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Cryptocurrency and Blockchain: Opportunities and Challenges for Financial Systems
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Cryptocurrency and Blockchain: Opportunities and Challenges for Financial Systems

A special issue of International Journal of Financial Studies (ISSN 2227-7072).

Deadline for manuscript submissions: 31 October 2026 | Viewed by 7815

Special Issue Editor

Prof. Dr. Yosef Bonaparte

E-Mail Website
Guest Editor
CU Denver Business School, University of Colorado Denver, Denver, CO 80204, USA
Interests: FinTech; AI and ML in finance; behavioral finance; political finance; econometrics

Special Issue Information

Dear Colleagues,

This Special Issue will explore the transformative potential of cryptocurrency and blockchain technologies in reshaping the financial landscape. Over the past decade, these innovations have moved from niche experimentation to mainstream adoption, enabling decentralized finance (DeFi), cross-border payments, tokenized assets, and smart contract-driven markets. At the same time, they present significant challenges around regulatory uncertainty, market volatility, scalability limitations, cybersecurity risks, and implications for monetary policy and financial stability.

We invite contributions that investigate both the opportunities and the risks posed by these technologies. Topics may include blockchain-based financial innovation, cryptocurrency valuation and market dynamics, central bank digital currencies (CBDCs), security and governance frameworks, integration with traditional financial systems, and the socio-economic consequences of decentralization. By bringing together interdisciplinary research, this Special Issue aims to provide a rigorous and balanced understanding of how blockchain and cryptocurrencies can be harnessed for inclusive, efficient, and resilient financial systems, while critically assessing the challenges and unintended consequences caused.

Prof. Dr. Yosef Bonaparte
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. International Journal of Financial Studies is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • cryptocurrency
  • blockchain technology
  • decentralized finance (DeFi)
  • distributed ledger technology (DLT)
  • smart contracts
  • tokenization
  • initial coin offerings (ICOs)
  • central bank digital currencies (CBDCs)
  • financial innovation
  • regulatory challenges
  • market volatility
  • security and privacy
  • fraud prevention
  • adoption and scalability
  • finTech integration
  • peer-to-peer transactions
  • governance models
  • digital asset valuation
  • cross-border payments
  • financial inclusion

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (5 papers)

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Research

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17 pages, 307 KB  
Article
Blockchain-Enabled Transparency and Organizational Value: Evidence from Chinese Firms Referencing DAO Concepts
by Chaoyang Chen and Ziting Wang
Int. J. Financial Stud. 2026, 14(5), 119; https://doi.org/10.3390/ijfs14050119 - 6 May 2026
Viewed by 353
Abstract
This study investigates how information transparency affects organizational value in the Chinese institutional setting, where firms operate under a heavily regulated disclosure regime while increasingly referencing Decentralized Autonomous Organization (DAO) or blockchain-based decentralized governance concepts. Using a panel of 10,029 firm-year observations from [...] Read more.
This study investigates how information transparency affects organizational value in the Chinese institutional setting, where firms operate under a heavily regulated disclosure regime while increasingly referencing Decentralized Autonomous Organization (DAO) or blockchain-based decentralized governance concepts. Using a panel of 10,029 firm-year observations from 1368 Shenzhen A-share listed firms over the period 2012–2022, we employ two-way fixed effects regressions and robustness tests, with information transparency proxied by Shenzhen Stock Exchange disclosure ratings. We find that higher transparency is positively and significantly associated with organizational value (measured by Tobin’s Q). Heterogeneity analyses show that this positive relationship is stronger among state-owned enterprises, firms with lower digital maturity, and firms led by innovation-oriented executives. Comparative tests further reveal that the transparency–value link holds primarily among DAO-referencing firms, whereas it turns negative (though marginally significant) for non-referencing firms. These results suggest that signaling interest in decentralized governance mechanisms can enhance the value relevance of disclosure in regulated emerging markets. Practical implications for managers and policymakers are discussed, along with limitations and directions for future research. Full article
(This article belongs to the Special Issue Cryptocurrency and Blockchain: Opportunities and Challenges for Financial Systems)
36 pages, 431 KB  
Article
Predicting the Volatility of Cryptocurrencies’ Returns Using High-Frequency Data: A Comparative Analysis of GARCH, EGARCH, IGARCH, GJR-GARCH, LRE, and HAR Models
by Abdulrahman Alsamaani and Huda Aldhahi
Int. J. Financial Stud. 2026, 14(4), 90; https://doi.org/10.3390/ijfs14040090 - 3 Apr 2026
Viewed by 2033
Abstract
This study provides a comprehensive evaluation of six volatility forecasting models applied to twelve dominant and less dominant cryptocurrencies across multiple time horizons using high-frequency intraday data. The exponential generalized autoregressive conditional heteroskedastic (EGARCH), integrated GARCH (IGARCH), standard GARCH, GJR-GARCH, lagged realized volatility [...] Read more.
This study provides a comprehensive evaluation of six volatility forecasting models applied to twelve dominant and less dominant cryptocurrencies across multiple time horizons using high-frequency intraday data. The exponential generalized autoregressive conditional heteroskedastic (EGARCH), integrated GARCH (IGARCH), standard GARCH, GJR-GARCH, lagged realized volatility (LRE), and heterogeneous autoregressive (HAR) models are systematically compared using 5 min computed return data from September 2018 to September 2020. Our analysis encompasses three forecast horizons (1-day, 7-day, and 30-day) to assess model performance under varying temporal constraints. Through univariate Mincer–Zarnowitz regressions, encompassing tests, and out-of-sample evaluation using root mean squared error (RMSE) and quasi-likelihood loss (QLIKE) functions, we identify significant performance heterogeneity across models and cryptocurrencies. The HAR model exhibits stronger predictive accuracy at short horizons, while EGARCH exhibits relatively stronger performance at longer horizons, although overall explanatory power declines as forecast horizon increases. Importantly, no single model consistently provides optimal forecasts across all cryptocurrencies. Consistent with prior evidence suggesting model performance varies across assets. Encompassing regressions reveal that combining HAR with EGARCH specifications significantly enhances explanatory power across all temporal frames. Out-of-sample Diebold–Mariano tests indicate that HAR generates the lowest forecast errors for most cryptocurrencies, though EGARCH performs exceptionally well for high-market-capitalization assets. These findings provide regime-conditional insights into horizon- and asset-specific volatility dynamics during the pre-institutionalization phase of cryptocurrency markets. The study contributes to emerging literature by incorporating less-dominant cryptocurrencies and offering robust empirical evidence on the asymmetric and persistent volatility characteristics unique to digital asset markets. These findings should be interpreted within the context of the 2018–2020 sample period, representing a pre-institutionalized phase of cryptocurrency markets, and may not fully generalize to structurally different market regimes characterized by increased institutional participation and regulatory development. Full article
(This article belongs to the Special Issue Cryptocurrency and Blockchain: Opportunities and Challenges for Financial Systems)
12 pages, 484 KB  
Article
Quantum Blockchain: A Theoretical Framework and Applications in Cryptocurrency
by Yosef Bonaparte
Int. J. Financial Stud. 2025, 13(4), 220; https://doi.org/10.3390/ijfs13040220 - 20 Nov 2025
Viewed by 2894
Abstract
Blockchain technology has emerged as the backbone of cryptocurrencies and decentralized finance, yet its long-term resilience is increasingly threatened by advances in quantum computing. Quantum algorithms, such as Shor’s algorithm, can undermine public-key cryptography, while Grover’s algorithm accelerates brute-force search, weakening proof-of-work schemes. [...] Read more.
Blockchain technology has emerged as the backbone of cryptocurrencies and decentralized finance, yet its long-term resilience is increasingly threatened by advances in quantum computing. Quantum algorithms, such as Shor’s algorithm, can undermine public-key cryptography, while Grover’s algorithm accelerates brute-force search, weakening proof-of-work schemes. In this paper, we propose a Quantum Blockchain Framework that integrates quantum communication protocols, quantum consensus mechanisms, and quantum-resistant cryptography. We construct a theoretical model of quantum-secured distributed ledgers, where qubits, entanglement, and quantum key distribution (QKD) enhance security and efficiency. Applications to cryptocurrency are explored, highlighting how quantum blockchain can mitigate security risks, improve consensus speed, and enable quantum-native digital assets. Full article
(This article belongs to the Special Issue Cryptocurrency and Blockchain: Opportunities and Challenges for Financial Systems)
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Review

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25 pages, 728 KB  
Review
Augmented Finance for Climate Action: A Systematic Review of AI, IoT, and Blockchain Applications in Sustainable Finance
by Nadia Mansour
Int. J. Financial Stud. 2026, 14(4), 91; https://doi.org/10.3390/ijfs14040091 - 3 Apr 2026
Viewed by 1008
Abstract
Through assessing the roles of artificial intelligence (AI), Internet of Things (IoT), and blockchain in augmented finance, a critical synthesis of the literature for addressing the complex financial challenges that accompany climate change is provided. This systematic review synthesizes the existing literature to [...] Read more.
Through assessing the roles of artificial intelligence (AI), Internet of Things (IoT), and blockchain in augmented finance, a critical synthesis of the literature for addressing the complex financial challenges that accompany climate change is provided. This systematic review synthesizes the existing literature to identify how these technologies may help in the context of sustainable finance. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we reviewed and analyzed 42 peer-reviewed studies published between 2018 and 2025. Our results are applicable in three general areas: (1) increased measurement, reporting, and verification (MRV) of environmental impacts through employing IoT and blockchain to ensure transparency and traceability; (2) better physical and transition risk control using predictive AI modeling; and (3) better environmental, social, and governance (ESG) analysis and detection of greenwashing and risk reduction via alternative data. We highlight the power of these technologies to address problems such as information asymmetry and transparency gaps in impact chains. However, significant challenges such as algorithmic bias, difficulties associated with data governance, and regulatory delays persist. This study addresses this critical gap by synthesizing the evidence into a cohesive overview of the augmented finance landscape, identifying key challenges and priorities for future research. It also proposes a future research agenda with emphasis on impact assessment, algorithmic transparency, and impact on financial stability. Full article
(This article belongs to the Special Issue Cryptocurrency and Blockchain: Opportunities and Challenges for Financial Systems)
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Other

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31 pages, 879 KB  
Systematic Review
Designing Retail Central Bank Digital Currencies: A Systematic Literature Review of Trade-Offs Between Security, Privacy, and Financial Stability
by Jwa Emma Said and Jan Lánský
Int. J. Financial Stud. 2026, 14(5), 122; https://doi.org/10.3390/ijfs14050122 - 7 May 2026
Viewed by 661
Abstract
This paper proposes a CBDC design trilemma, the claim that central banks cannot simultaneously maximize privacy, financial stability, and regulatory compliance when designing retail central bank digital currencies and finds the existing literature consistent with this proposition. Through a systematic review of 140 [...] Read more.
This paper proposes a CBDC design trilemma, the claim that central banks cannot simultaneously maximize privacy, financial stability, and regulatory compliance when designing retail central bank digital currencies and finds the existing literature consistent with this proposition. Through a systematic review of 140 peer-reviewed articles (Web of Science SCIE/SSCI indexes, 2014–2026, supplemented by Scopus and SSRN), evidence is synthesized across four thematic dimensions: design frameworks and architecture, financial stability and banking risk, privacy and security trade-offs, and user adoption and institutional quality. Cross-tabulation of coded data supports all three pairwise tensions: privacy-enhancing designs weaken AML/CFT enforcement, anonymous holdings amplify bank-run risk, and stringent prudential safeguards constrain transaction monitoring. The literature converges on two-tier, hybrid architectures with tiered privacy as the dominant compromise a “zone of feasible design”, that sacrifices full optimality on each vertex. Nine research gaps are identified, most critically the scarcity of empirical evidence from live deployments, the neglect of wholesale CBDC, and insufficient analysis of cross-border interoperability. The framework offers policymakers a structured lens for evaluating retail CBDC design trade-offs and researchers a testable proposition for future empirical work. Full article
(This article belongs to the Special Issue Cryptocurrency and Blockchain: Opportunities and Challenges for Financial Systems)
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