Narrative Research Study: Market Sentiment As A Trigger For Cryptocurrency Volatility
DOI:
https://doi.org/10.33506/sl.v14i1.3900Keywords:
Cryptocurrencies, Market Sentiment, Volatility, Narrative ResearchAbstract
This study aims to analyze the impact of market sentiment on cryptocurrency price volatility, focusing on the top 50 cryptocurrencies by market capitalization in 2024. Data was collected from CoinMarketCap for the period 2021-2023, and market sentiment is measured using Natural Language Processing on text data from social media (Twitter, Reddit), forums, and news articles. The analysis employs Structural Equation Modeling - Partial Least Squares to examine the relationship between market sentiment and price volatility. The latent variable "Market Sentiment" is constructed using the NLP indicator, while "Price Volatility" is measured by daily standard deviations and the Average True Range. Additional factors, such as Layer-1, Layer-2, Decentralized Finance, Specialized Computing, Real World Assets, and Decentralized Infrastructure Projects, are also incorporated for a more comprehensive analysis. The results show that positive sentiment significantly increased price volatility, especially for speculative projects like Layer-2 and DeFi, while negative sentiment significantly reduced volatility. Neutral sentiment had no significant effect on price volatility. These findings highlight the important role of social media and news in driving sharp price movements in the cryptocurrency market, providing valuable insights for investors and policymakers in managing and responding to market sentiment.
References
B. J. Jansen, M. Zhang, K. Sobel, dan A. Chowdury, “Twitter Power: Tweets as Electronic Word of Mouth,” J. Am. Soc. Inf. Sci. Technol., vol. 60, no. 11, hal. 2169–2188, 2009.
Y. Xie dan Y. Wang, “A Survey on Social Media Sentiment Analysis: Approaches, Applications, and Challenges,” J. Comput. Secur., vol. 36, hal. 13–22, 2019.
A. A. Kirilenko dan S. Stepchenkova, “The Influence of Media Coverage on Financial Market Volatility: Evidence from Russia,” J. Econ. Behav. & Organ., vol. 98, hal. 118–128, 2014.
E. Bouri, R. Gupta, dan D. Roubaud, “Cryptocurrency market integration: A volatility analysis,” J. Int. Financ. Mark. Institutions Money, vol. 49, hal. 30–39, 2017, doi: 10.1016/j.intfin.2017.02.004.
Q. Zhang, X. Cai, dan J. Wen, “Social Media Sentiment and Cryptocurrency Price Dynamics: A Predictive Modeling Approach,” J. Comput. Financ., vol. 22, no. 3, hal. 45–56, 2018.
X. Liu, X. Hu, dan L. Zhao, “Social Media Sentiment and Financial Market Behavior: A Case Study on Bitcoin,” Comput. Econ., vol. 56, no. 3, hal. 329–342, 2020.
C. Catalini dan J. S. Gans, “Blockchain Technology and the Economics of Cryptocurrencies: A Comprehensive Review,” J. financ. econ., vol. 134, no. 2, hal. 358–379, 2020.
X. Liu dan L. Zhao, “Bitcoin and Social Media Sentiment: A Relationship Analysis Using NLP,” J. Comput. Financ., vol. 22, no. 5, hal. 67–85, 2019.
E. Bouri dan R. Lipy, “The Role of Investor Sentiment in Cryptocurrency Market Volatility,” J. Behav. Financ., vol. 18, no. 4, hal. 295–311, 2017.
P. Mavrodiev, D. Garcia, dan F. Schweitzer, “Social Dynamics in the Cryptocurrency Market,” Sci. Rep., vol. 4, hal. 3947, 2014.
L. Bachelier, “Théorie de la spéculation,” Ann. Sci. l’École Norm. Supérieure, vol. 3, no. 1, hal. 21–86, 2019.
J. Zhang, K. Liu, dan M. Chen, “The impact of liquidity constraints on cryptocurrency price stability,” J. Comput. Econ., vol. 12, no. 1, hal. 123–140, 2022.
D. Garcia, P. Mavrodiev, dan F. Schweitzer, “Social media and market sentiment: Evidence from Twitter and Reddit on cryptocurrency prices,” J. Soc. Networks, vol. 14, no. 3, hal. 234–245, 2021.
I. Ghozali, Partial Least Squares Structural Equation Modeling (PLS-SEM): Concepts and Applications using SmartPLS 3.0, 4th ed. Diponegoro University Publishing Agency, 2021.
J. Beunckens dan R. Maes, “The Volatility of Cryptocurrency Markets: An Empirical Study,” Econ. Lett., vol. 190, hal. 109907, 2020.
Q. Zhang dan X. Cai, “Predicting Cryptocurrency Price Volatility with Machine Learning,” J. Comput. Financ., vol. 23, no. 1, hal. 75–91, 2020.
X. Cai dan Q. Zhang, “Sentiment Analysis of Cryptocurrency News for Volatility Prediction,” Comput. Econ., vol. 56, no. 4, hal. 539–556, 2020.
E. Chung, J. Yoo, dan Y. Cho, “The Effect of Social Media Sentiment on Cryptocurrency Price Volatility,” Int. J. Financ. Res., vol. 10, no. 1, hal. 40–50, 2019.
J. Baker dan R. Thompson, “Crypto regulations and market behavior: How regulatory changes influence volatility,” J. Econ. Policy Res., vol. 29, no. 1, hal. 55–78, 2023.
K. Lim dan R. Gupta, “Cryptocurrency Volatility and the Role of Social Media Sentiment,” J. Financ. Quant. Anal., vol. 52, no. 6, hal. 2227–2253, 2017.
E. Bouri, R. Lipy, dan S. Bouri, “Bitcoin Price and Investor Sentiment: The Role of Sentiment in Predicting Bitcoin Price Volatility,” Int. Rev. Financ. Anal., vol. 72, hal. 101595, 2020.
L. Tan dan J. Liu, “Impact of Social Media Sentiment on Cryptocurrency Market Returns,” Int. J. Inf. Manage., vol. 46, hal. 101490, 2019.
H. Cho dan C. Wang, “Volatility and Investor Sentiment in the Cryptocurrency Market,” J. Int. Financ. Mark., vol. 65, hal. 101282, 2019.
H. Xu, L. Zhao, dan W. Chen, “Forecasting cryptocurrency price volatility using machine learning models: A comparative study,” J. Comput. Financ., vol. 18, no. 2, hal. 130–150, 2023.
K. Lee dan S. Park, “The influence of real-world asset tokenization on cryptocurrency market dynamics,” J. Digit. Financ., vol. 10, no. 4, hal. 78–91, 2021.
S. Chen, Y. Huang, dan Z. Xiao, “The role of decentralized finance in driving cryptocurrency volatility,” J. Financ. Innov., vol. 15, no. 2, hal. 45–67, 2023.
C. Lai dan L. Zhao, “Price Formation and Market Behavior in the Cryptocurrency Market,” J. financ. econ., vol. 141, no. 2, hal. 217–237, 2020.
X. Pan dan F. Li, “Dynamic Volatility of Cryptocurrencies: A Machine Learning Approach,” Comput. Econ., vol. 53, no. 4, hal. 1239–1254, 2018.
L. Hu dan W. Zhou, “Relationship between Social Media Sentiment and Cryptocurrency Market Trends,” J. Financ. Quant. Anal., vol. 54, no. 1, hal. 105–122, 2019.
X. Zhang dan Y. Gao, “Predicting Cryptocurrency Volatility Using Social Media and News Sentiment,” J. Behav. Financ., vol. 19, no. 2, hal. 151–163, 2018.
W. Abdillah dan H. Jogiyanto, Partial Least Square (PLS): Alternatif Structural Equation Modeling (SEM) dalam Penelitian Bisnis. Yogyakarta: Andi, 2015.
J. F. Hair dan others, “PLS-SEM: Indeed a silver bullet,” J. Mark. Theory Pract., vol. 19, no. 2, hal. 139–152, 2022.
D. Garcia, C. J. Tessone, P. Mavrodiev, dan N. Perony, “The role of social media in the cryptocurrency market: Twitter and Reddit’s effect on volatility,” Soc. Sci. Res. Netw., 2021, doi: 10.2139/ssrn.3091262.
J. Kim dan H. Jung, “Natural language processing applications in cryptocurrency markets: A review,” Int. J. Data Sci., vol. 12, no. 1, hal. 123–145, 2022.
C. Lin, J. Wang, dan L. Chen, “Predictive modeling of cryptocurrency price volatility using narrative research and NLP,” Int. J. Financ. Econ., vol. 17, no. 6, hal. 201–219, 2023.
S. Corbet, B. M. Lucey, dan L. Yarovaya, “Datestamping the Bitcoin and Ethereum bubbles,” Financ. Res. Lett., vol. 26, hal. 81–88, 2018, doi: 10.1016/j.frl.2017.12.006.
L. Kristoufek, “Safe haven, hedge, or diversifier? Bitcoin and other cryptocurrencies in global financial markets,” J. Int. Financ. Mark. Institutions, Money, vol. 62, hal. 101161, 2020, doi: 10.1016/j.intfin.2019.101161.
E. Bouri, P. Molnár, G. Azzi, D. Roubaud, dan L. I. Hagfors, “On the hedge and safe haven properties of Bitcoin: Is it really more than a diversifier?,” Financ. Res. Lett., vol. 20, hal. 192–198, 2017, doi: 10.1016/j.frl.2016.09.025.
D. Y. Aharon, M. Qadan, dan Y. Yagil, “Media coverage and cryptocurrency prices,” Res. Int. Bus. Financ., vol. 58, hal. 101433, 2021, doi: 10.1016/j.ribaf.2021.101433.
R. S. Hamid dan A. Suhardi, Structural Equation Modeling (SEM) Berbasis Varian Konsep Dasar dan Aplikasi PLS 3.2.8 Dalam Riset Bisnis, 1 ed. 2019.
R. J. Shiller, Narrative Economics: How Stories Go Viral and Drive Major Economic Events. Princeton University Press, 2020.
C. Roberts dan P. Wilson, “Sentiment analysis and cryptocurrency forecasting using Twitter data,” J. Predict. Anal., vol. 12, no. 3, hal. 100–118, 2023.
R. Garcia dan A. Lopez, “Collaboration in green supply chain management: A systematic review,” J. Clean. Prod., vol. 20, no. 2, hal. 230–250, 2019.
J. Chen, Z. Huang, dan Y. Xiao, “The impact of sentiment on cryptocurrency price volatility: Evidence from NLP analysis and blockchain projects,” J. Blockchain Res., vol. 18, no. 2, hal. 203–217, 2023.
V. Patel dan S. Shah, “Liquidity dynamics and cryptocurrency volatility: The role of market sentiment,” J. Decentralized Financ., vol. 14, no. 4, hal. 201–218, 2023.
J. Huang, C. Yu, dan K. Li, “High-frequency trading and its role in amplifying cryptocurrency volatility,” J. FinTech Res., vol. 9, no. 1, hal. 67–80, 2023.
X. Zhao, L. Liu, dan J. Li, “Social media-driven market sentiment: An analysis of cryptocurrency volatility,” J. Media Econ., vol. 18, no. 2, hal. 89–102, 2023.
R. Kumar dan S. Arora, “Investor sentiment in emerging crypto markets: Evidence from sentiment analysis,” J. Digit. Econ., vol. 8, no. 3, hal. 203–220, 2023.
Z. Deng, Y. He, dan W. Sun, “Regulatory news and cryptocurrency market responses: A volatility analysis,” J. Int. Financ. Mark., vol. 22, no. 4, hal. 95–112, 2023.
R. Hudson dan A. Urquhart, “Technical Trading and Cryptocurrencies,” 2019. [Daring]. Tersedia pada: https://www.ft.com/content/c8a47b42-11d4-11e8-8cb6-b9ccc4c4dbbb.
N. Antonakakis, I. Chatziantoniou, dan D. Gabauer, “Cryptocurrency market contagion: Market uncertainty, market sentiment, and the energy market,” J. Int. Financ. Mark. Institutions, Money, vol. 61, hal. 37–51, 2019, doi: 10.1016/j.intfin.2019.03.013.
S. Li, Y. Zhang, dan Q. Wang, “The impact of blockchain technology on investor sentiment and cryptocurrency markets,” Int. J. Innov. Comput., vol. 12, no. 3, hal. 123–135, 2023.
T. Wong, P. Tan, dan R. Lim, “Sentiment-driven market dynamics in cryptocurrency trading,” Econ. Comput., vol. 16, no. 3, hal. 89–103, 2022.
F. Martinez, J. Lopez, dan D. Perez, “Sentiment analytics in DeFi projects: Impacts on price volatility,” J. Blockchain Res., vol. 13, no. 5, hal. 121–135, 2023.
Z. Li dan J. Wu, “Investor sentiment and cryptocurrency returns: A sentiment-based trading strategy,” J. Financ. Mark., vol. 23, no. 4, hal. 85–103, 2023.
S. Kim dan H. Jung, “Sentiment Analysis and Its Application in Financial Markets: A Review,” Int. J. Financ. Stud., vol. 10, no. 1, hal. 12–34, 2022, doi: 10.3390/ijfs10120012.
A. Gupta, R. Bansal, dan H. Mehta, “Stablecoins as safe-haven assets during market downturns,” J. Financ. Innov., vol. 17, no. 2, hal. 231–245, 2023.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 SENTRALISASI
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Please find the rights and licenses in Sentralisasi. By submitting the article/manuscript of the article, the author(s) agree with this policy. No specific document sign-off is required.
1. License
The non-commercial use of the article will be governed by the Creative Commons Attribution license as currently displayed on Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
2. Author(s)' Warranties
The author warrants that the article is original, written by the stated author(s), has not been published before, contains no unlawful statements, does not infringe the rights of others, is subject to copyright that is vested exclusively in the author, and free of any third party rights, and that any necessary written permissions to quote from other sources have been obtained by the author(s).
3. User/Public Rights
Sentralisasi's spirit is to disseminate articles published are as free as possible. Under the Creative Commons license, Sentralisasi permits users to copy, distribute, display, and perform the work for non-commercial purposes only. Users will also need to attribute authors and Sentralisasi on distributing works in the journal and other media of publications. Unless otherwise stated, the authors are public entities as soon as their articles got published.
4. Rights of Authors
Authors retain all their rights to the published works, such as (but not limited to) the following rights;
- Copyright and other proprietary rights relating to the article, such as patent rights,
- The right to use the substance of the article in own future works, including lectures and books,
- The right to reproduce the article for own purposes,
- The right to self-archive the article (please read our deposit policy),
- The right to enter into separate, additional contractual arrangements for the non-exclusive distribution of the article's published version (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal (Sentralisasi).
5. Co-Authorship
If the article was jointly prepared by more than one author, any authors submitting the manuscript warrants that he/she has been authorized by all co-authors to be agreed on this copyright and license notice (agreement) on their behalf, and agrees to inform his/her co-authors of the terms of this policy. Sentralisasi will not be held liable for anything that may arise due to the author(s) internal dispute. Sentralisasi will only communicate with the corresponding author.
6. Royalties
Being an open accessed journal and disseminating articles for free under the Creative Commons license term mentioned, author(s) aware that Sentralisasi entitles the author(s) to no royalties or other fees.
7. Miscellaneous
Sentralisasi will publish the article (or have it published) in the journal if the article editorial process is successfully completed. Sentralisasi's editors may modify the article to a style of punctuation, spelling, capitalization, referencing, and usage that deems appropriate. The author acknowledges that the article may be published so that it will be publicly accessible and such access will be free of charge for the readers as mentioned in point 3.