QUANTIFYING RISK IN DEFI ECOSYSTEMS: A SIX-FACTOR COMPOSITE MODEL FOR SOLANA DEX TOKEN MARKETS

Abstract

High throughput blockchains Decentralised exchange (DEX) ecosystems have become a structurally important part of the global digital asset market, but have not been studied using rigorous and multi-dimensional risk frameworks. The paper is a new composite risk assessment framework used on twenty Solana-based tokens based on live DEX screener data, including a dollar and one hundred and sixty to seven hundred and forty-six thousand dollars in token price and market capitalisation of one hundred and sixty million to six hundred and seventy billion dollars. The six orthogonal risk dimensions are operationalised, viz. volatility risk, liquidity risk, systemic/exchange risk, market/trend risk, sentiment risk, and long-term value risk, all of which have a formal quantitative formula and an established scoring rubric, calibrated to the market microstructure of DEX. Composite Risk Scores (CRS) are calculated as unweighted arithmetic averages of dimension-level scores and categorized under a five level ordinal taxonomy (Low to Extreme). Empirical evidence indicates that tokens that have low levels of market capitalisation and low liquidity pools (particularly FLIQ, BARREL, and COIN) have an extreme-to-very-high composite risk profile, whereas large-capitalisation stablecoin-proximate instruments (SYRUPUSDC, USDG) and Bitcoin-wrapped assets (WBTC) have a significantly lower aggregate risk. The framework incorporates the sell-to-buy flow ratios, liquidity-adjusted capitalisation ratios, and absolute price momentum as a single scoring architecture in real-time DEX data feeds. There are six figures of publication quality to support the empirical analysis: a composite risk bar chart, a six-dimensional heatmap, a radar profile plot, a liquidity-versus-capitalisation bubble chart, a tier distribution panel, and a sentiment flow analysis.