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The interdependence structure of cryptocurrencies and Chinese financial assets

Author

Listed:
  • Gao, Ting
  • Wang, Huaiming
  • Du, Dongying

Abstract

This study examines the interdependence structure between cryptocurrencies and Chinese financial assets. The results show a substantial multifractal cross-correlation between cryptocurrencies and Chinese financial assets. When cryptocurrency yield rates follow different trends, their cross-correlations with Chinese financial assets differ, and the asymmetry becomes more prominent. Furthermore, although a “shutdown” policy would impact the two factors’ interdependent structure, it would not eliminate the impact of cryptocurrencies on financial assets.

Suggested Citation

  • Gao, Ting & Wang, Huaiming & Du, Dongying, 2024. "The interdependence structure of cryptocurrencies and Chinese financial assets," Finance Research Letters, Elsevier, vol. 62(PA).
    • Handle: RePEc:eee:finlet:v:62:y:2024:i:pa:s1544612324001168
    DOI: 10.1016/j.frl.2024.105086
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    References listed on IDEAS

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    1. Conlon, Thomas & Corbet, Shaen & McGee, Richard J., 2024. "The Bitcoin volume-volatility relationship: A high frequency analysis of futures and spot exchanges," International Review of Financial Analysis, Elsevier, vol. 91(C).
    2. Wang, Yijun & Andreeva, Galina & Martin-Barragan, Belen, 2023. "Machine learning approaches to forecasting cryptocurrency volatility: Considering internal and external determinants," International Review of Financial Analysis, Elsevier, vol. 90(C).
    3. Zhang, Wei & Li, Yi & Xiong, Xiong & Wang, Pengfei, 2021. "Downside risk and the cross-section of cryptocurrency returns," Journal of Banking & Finance, Elsevier, vol. 133(C).
    4. Proelss, Juliane & Sévigny, Stéphane & Schweizer, Denis, 2023. "GameFi: The perfect symbiosis of blockchain, tokens, DeFi, and NFTs?," International Review of Financial Analysis, Elsevier, vol. 90(C).
    5. Yan, Xiang & Wang, Xuefang & Liu, Sheng, 2023. "A U-shaped relationship between real financialization and financial risk: Evidence from a single threshold model," Finance Research Letters, Elsevier, vol. 56(C).
    6. Zhang, Dingxuan & Sun, Yuying & Duan, Hongbo & Hong, Yongmiao & Wang, Shouyang, 2023. "Speculation or currency? Multi-scale analysis of cryptocurrencies—The case of Bitcoin," International Review of Financial Analysis, Elsevier, vol. 88(C).
    7. Bouri, Elie & Jalkh, Naji, 2023. "Spillovers of joint volatility-skewness-kurtosis of major cryptocurrencies and their determinants," International Review of Financial Analysis, Elsevier, vol. 90(C).
    8. 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).
    9. Wang, Junkai & Qi, Baolei & Nie, Yaoxiang & Hussain, Muhammad Jameel, 2023. "Will the investment environment in the region where the company is located affect its financial risk? Evidence from Chinese listed companies," Finance Research Letters, Elsevier, vol. 57(C).
    10. Amine Lahiani & Ahmed Jeribi & Nabila Boukef Jlassi, 2021. "Nonlinear tail dependence in cryptocurrency-stock market returns: The role of Bitcoin futures," Post-Print hal-03573206, HAL.
    11. Cao, Guangxi & Cao, Jie & Xu, Longbing & He, LingYun, 2014. "Detrended cross-correlation analysis approach for assessing asymmetric multifractal detrended cross-correlations and their application to the Chinese financial market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 393(C), pages 460-469.
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    More about this item

    Keywords

    Cryptocurrency; Chinese financial assets; Interdependence structure;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • F30 - International Economics - - International Finance - - - General
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • O53 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - Asia including Middle East

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