IDEAS home Printed from https://ideas.repec.org/r/eme/jrfpps/jrf-06-2017-0092.html
   My bibliography  Save this item

Using sentiment analysis to predict interday Bitcoin price movements

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Bouteska, Ahmed & Mefteh-Wali, Salma & Dang, Trung, 2022. "Predictive power of investor sentiment for Bitcoin returns: Evidence from COVID-19 pandemic," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
  2. ?ikolaos A. Kyriazis, 2021. "Impacts of Stock Indices, Oil, and Twitter Sentiment on Major Cryptocurrencies during the COVID-19 First Wave," Bulletin of Applied Economics, Risk Market Journals, vol. 8(2), pages 133-146.
  3. Vincent Gurgul & Stefan Lessmann & Wolfgang Karl Hardle, 2023. "Deep Learning and NLP in Cryptocurrency Forecasting: Integrating Financial, Blockchain, and Social Media Data," Papers 2311.14759, arXiv.org, revised Oct 2024.
  4. Yousaf, Imran & Youssef, Manel & Goodell, John W., 2022. "Quantile connectedness between sentiment and financial markets: Evidence from the S&P 500 twitter sentiment index," International Review of Financial Analysis, Elsevier, vol. 83(C).
  5. Ahmet Faruk Aysan & Ali Yavuz Polat & Hasan Tekin & Ahmet Semih Tunali, 2021. "Bitcoin-specific fear sentiment and bitcoin returns in the COVID-19 outbreak," Working Papers hal-03354930, HAL.
  6. Park, Sangjin & Jang, Kwahngsoo & Yang, Jae-Suk, 2021. "Information flow between bitcoin and other financial assets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 566(C).
  7. Flori, Andrea, 2019. "News and subjective beliefs: A Bayesian approach to Bitcoin investments," Research in International Business and Finance, Elsevier, vol. 50(C), pages 336-356.
  8. Mingzhe Wei & Georgios Sermpinis & Charalampos Stasinakis, 2023. "Forecasting and trading Bitcoin with machine learning techniques and a hybrid volatility/sentiment leverage," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 852-871, July.
  9. Almeida, José & Gonçalves, Tiago Cruz, 2023. "A systematic literature review of investor behavior in the cryptocurrency markets," Journal of Behavioral and Experimental Finance, Elsevier, vol. 37(C).
  10. Mokni, Khaled & Bouteska, Ahmed & Nakhli, Mohamed Sahbi, 2022. "Investor sentiment and Bitcoin relationship: A quantile-based analysis," The North American Journal of Economics and Finance, Elsevier, vol. 60(C).
  11. Kraaijeveld, Olivier & De Smedt, Johannes, 2020. "The predictive power of public Twitter sentiment for forecasting cryptocurrency prices," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 65(C).
  12. Kensuke Ito & Kyohei Shibano & Gento Mogi, 2022. "Bubble Prediction of Non-Fungible Tokens (NFTs): An Empirical Investigation," Papers 2203.12587, arXiv.org, revised Jun 2022.
  13. Umar, Muhammad & Ji, Xiangfeng & Mirza, Nawazish & Li, Haiping, 2022. "Crypto swings and the performance of carbon-intensive equity funds in China," Resources Policy, Elsevier, vol. 78(C).
  14. Walid Bakry & Audil Rashid & Somar Al-Mohamad & Nasser El-Kanj, 2021. "Bitcoin and Portfolio Diversification: A Portfolio Optimization Approach," JRFM, MDPI, vol. 14(7), pages 1-24, June.
  15. Gaies, Brahim & Nakhli, Mohamed Sahbi & Sahut, Jean Michel & Guesmi, Khaled, 2021. "Is Bitcoin rooted in confidence? – Unraveling the determinants of globalized digital currencies," Technological Forecasting and Social Change, Elsevier, vol. 172(C).
  16. Sapkota, Niranjan, 2022. "News-based sentiment and bitcoin volatility," International Review of Financial Analysis, Elsevier, vol. 82(C).
  17. Fang Wang & Marko Gacesa, 2024. "Semi-strong Efficient Market of Bitcoin and Twitter: an Analysis of Semantic Vector Spaces of Extracted Keywords and Light Gradient Boosting Machine Models," Papers 2409.15988, arXiv.org.
  18. A. V. Biju & Aparna Merin Mathew & P. P. Nithi Krishna & M. P. Akhil, 2022. "Is the future of bitcoin safe? A triangulation approach in the reality of BTC market through a sentiments analysis," Digital Finance, Springer, vol. 4(4), pages 275-290, December.
  19. Kajtazi, Anton & Moro, Andrea, 2019. "The role of bitcoin in well diversified portfolios: A comparative global study," International Review of Financial Analysis, Elsevier, vol. 61(C), pages 143-157.
  20. Clark, Ephraim & Lahiani, Amine & Mefteh-Wali, Salma, 2023. "Cryptocurrency return predictability: What is the role of the environment?," Technological Forecasting and Social Change, Elsevier, vol. 189(C).
  21. Dong, Xiyong & Xiong, Youlin & Nie, Siyue & Yoon, Seong-Min, 2023. "Can bonds hedge stock market risks? Green bonds vs conventional bonds," Finance Research Letters, Elsevier, vol. 52(C).
  22. Saggu, Aman, 2022. "The Intraday Bitcoin Response to Tether Minting and Burning Events: Asymmetry, Investor Sentiment, and “Whale Alerts” on Twitter," Finance Research Letters, Elsevier, vol. 49(C).
  23. Sheng‐Tun Li & Kuei‐Chen Chiu & Chien‐Chang Wu, 2023. "Apply big data analytics for forecasting the prices of precious metals futures to construct a hedging strategy for industrial material procurement," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 44(2), pages 942-959, March.
  24. Ahmed, Walid M.A., 2022. "Robust drivers of Bitcoin price movements: An extreme bounds analysis," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
  25. Hajek, Petr & Hikkerova, Lubica & Sahut, Jean-Michel, 2023. "How well do investor sentiment and ensemble learning predict Bitcoin prices?," Research in International Business and Finance, Elsevier, vol. 64(C).
  26. Andreas Hackethal & Tobin Hanspal & Dominique M Lammer & Kevin Rink, 2022. "The Characteristics and Portfolio Behavior of Bitcoin Investors: Evidence from Indirect Cryptocurrency Investments [The investor in structured retail products: advice driven or gambling oriented]," Review of Finance, European Finance Association, vol. 26(4), pages 855-898.
  27. Gradojevic, Nikola & Kukolj, Dragan & Adcock, Robert & Djakovic, Vladimir, 2023. "Forecasting Bitcoin with technical analysis: A not-so-random forest?," International Journal of Forecasting, Elsevier, vol. 39(1), pages 1-17.
  28. Suardi, Sandy & Rasel, Atiqur Rahman & Liu, Bin, 2022. "On the predictive power of tweet sentiments and attention on bitcoin," International Review of Economics & Finance, Elsevier, vol. 79(C), pages 289-301.
  29. Hashem A. AlNemer & Besma Hkiri & Muhammed Asif Khan, 2021. "Time-Varying Nexus between Investor Sentiment and Cryptocurrency Market: New Insights from a Wavelet Coherence Framework," JRFM, MDPI, vol. 14(6), pages 1-19, June.
  30. Ahmed M. Khedr & Ifra Arif & Pravija Raj P V & Magdi El‐Bannany & Saadat M. Alhashmi & Meenu Sreedharan, 2021. "Cryptocurrency price prediction using traditional statistical and machine‐learning techniques: A survey," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 28(1), pages 3-34, January.
  31. López-Cabarcos, M. Ángeles & Pérez-Pico, Ada M. & Piñeiro-Chousa, Juan & Šević, Aleksandar, 2021. "Bitcoin volatility, stock market and investor sentiment. Are they connected?," Finance Research Letters, Elsevier, vol. 38(C).
  32. Gaies, Brahim & Nakhli, Mohamed Sahbi & Sahut, Jean-Michel & Schweizer, Denis, 2023. "Interactions between investors’ fear and greed sentiment and Bitcoin prices," The North American Journal of Economics and Finance, Elsevier, vol. 67(C).
  33. Dias, Ishanka K. & Fernando, J.M. Ruwani & Fernando, P. Narada D., 2022. "Does investor sentiment predict bitcoin return and volatility? A quantile regression approach," International Review of Financial Analysis, Elsevier, vol. 84(C).
  34. Osman, Myriam Ben & Urom, Christian & Guesmi, Khaled & Benkraiem, Ramzi, 2024. "Economic sentiment and the cryptocurrency market in the post-COVID-19 era," International Review of Financial Analysis, Elsevier, vol. 91(C).
  35. Wang, Fang & Gacesa, Marko, 2023. "Semi-strong efficient market of Bitcoin and Twitter: An analysis of semantic vector spaces of extracted keywords and light gradient boosting machine models," International Review of Financial Analysis, Elsevier, vol. 88(C).
  36. Melisa Ozdamar & Levent Akdeniz & Ahmet Sensoy, 2021. "Lottery-like preferences and the MAX effect in the cryptocurrency market," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-27, December.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.