Connectedness between DeFi assets and TradFi sectors in emerging Asian markets

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Type of the article: Research Article

Abstract
The rise of decentralized finance (DeFi) presents new opportunities for accessing modern financial services. Despite their transformative architecture, most DeFi applications are currently unregulated, which exposes market participants to unforeseen risks. Therefore, understanding the level of connectedness between DeFi and traditional finance (TradFi) is crucial, particularly in emerging Asian markets where the level of cryptocurrency acceptance is high. Applying the time-varying parameter vector autoregressive model, this study examines the return connectedness between leading DeFi assets and traditional financial sectors in Indonesia, India, and Vietnam – the top three countries in Asia for cryptocurrency adoption. By analyzing TradFi at the industry level, this study captures sector-specific spillover dynamics that are essential to the monitoring of systemwide risk. The empirical results reveal low, time-varying return spillovers between DeFi and traditional financial sectors in the selected emerging Asian markets. The emerging financial sectors exhibit stronger linkages with broader traditional market indicators than with DeFi, in which assets interact primarily with each other. Emerging financial sectors and gold are the recipients of return spillovers, and DeFi assets act as the return transmitters. The current low degree of integration between DeFi and TradFi offers policymakers a window of opportunity to develop a robust financial regulatory framework that addresses issues of market stability and consumer protection while promoting the advancement of financial innovation.

Acknowledgments
We thank the editors and anonymous reviewers for their valuable and constructive feedback, which has contributed significantly to improving the quality of this manuscript.

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    • Figure 1. Daily returns of DeFi assets and the traditional financial sector
    • Figure 2. Dynamic total connectedness
    • Figure 3. Net total directional connectedness
    • Figure 4. Net pairwise directional connectedness
    • Table 1. Key indicators of IIV
    • Table 2. Descriptive statistics of the data
    • Table 3. Averaged dynamic return connectedness
    • Conceptualization
      Carol C. Huang, Chris C. Hsu
    • Data curation
      Carol C. Huang, Chris C. Hsu
    • Formal Analysis
      Carol C. Huang, Chris C. Hsu
    • Investigation
      Carol C. Huang, Chris C. Hsu
    • Methodology
      Carol C. Huang, Chris C. Hsu
    • Project administration
      Carol C. Huang
    • Software
      Carol C. Huang, Chris C. Hsu
    • Supervision
      Carol C. Huang, Chris C. Hsu
    • Validation
      Carol C. Huang, Chris C. Hsu
    • Visualization
      Carol C. Huang, Chris C. Hsu
    • Writing – original draft
      Carol C. Huang, Chris C. Hsu
    • Writing – review & editing
      Carol C. Huang, Chris C. Hsu
    • Funding acquisition
      Chris C. Hsu