Despite increased demand for cleaner fuel alternatives such as ethanol in recent decades, portfolio weight allocation has become challenging due to the complex interlinkage amongst crude, ethanol and soft agricultural commodities that form part of the value chain. As a result, portfolio returns face three trade-offs in terms of risk: dispersion across mean, risk arising due to market interconnectedness, and risk arising due to global shocks for assets sharing common macroeconomic fundamentals. This study proposes an optimal weight allocation portfolio strategy, encapsulating the three risk measures and returns, estimated using state-of-the-art multi-objective elitist Non-Dominated Sorting Algorithm II (NSGA-II). Our proposed strategy performs well for newly constituted objectives against the Markowitz Mean-Variance approach and Global Minimum Variance. A balanced diversification escapes the feedback spillover loop trap at the same time. Our results indicate that soybean oil, sugar, and rice offer a better reward to risk, aiding portfolio immunisation to extreme market movements. Furthermore, using GJR-GARCH volatility to capture the volatility asymmetry effect, the Generalized Forecast Variance Decomposition (GFVED) shows the existence of a strong triplet pair Crude-Ethanol-Soybean as a breeding ground for the feedback effect to occur. Moreover, replacing crude weight with ethanol depicts a fall in spillover risk up to a threshold of 30% Ethanol weight, after which the feedback effect kicks in.