American Journal of Economics and Finance, 2023, vol. 68. URL: Link
3. Dastgir S., Demir E., Downing G. et al. The Causal Relationship Between Bitcoin Attention and Bitcoin Returns: Evidence from the Copula-based Granger Causality Test. Finance Research Letters, 2019, vol. 28, pp. 160–164. URL: Link
4. Shahzad S.J.H., Bouri E., Roubaud D. et al. Is Bitcoin a Better Safe-Haven Investment Than Gold and Commodities? International Review of Financial Analysis, 2019, vol. 63, pp. 322–330. URL: Link
5. Liu Yu., Tsyvinski A. Risks and Returns of Cryptocurrency. Review of Financial Studies, 2021, vol. 34, iss. 6, pp. 2689–2727. URL: Link
6. Mnif E., Salhi B., Trabelsi L., Jarboui A. Efficiency and Herding Analysis in Gold-backed Cryptocurrencies. Heliyon, 2022, vol. 8, iss. 12. URL: Link
7. Naeem M.A., Mbarki I., Shahzad S.J.H. Predictive Role of Online Investor Sentiment for Cryptocurrency Market: Evidence from Happiness and Fears. International Review of Economics & Finance, 2021, vol. 73, pp. 496–514. URL: Link
8. Bouri E., Gupta R., Roubaud D. Herding Behaviour in Cryptocurrencies. Finance Research Letters, 2019, vol. 29, pp. 216–221. URL: Link
9. Menkhoff L., Taylor M.P. The Obstinate Passion of Foreign Exchange Professionals: Technical Analysis. Journal of Economic Literature, 2007, vol. 45, no. 4, pp. 936–972. URL: Link
10. Greenwood R., Nagel S. Inexperienced Investors and Bubbles. Journal of Financial Economics, 2009, vol. 93, iss. 2, pp. 239–258. URL: Link
11. Anamika, Chakraborty M., Subramaniam S. Does Sentiment Impact Cryptocurrency? Journal of Behavioral Finance, 2023, vol. 24, iss. 2, pp. 202–218. URL: Link
12. Ángeles López-Cabarcos M., Vázquez-Rodríguez P., Quiñoá-Piñeiro L.M. An Approach to Employees' Job Performance Through Work Environmental Variables and Leadership Behaviours. Journal of Business Research, 2022, vol. 140, pp. 361–369. URL: Link
13. Kumar P., Islam M.A., Pillai R., Sharif T. Analysing the Behavioural, Psychological, and Demographic Determinants of Financial Decision Making of Household Investors. Heliyon, 2023, vol. 9, iss. 2. URL: Link
14. Laurini M.P., Furlani L.G.C., Portugal M.S. Empirical Market Microstructure: An Analysis of the BRL/US$ Exchange Rate Market. Emerging Markets Review, 2008, vol. 9, iss. 4, pp. 247–265. URL: Link
15. Chang C.Y., Shie F.S. The Relation Between Relative Order Imbalance and Intraday Futures Returns: An Application of the Quantile Regression Model to Taiwan. Emerging Markets Finance & Trade, 2011, vol. 47, no. 3, pp. 69–87.
16. Ha L.T., Nham N.T.H. An Application of a TVP-VAR Extended Joint Connected Approach to Explore Connectedness Between WTI Crude Oil, Gold, Stock and Cryptocurrencies During the COVID-19 Health Crisis. Technological Forecasting and Social Change, 2022, vol. 183. URL: Link
17. Georgoula I., Pournarakis D., Bilanakos C. et al. Using Time-Series and Sentiment Analysis to Detect the Determinants of Bitcoin Prices. 2015. URL: Link
18. Anastasiou D., Ballis A., Drakos K. Constructing a Positive Sentiment Index for COVID-19: Evidence from G20 Stock Markets. International Review of Financial Analysis, 2022, vol. 81. URL: Link
19. Cheng X. The Impact of Economic Policy Uncertainty on the Efficiency of Corporate Working Capital Management – The Evidence from China. Modern Economy, 2019, vol. 10, no. 3, pp. 811–827. URL: Link
20. Green D.M., Swets J.A. Signal Detection Theory and Psychophysics. New York, Wiley, 1966.
21. Fama E.F. Efficient Capital Markets: A Review of Theory and Empirical Work. The Journal of Finance, 1970, vol. 25, no. 2, pp. 383–417. URL: Link
22. Gregoriou A. Cryptocurrencies and Asset Pricing. Applied Economics Letters, 2019, vol. 26, iss. 12, pp. 995–998. URL: Link
23. Connelly B.L., Certo S.T., Ireland R.D., Reutze C.R. Signaling Theory: A Review and Assessment. Journal of Management, 2011, vol. 37, iss. 1, pp. 39–67. URL: Link
24. Romer D. Rational Asset-Price Movements Without News. The American Economic Review, 1993, vol. 83, no. 5, pp. 1112–1130. URL: Link
25. Tetlock P.C. All the News That's Fit to Reprint: Do Investors React to Stale Information? The Review of Financial Studies, 2011, vol. 24, iss. 5, pp. 1481–1512. URL: Link
26. Shen D., Urquhart A., Wang P. Does Twitter Predict Bitcoin? Economics Letters, 2019, vol. 174, pp. 118–122. URL: Link
27. Karalevicius V., Degrande N., De Weerdt J. Using Sentiment Analysis to Predict Interday Bitcoin Price Movements. Journal of Risk Finance, 2018, vol. 19, no. 1, pp. 56–75. URL: Link
28. Shiller R.J. Irrational Exuberance. Princeton, Princeton University Press, 2000, 296 p.
29. Black F. Noise. The Journal of Finance, 1986, vol. 41, iss. 3, pp. 528–543. URL: Link
30. Tetlock P.C., Saar-Tsechansky M., Macskassy S. More Than Words: Quantifying Language to Measure Firms' Fundamentals. The Journal of Finance, 2008, vol. 63, no. 3, pp. 1437–1467. URL: Link
31. Caferra R. Good Vibes Only: The Crypto-Optimistic Behavior. Journal of Behavioral and Experimental Finance, 2020, vol. 28. URL: Link
32. Philippas D., Rjiba H., Guesmi K., Goutte S. Media Attention and Bitcoin Prices. Finance Research Letters, 2019, vol. 30, pp. 37–43. URL: Link
33. Bouri E., Gupta R., Tiwari A.K., Roubaud D. Does Bitcoin Hedge Global Uncertainty? Evidence from Wavelet-Based Quantile-in-Quantile Regressions. Finance Research Letters, 2017, vol. 23, pp. 87–95. URL: Link
34. Mnif E., Jarboui A., Mouakhar K. How the Cryptocurrency Market Has Performed During COVID-19? A Multifractal Analysis. Finance Research Letters, 2020, vol. 36. URL: Link
35. Umar Z., Gubareva M. A Time–Frequency Analysis of the Impact of the COVID-19 Induced Panic on the Volatility of Currency and Cryptocurrency Markets. Journal of Behavioral and Experimental Finance, 2020, vol. 28. URL: Link
36. Vidal-Tomás D. Transitions in the Cryptocurrency Market During the COVID-19 Pandemic: A Network Analysis. Finance Research Letters, 2021, vol. 43. URL: Link
37. Han H., Linton O., Oka T., Whang Y.-J. The Cross-Quantilogram: Measuring Quantile Dependence and Testing Directional Predictability Between Time Series. Journal of Econometrics, 2016, vol. 193, iss. 1, pp. 251–270. URL: Link
38. Borg A., Boldt M. Using VADER Sentiment and SVM for Predicting Customer Response Sentiment. Expert Systems with Applications, 2020, vol. 162. URL: Link
39. Krumholz M.R., Forbes J.C. VADER: A Flexible, Robust, Open-Source Code for Simulating Viscous Thin Accretion Disks. Astronomy and Computing, 2015, vol. 11, part A, pp. 1–17. URL: Link
40. Gaies B., Nakhli M.S., Sahut J.M., Guesmi K. Is Bitcoin Rooted in Confidence? – Unraveling the Determinants of Globalized Digital Currencies. Technological Forecasting and Social Change, 2021, vol. 172. URL: Link
41. Jo H., Park H., Shefrin H. Bitcoin and Sentiment. The Journal of Futures Markets, 2020, vol. 40, iss. 12, pp. 1861–1879. URL: Link
42. Bianchi D., Babiak M., Dickerson A. Trading Volume and Liquidity Provision in Cryptocurrency Markets. Journal of Banking & Finance, 2022, vol. 142. URL: Link
43. Kristoufek L. BitCoin Meets Google Trends and Wikipedia: Quantifying the Relationship Between Phenomena of the Internet Era. Scientific Reports, 2013, vol. 3. URL: Link
44. Partida A., Gerassis S., Criado R. et al. The Chaotic, Self-Similar and Hierarchical Patterns in Bitcoin and Ethereum Price Series. Chaos, Solitons & Fractals, 2022, vol. 165, part 2. URL: Link
45. Tversky A., Kahneman D. Judgment under Uncertainty: Heuristics and Biases: Biases in Judgments Reveal Some Heuristics of Thinking under Uncertainty. Science, 1974, vol. 185, no. 4157, pp. 1124–1131. URL: Link
46. Loughran T., McDonald B. IPO First-Day Returns, Offer Price Revisions, Volatility, and Form S-1 Language. Journal of Financial Economics, 2013, vol. 109, iss. 2, pp. 307–326. URL: Link
47. Lin Z.-Y. Investor Attention and Cryptocurrency Performance. Finance Research Letters, 2021, vol. 40. URL: Link
48. Al Guindy M. Cryptocurrency Price Volatility and Investor Attention. International Review of Economics & Finance, 2021, vol. 76, pp. 556–570. URL: Link

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