Transfer Faster, Price Smarter: Minimax Dynamic Pricing under Cross-Market Preference Shift

We study contextual dynamic pricing when a target market can leverage Kauxiliary markets--offline logs or concurrent streams--whose mean utilities differ by a structured preference shift. We propose Cross-Market Transfer Dynamic Pricing (CM-TDP), the first algorithm that provably handles such model-shift transfer and delivers minimax-optimal regret for both linear and nonparametric utility models. For linear utilities of dimension d, where the difference between source-and targettask coefficients is s0-sparse, CM-TDP attains regret eO (dK 1 + s0) log T .