This thesis investigates how technological innovation influences the valuation of cryptocurrencies, focusing on the top 50 DeFi tokens by market capitalization. To capture the multifaceted nature of blockchain innovation, I construct three distinct indicators: a Whitepaper Innovation Index based on word embedding and clustering techniques, a standardized Audit Security Score derived from rubric-guided evaluation of audit reports, and a Code Maturity Proxy based on GitHub fork counts. These metrics are combined with financial data from CoinMarketCap and project-level metadata including blockchain architecture classification, academic involvement, historical volatility, and token age. Cross-sectional regression analysis shows that the proposed innovation indicators—while theoretically meaningful—do not exhibit statistically significant relationships with either market capitalization or trading volume. Instead, token age emerges as the most robust and consistent predictor across specifications, indicating that investor behavior is more responsive to project longevity than to technical complexity. Historical volatility is also negatively associated with market capitalization, suggesting that market participants tend to penalize assets with unstable pricing histories. The results suggest that, within the current market landscape, signals of maturity and stability outweigh detailed technical disclosures in shaping investor perception. This study contributes to the empirical literature by introducing a structured, multi-dimensional framework for evaluating technological innovation in crypto assets and by shedding light on the behavioral cues that dominate pricing dynamics in decentralized finance.