Improving Bayesian Optimization for Portfolio Management with an Adaptive Scheduling

ArXi:2504.13529v4 Announce Type: replace Existing black-box portfolio management systems are prevalent in the financial industry due to commercial and safety constraints, though their performance can fluctuate dramatically with changing market regimes. Evaluating these non-transparent systems is computationally expensive, as fixed budgets limit the number of possible observations. Therefore, achieving stable and sample-efficient optimization for these systems has become a critical challenge.