Cryptocurrency Pricing and Trading

A special issue of Risks (ISSN 2227-9091).

Deadline for manuscript submissions: 31 March 2025 | Viewed by 1388

Special Issue Editors


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Guest Editor
Department of Management, ISEG—Lisbon School of Economics & Management, University of Lisbon, 1200-781 Lisbon, Portugal
Interests: cryptocurrencies and financial markets; financial statement analysis; corporate finance; financial and non financial reporting and corporate governance; financial literacy and stock market inclusion

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Co-Guest Editor
ISEG—Lisbon School of Economics & Management, University of Lisbon, 1200-781 Lisbon, Portugal
Interests: financial economics; macroeconomics; financial markets; alternative finance; behavioral finance; green finance

Special Issue Information

Dear Colleagues,

This Special Issue of Risks will feature original research focused on the evolving landscape of cryptocurrency pricing and trading. This encompasses a wide range of topics, from the implications of artificial intelligence (AI) and technological advancements on trading strategies and market behavior to new developments and innovations within cryptocurrency markets.

The rapid advancement of trading strategies, supported by machine learning and financial innovation, emphasizes the need for ongoing research to navigate technological evolutions and their market impacts (Fang et al., 2022; Koker & Koutmos, 2020). In addition, the development of more accurate asset pricing models for cryptocurrencies contributes to our foundational knowledge of digital currency valuation (Gregoriou, 2019; Momtaz, 2021). Investigations into behavioral economics, specifically herd behavior and feedback trading, along with trading and arbitrage opportunities shed light on market efficiency, liquidity, and profit-making strategies within cryptocurrency markets (King & Koutmos, 2021; Makarov & Schoar, 2020).

Moreover, the relationship between traditional and crypto markets, as evidenced by their sensitivity to global uncertainties, particularly in major economies, underscores the importance of cryptocurrencies in the global financial ecosystem (Almeida et al., 2024). The market microstructure and the interplay between cryptocurrencies and other digital assets, such as NFTs, also reveal the complex mechanisms of digital finance and its implications for investors (Almeida & Gonçalves, 2023b; Dowling, 2022). Due to crypto currency’s unique market dynamics, it is essential to understand the psychological factors influencing traders' decisions. Insights into how emotions affect trading decisions can significantly enhance our understanding of cryptocurrency market behaviors, providing a deeper dive beyond what traditional financial models can offer (Ahn & Kim, 2021; Almeida & Gonçalves, 2023a).

We seek submissions that delve into the vast landscape of cryptocurrency pricing and trading, focusing on innovative research that spans financial analysis, market dynamics, regulatory impacts, and advanced computational approaches to understanding digital currencies.

List of topic areas:

  • Empirical analysis of cryptocurrency price determinants;
  • Trading volume and its impact on cryptocurrency markets;
  • Algorithmic trading strategies in cryptocurrency markets;
  • Market sentiment analysis and its effect on cryptocurrency pricing;
  • Regulatory impact on cryptocurrency trading and valuation;
  • Cryptocurrency market efficiency and speculation;
  • Risk assessment and management in cryptocurrency investments;
  • Comparative analysis of crypto and traditional assets in terms of pricing and trading;
  • Innovations in cryptocurrency trading platforms and instruments.

Inquiries: Questions about submission guidelines, topic suitability, or any other related matters can be sent to Dr. Tiago Cruz Gonçalves ([email protected]).

References

Dr. Tiago Gonçalves
Guest Editor

Dr. José Almeida
Co-Guest Editor

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Keywords

  • cryptocurrency pricing
  • trading strategies
  • market sentiment
  • risk management
  • market efficiency
  • digital assets
  • financial technology
  • investment analysis
  • artificial intelligence

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Published Papers (1 paper)

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Research

25 pages, 2301 KiB  
Article
Cryptocurrency Portfolio Allocation under Credibilistic CVaR Criterion and Practical Constraints
by Hossein Ghanbari, Emran Mohammadi, Amir Mohammad Larni Fooeik, Ronald Ravinesh Kumar, Peter Josef Stauvermann and Mostafa Shabani
Risks 2024, 12(10), 163; https://doi.org/10.3390/risks12100163 - 11 Oct 2024
Viewed by 995
Abstract
The cryptocurrency market offers attractive but risky investment opportunities, characterized by rapid growth, extreme volatility, and uncertainty. Traditional risk management models, which rely on probabilistic assumptions and historical data, often fail to capture the market’s unique dynamics and unpredictability. In response to these [...] Read more.
The cryptocurrency market offers attractive but risky investment opportunities, characterized by rapid growth, extreme volatility, and uncertainty. Traditional risk management models, which rely on probabilistic assumptions and historical data, often fail to capture the market’s unique dynamics and unpredictability. In response to these challenges, this paper introduces a novel portfolio optimization model tailored for the cryptocurrency market, leveraging a credibilistic CVaR framework. CVaR was chosen as the primary risk measure because it is a downside risk measure that focuses on extreme losses, making it particularly effective in managing the heightened risk of significant downturns in volatile markets like cryptocurrencies. The model employs credibility theory and trapezoidal fuzzy variables to more accurately capture the high levels of uncertainty and volatility that characterize digital assets. Unlike traditional probabilistic approaches, this model provides a more adaptive and precise risk management strategy. The proposed approach also incorporates practical constraints, including cardinality and floor and ceiling constraints, ensuring that the portfolio remains diversified, balanced, and aligned with real-world considerations such as transaction costs and regulatory requirements. Empirical analysis demonstrates the model’s effectiveness in constructing well-diversified portfolios that balance risk and return, offering significant advantages for investors in the rapidly evolving cryptocurrency market. This research contributes to the field of investment management by advancing the application of sophisticated portfolio optimization techniques to digital assets, providing a robust framework for managing risk in an increasingly complex financial landscape. Full article
(This article belongs to the Special Issue Cryptocurrency Pricing and Trading)
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