<p>Dry bulk shipping plays an irreplaceable role in global trade but investments in the sector are characterized by high risk and uncertainty. This paper—a sequel to our similar earlier work on tanker investments—develops a multi-objective portfolio optimization model based on stable distributions and investor preferences, referred to as the Mean-VaR-Scale-Skewness-Shannon Entropy-Gini Index (MVSS-SG) framework. The objective is to maximize returns while controlling for risk, according to investor risk preferences. We look into investments in the three most representative types of bulk carriers, i.e., the Capesize, Panamax, and Supramax ships. To shape investor preferences and their risk–return balance, the model considers five objectives: returns, risk, scale, skewness, and diversification. All indices display the typical characteristics of financial time series, with sharp peaks and heavy tails. Key findings show that constraints based on skewness and entropy improve returns, with Shannon entropy having a stronger impact on them, and the Gini index being better in mitigating risk. Sensitivity analysis shows that higher entropy preferences improve significantly both returns and diversification. The model achieves substantial risk reduction for Capesize vessels (up to 91%) and performs well in terms of cumulative returns, ranging from 526.64 to 736.96% over the 2005–2024 period. We also observe significant declines in cumulative returns during five global events—the 2009 financial crisis, Brexit, the China–US trade war, the COVID-19 pandemic, and the Russia–Ukraine war. This research contributes to the theory and practice of bulk carrier investments by offering an adaptive and customizable approach that integrates risk, returns, and investor preferences. This supports more informed investment decisions in dynamic market conditions.</p>