Determinants of Return and Volatility of Cryptocurrencies
Creators: name: Bui, Mai
Publisher: name: RMIT University
Year: 2024
Subjects: classificationCode: 350202
subject: Finance

description: The rise of cryptocurrencies has significantly altered the financial landscape, drawing considerable attention from both investors and researchers. This interest highlights the transformative potential of cryptocurrencies and underscores the need to understand the determinants of their returns and return volatilities. As a novel and distinct asset class, cryptocurrencies differ markedly from traditional financial assets, rendering traditional asset pricing models inadequate for their valuation. This thesis aims to bridge the gap between traditional asset pricing theories and the evolving cryptocurrency market.

Recent studies have attempted to apply common risk factors from traditional asset pricing models to the cryptocurrency market. However, these models often fail to fully account for the unique characteristics of cryptocurrencies, such as their decentralized nature and reliance on cryptographic technology. To address this gap, this thesis examines the effects of common risk factors (market risk premium, size effect, momentum effect), economic risk factors (money supply, investor attention), and technological risk factors (mining cost, scarcity effect) on the cryptocurrency market. By incorporating these diverse risk factors, this thesis provides a deeper understanding of cryptocurrency returns and return volatilities, ensuring the models reflect the distinct features of the cryptocurrency landscape.

The scarcity effect, categorized as a technological risk factor, emerges as a novel and compelling factor deserving investigation due to its fundamental role in shaping asset values and market dynamics. Unlike traditional asset classes, cryptocurrencies often have limited supplies or predetermined issuance schedules, leading to inherent scarcity. Understanding the interplay between scarcity and cryptocurrency returns offers valuable insights into cryptocurrency pricing and portfolio management strategies. Moreover, the scarcity principle, a fundamental concept in economics, presents an intriguing yet underexplored avenue in the context of cryptocurrencies. Through empirical analysis and methodological innovation, this thesis reveals a positive relationship between scarcity and cryptocurrency returns, extending the boundaries of the existing scarcity principle and enhancing our understanding of the cryptocurrency market.

This thesis undertakes a distinct examination of the determinants of Proof-of-Work (PoW) and Proof-of-Stake (PoS) cryptocurrencies, attributed to the contrasting consensus mechanisms inherent to each. By analyzing these cryptocurrencies separately, a deeper comprehension of the factors influencing their excess returns and return volatilities is achieved. Consequently, the construction of mimicking portfolios to explore the size effect, momentum effect, and scarcity effect of PoW and PoS cryptocurrencies is executed independently. This methodological differentiation acknowledges the distinctive attributes and consensus mechanisms of PoW and PoS cryptocurrencies, facilitating a tailored evaluation of their scarcity effects. Furthermore, mimicking portfolios for size, momentum, and scarcity effects are found to outperform their background factors, underscoring the importance of employing such portfolios.

To conduct a thorough analysis of cryptocurrency excess return determinants, this thesis employs Newey–West standard error regressions and two-stage least squares models, effectively addressing issues such as serial correlation, heteroscedasticity, and endogeneity. Robustness tests are conducted through three distinct methods. Initially, the impact of various factors including UCRYPOLICY, gold price, S&amp;P 500 index, crude oil price, and hacking events is evaluated to gauge their influence on the results. Subsequently, the Autoregressive Distributed Lag – Error Correction Model (ARDL-ECM) is employed to validate the findings, ensuring the reliability of the results. Lastly, a panel data analysis is undertaken to collectively assess the significance of identified variables across all PoW and PoS cryptocurrencies. Further strengthening the conclusions, an evaluation is conducted on the impact of excluding Bitcoin and Ethereum from the analysis, revealing consistent results that underscore the persistent significance of the identified variables, thus confirming the robustness of the findings. The findings reveal common determinants for both PoW and PoS cryptocurrency excess returns. For PoW cryptocurrency excess returns, the main determinants are momentum effect, size effect, market risk premium, scarcity effect, investor attention, and mining cost. Meanwhile, for PoS excess returns, the main determinants are size effect, market risk premium, scarcity effect, momentum effect, and investor attention. Mining cost is exclusively applicable to PoW cryptocurrencies, as PoS cryptocurrencies do not rely on computational power for minting.

This thesis further investigates the determinants of cryptocurrency return volatility using the Generalized Autoregressive Conditional Heteroscedasticity (1,1) process. To validate the robustness of the findings, additional tests including Threshold-ARCH, Exponential GARCH (EGARCH), and Power-ARCH (PARCH) models are performed. Subsequently, Akaike's Information Criteria (AIC) and Bayesian Information Criteria (BIC) are utilized to identify the most suitable model for analysis. A GARCH (1,1) model is also applied to the panel data of all PoW and PoS cryptocurrencies to determine if the previously identified significant determinants retain their significance when considering all cryptocurrencies collectively. The results suggest shared determinants influencing both PoW and PoS cryptocurrency return volatilities. These determinants are size effect, momentum effect, market risk premium, scarcity effect, and investor attention.