Abstract
Despite growing investor participation in cryptocurrency markets, there remains limited empirical guidance on how to value, classify, and integrate crypto assets into investment portfolios using established style-based frameworks. The blockchain-based valuation metrics are relatively nascent, their theoretical foundations are still evolving, and they are not yet fully integrated into classical asset pricing theory, especially in growing economies like South Africa, which is still undergoing a structural shift to legitimize crypto assets in the mainstream. This challenge reflects three interrelated gaps in the broader cryptocurrency literature: the limited application of blockchain-based market-to-fundamental ratios in explaining return dynamics; the underexploitation of value and growth style investing in crypto markets; and the absence of empirical evidence on whether integrating crypto and equity portfolios of similar investment styles enhances portfolio performance relative to equity-only benchmarks. The overarching aim of this study is thus to examine the role of blockchain-based market-to-fundamental ratios in explaining cryptocurrency return dynamics and to assess whether these fundamentals can be leveraged to identify value premiums and enhance portfolio performance through style-based investing and cross-market integration. To achieve this aim, three central objectives are empirically tested within the South African investment context and benchmarked against global market indices, including style-based S&P 500 indices.
Objective one applied the dynamic panel autoregressive distributed lag (ARDL) and panel generalised method of moments (GMM) data models to investigate the impact of market to fundamental ratios (network value to transaction ratio (NVT), market value to realised value (MVRV), and active address to the network value (AANV)) on cryptocurrency (crypto) assets returns. The models were employed to further test for the robust speed of the adjustment processes and persistence in the returns, respectively. Using quarterly data spanning from 2018 to 2023, the findings from the GMM model revealed the importance of factoring blockchain and market fundamental metrics in crypto pricing and valuation. That is, the NVT and the MVRV significantly affected returns, but the effect became negative for the AANV ratio. A mean-reverting behaviour was found in the returns, indicating negative persistence in the market. The robust impact using the ARDL approach showed positive long-term trends in the...