Do Blockchain Competent Investors’ Sentiments Drive Bitcoin Volatility: A Machine Learning and Nonlinear Analysis? (notice n° 2079792)

détails MARC
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041 ## - LANGUAGE CODE
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100 10 - MAIN ENTRY--PERSONAL NAME
Personal name Bourghelle, David
Relator term author
245 00 - TITLE STATEMENT
Title Do Blockchain Competent Investors’ Sentiments Drive Bitcoin Volatility: A Machine Learning and Nonlinear Analysis?
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Date of publication, distribution, etc. 2026.<br/>
500 ## - GENERAL NOTE
General note 3
520 ## - SUMMARY, ETC.
Summary, etc. This paper extends the behavioral finance literature on the relationship between investor sentiment and bitcoin volatility in two ways. First, we propose a natural language-processing method to measure Blockchain-competent investor sentiment, while extracting information from Reddit forums. Second, we extend the Heterogeneous Autoregressive Realized Volatility(HARRV) model to a nonlinear context, using a Markov switching approach; and we investigate the effect of Blockchain-competent investor sentiment on bitcoin volatility over the period 2018-2023. Further, using FinBERT (Financial Bidirectional Encoder Representations from Transformers) test, we comparatively analyze the effect of Blockchain-Competent (BC) and Non-Blockchain-Competent (NBC) investors’ comments on Reddit on Bitcoin’s volatility. Accordingly, we find that Blockchain-competent investor sentiment has a significant and nonlinear effect on bitcoin volatility. In addition, the distinction between positive and negative sentiment, as well as Blockchain-competent investor sentiment and Blockchain-non-competent investor sentiment significantly improves the forecast of bitcoin volatility. JEL Classification: C2, F10, G10
520 ## - SUMMARY, ETC.
Summary, etc. Cet article approfondit la littérature sur la finance comportementale concernant la relation entre le sentiment des investisseurs et la volatilité du bitcoin de deux manières. D’abord, nous proposons une procédure de traitement du langage naturel pour mesurer le sentiment des investisseurs compétents en matière de blockchain, tout en extrayant des informations des forums Reddit. Ensuite, nous étendons le modèle HAR-RV (Heterogeneous Autoregressive Realized Volatility) à un contexte non-linéaire, en utilisant une approche à changement de régime de Markov, et nous étudions l'effet du sentiment des investisseurs compétents en matière de blockchain sur la volatilité du bitcoin au cours de la période 2018-2023. En outre, à l'aide du test FinBERT (Financial Bidirectional Encoder Representations from Transformers), nous analysons de manière comparative l'effet des commentaires des investisseurs compétents en matière de blockchain (BC) et non compétents en matière de blockchain (NBC) sur Reddit sur la volatilité du bitcoin. Nous montrons ainsi que le sentiment des investisseurs compétents en matière de blockchain a un effet significatif et non-linéaire sur la volatilité du bitcoin. En outre, la distinction entre sentiment positif et négatif, ainsi qu'entre sentiment des investisseurs compétents en matière de blockchain et sentiment des investisseurs non compétents en matière de blockchain, améliore considérablement la prévision de la volatilité du bitcoin. Classification JEL: C2, F10, G10
690 ## - LOCAL SUBJECT ADDED ENTRY--TOPICAL TERM (OCLC, RLIN)
Topical term or geographic name as entry element Analyse du sentiment
690 ## - LOCAL SUBJECT ADDED ENTRY--TOPICAL TERM (OCLC, RLIN)
Topical term or geographic name as entry element méthode de traitement du langage naturel
690 ## - LOCAL SUBJECT ADDED ENTRY--TOPICAL TERM (OCLC, RLIN)
Topical term or geographic name as entry element modèle de transition de Markov HAR-RV
690 ## - LOCAL SUBJECT ADDED ENTRY--TOPICAL TERM (OCLC, RLIN)
Topical term or geographic name as entry element prévisions.
690 ## - LOCAL SUBJECT ADDED ENTRY--TOPICAL TERM (OCLC, RLIN)
Topical term or geographic name as entry element représentations bidirectionnelles des encodeurs financiers à partir de transformateurs
690 ## - LOCAL SUBJECT ADDED ENTRY--TOPICAL TERM (OCLC, RLIN)
Topical term or geographic name as entry element sentiment des investisseurs compétents en matière de blockchain
690 ## - LOCAL SUBJECT ADDED ENTRY--TOPICAL TERM (OCLC, RLIN)
Topical term or geographic name as entry element volatilité du bitcoin
690 ## - LOCAL SUBJECT ADDED ENTRY--TOPICAL TERM (OCLC, RLIN)
Topical term or geographic name as entry element Bitcoin volatility
690 ## - LOCAL SUBJECT ADDED ENTRY--TOPICAL TERM (OCLC, RLIN)
Topical term or geographic name as entry element Blockchain-competent investor sentiment
690 ## - LOCAL SUBJECT ADDED ENTRY--TOPICAL TERM (OCLC, RLIN)
Topical term or geographic name as entry element Financial Bidirectional Encoder Representations from Transformers
690 ## - LOCAL SUBJECT ADDED ENTRY--TOPICAL TERM (OCLC, RLIN)
Topical term or geographic name as entry element Forecast.
690 ## - LOCAL SUBJECT ADDED ENTRY--TOPICAL TERM (OCLC, RLIN)
Topical term or geographic name as entry element HAR-RV Markov Switching model
690 ## - LOCAL SUBJECT ADDED ENTRY--TOPICAL TERM (OCLC, RLIN)
Topical term or geographic name as entry element Natural Language Processing method
690 ## - LOCAL SUBJECT ADDED ENTRY--TOPICAL TERM (OCLC, RLIN)
Topical term or geographic name as entry element Sentiment analysis
700 10 - ADDED ENTRY--PERSONAL NAME
Personal name Fay, Pierre
Relator term author
700 10 - ADDED ENTRY--PERSONAL NAME
Personal name Jawadi, Fredj
Relator term author
786 0# - DATA SOURCE ENTRY
Note Finance | Pub. anticipées | 2026-03-02 | p. I54-XXXVII | 0752-6180
856 41 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://shs.cairn.info/journal-finance-2026-0-page-I54?lang=en&redirect-ssocas=7080">https://shs.cairn.info/journal-finance-2026-0-page-I54?lang=en&redirect-ssocas=7080</a>

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