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Sentiment spillover and price dynamics: Information flow in the cryptocurrency and stock market

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  • Caferra, Rocco

Abstract

This study examines the sentiment–returns relationship in both stock (S&P500) and cryptocurrency (Bitcoin) markets. An explorative wavelet analysis evidences period of episodic interconnectedness across different data frequencies. Therefore, Transfer Entropy (ET) measures remark the relative statistical significance, frequently outperforming traditional (VAR) estimates. In particular, ET methods successfully identify the mediating role of sentiments in connecting the two different markets. Hence, it is discussed how the potential cryptocurrencies indirect linkage with real economy moves through market sentiments.

Suggested Citation

  • Caferra, Rocco, 2022. "Sentiment spillover and price dynamics: Information flow in the cryptocurrency and stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 593(C).
    • Handle: RePEc:eee:phsmap:v:593:y:2022:i:c:s0378437122000747
    DOI: 10.1016/j.physa.2022.126983
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    Cited by:

    1. Balcilar, Mehmet & Ozdemir, Huseyin & Agan, Busra, 2022. "Effects of COVID-19 on cryptocurrency and emerging market connectedness: Empirical evidence from quantile, frequency, and lasso networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
    2. Tong, Zezheng & Goodell, John W. & Shen, Dehua, 2022. "Assessing causal relationships between cryptocurrencies and investor attention: New results from transfer entropy methodology," Finance Research Letters, Elsevier, vol. 50(C).
    3. 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.
    4. Pagnottoni, Paolo, 2023. "Superhighways and roads of multivariate time series shock transmission: Application to cryptocurrency, carbon emission and energy prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 615(C).
    5. Santorsola, Marco & Caferra, Rocco & Morone, Andrea, 2022. "The financial repercussions of military escalation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).

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    More about this item

    Keywords

    Cryptocurrencies; Information diffusion; Sentiment; Financial market;
    All these keywords.

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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