FINANCIAL PERFORMANCE EVALUATION OF CRYPTOCURRENCIES IN THE DIGITAL FINANCIAL MARKET A Study of Selected Digital Assets (2015–2025)

This study provides a comprehensive empirical assessment of the financial performance of ten major cryptocurrencies over the period 2015–2025. The findings reveal that the cryptocurrency market is characterised by a pronounced risk-return trade-off: assets generating superior average returns (Solana, Ethereum, Bitcoin) simultaneously exhibit the highest volatility. The Sharpe Ratio ranking—with Solana (1.90) and Binance Coin (0.512) leading—provides investors with a scientifically grounded framework for evaluating return per unit of risk. The statistical analysis confirms that while individual cryptocurrencies differ significantly in mean price levels (Paired t-test), group mean price variations across observation sub-periods are not statistically significant (ANOVA). This finding is consistent with the hypothesis that cryptocurrency markets are driven by common sentiment and macroeconomic cycles rather than idiosyncratic asset-specific factors within annual sub-periods. Bitcoin and Polkadot's rejection of homogeneity of variance, however, underscores the unique instability of these assets, requiring investors and analysts to employ robust inferential methods. Stablecoins emerge as distinct instruments serving liquidity and risk-management functions within crypto portfolios but offer no meaningful investment return above the risk-free rate. Their inclusion in a portfolio, however, can significantly reduce overall portfolio volatility during market corrections. The NIFTY 50's moderate Sharpe Ratio (0.170) positions traditional equity as a viable risk-adjusted alternative for conservative investors, while more aggressive investors may benefit from selective cryptocurrency exposure—particularly in Solana, Binance Coin, and Ethereum—calibrated to their risk tolerance. Future research should investigate intraday and monthly return dynamics, multi-factor predictive models, regulatory impact analysis, and portfolio optimisation strategies integrating both traditional and digital assets. A longitudinal extension of this study to post-2025 data will be particularly instructive as the cryptocurrency market matures and regulatory frameworks consolidate globally.  

Ram, A. P., & Arulmurugan, V. (2026). Cryptocurrency adoption and investment intensity: A systematic literature review and bibliometric analysis. NMIMS Management Review. Alsulami, F., & Raza, A. (2025). Financial markets effect on cryptocurrency volatility (pre- & post-FTX collapse). International Journal of Financial Studies. Almadadha, R. (2025). Blockchain and financial performance: Empirical evidence from major Australian banks. Frontiers in Blockchain. Wang, P., & Bai, Z. (2025). Decoding the crypto investor profile: Financial literacy and investment decisions. Humanities & Social Sciences Communications. Nagl, M. (2024). Intricacy of cryptocurrency return prediction: Evidence from machine learning models. Economics Letters. Saleem, M. N., et al. (2024). Decrypting cryptocurrencies: Impact on financial stability. Journal of Risk and Financial Management. Almeida, J., & Gonçalves, T. C. (2024). Cryptocurrency investment literature: Systematic and bibliometric review. Annals of Operations Research. Laksana, R., & Fauziyah, E. (2023). Best performing crypto assets 2020–2023: A risk-return analysis. Accounting Studies and Tax Journal. Liu, Y., & Tsyvinsk\ A. (2022). Risks and returns of cryptocurrency. Review of Financial Studies, 35(8), 3728–3766.