IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v62y2024ipas1544612324001168.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1544612324001168
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.frl.2024.105086?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Feng, Lingbing & Qi, Jiajun & Lucey, Brian, 2024. "Enhancing cryptocurrency market volatility forecasting with daily dynamic tuning strategy," International Review of Financial Analysis, Elsevier, vol. 94(C).
    2. Kristjanpoller, Werner & Nekhili, Ramzi & Bouri, Elie, 2024. "Blockchain ETFs and the cryptocurrency and Nasdaq markets: Multifractal and asymmetric cross-correlations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 637(C).
    3. Kakinaka, Shinji & Umeno, Ken, 2021. "Exploring asymmetric multifractal cross-correlations of price–volatility and asymmetric volatility dynamics in cryptocurrency markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
    4. Milan Fičura, 2023. "Impact of size and volume on cryptocurrency momentum and reversal," FFA Working Papers 5.003, Prague University of Economics and Business, revised 05 Apr 2023.
    5. Chen, Bin-xia & Sun, Yan-lin, 2024. "Risk characteristics and connectedness in cryptocurrency markets: New evidence from a non-linear framework," The North American Journal of Economics and Finance, Elsevier, vol. 69(PA).
    6. Chen, Yan & Zhang, Lei & Bouri, Elie, 2024. "Can a self-exciting jump structure better capture the jump behavior of cryptocurrencies? A comparative analysis with the S&P 500," Research in International Business and Finance, Elsevier, vol. 69(C).
    7. Alexander, Carol & Deng, Jun & Feng, Jianfen & Wan, Huning, 2023. "Net buying pressure and the information in bitcoin option trades," Journal of Financial Markets, Elsevier, vol. 63(C).
    8. Zhang, Guofu & Li, Jingjing, 2018. "Multifractal analysis of Shanghai and Hong Kong stock markets before and after the connect program," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 611-622.
    9. Jiang, Jiaqi & Gu, Rongbao, 2016. "Asymmetrical long-run dependence between oil price and US dollar exchange rate—Based on structural oil shocks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 75-89.
    10. Fracasso, Laís Martins & Müller, Fernanda Maria & Ramos, Henrique Pinto & Righi, Marcelo Brutti, 2023. "Is there a risk premium? Evidence from thirteen measures," The Quarterly Review of Economics and Finance, Elsevier, vol. 92(C), pages 182-199.
    11. Aziz N. Berdiev & Rajeev K. Goel & James W. Saunoris, 2024. "Global cryptocurrency use, corruption, and the shadow economy: New insights into the underlying linkages," American Journal of Economics and Sociology, Wiley Blackwell, vol. 83(3), pages 609-629, May.
    12. Li, Hanteng & Qin, Yun, 2024. "Land financialization and regional innovation dynamics: Evidence from China," Finance Research Letters, Elsevier, vol. 64(C).
    13. Kristoufek, Ladislav, 2015. "Power-law correlations in finance-related Google searches, and their cross-correlations with volatility and traded volume: Evidence from the Dow Jones Industrial components," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 428(C), pages 194-205.
    14. Dobrynskaya, Victoria, 2024. "Is downside risk priced in cryptocurrency market?," International Review of Financial Analysis, Elsevier, vol. 91(C).
    15. Almeida, José & Gaio, Cristina & Gonçalves, Tiago Cruz, 2024. "Crypto market relationships with bric countries' uncertainty – A wavelet-based approach," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    16. Yang, Liansheng & Zhu, Yingming & Wang, Yudong & Wang, Yiqi, 2016. "Multifractal detrended cross-correlations between crude oil market and Chinese ten sector stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 255-265.
    17. Zebende, G.F. & da Silva, M.F. & Machado Filho, A., 2013. "DCCA cross-correlation coefficient differentiation: Theoretical and practical approaches," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(8), pages 1756-1761.
    18. Abakah, Emmanuel Joel Aikins & Wali Ullah, GM & Adekoya, Oluwasegun B. & Osei Bonsu, Christiana & Abdullah, Mohammad, 2023. "Blockchain market and eco-friendly financial assets: Dynamic price correlation, connectedness and spillovers with portfolio implications," International Review of Economics & Finance, Elsevier, vol. 87(C), pages 218-243.
    19. Xinyu Huang & Weihao Han & David Newton & Emmanouil Platanakis & Dimitrios Stafylas & Charles Sutcliffe, 2023. "The diversification benefits of cryptocurrency asset categories and estimation risk: pre and post Covid-19," The European Journal of Finance, Taylor & Francis Journals, vol. 29(7), pages 800-825, May.
    20. Nagl, Maximilian, 2024. "Intricacy of cryptocurrency returns," Economics Letters, Elsevier, vol. 239(C).

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:finlet:v:62:y:2024:i:pa:s1544612324001168. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/frl .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.