We document “foreign bias” in AI financial predictions, reversing the classic home bias. U.S.-based ChatGPT is systematically more optimistic than China-based DeepSeek about Chinese firms—in price predictions and directional forecasts—yet significantly less accurate. Evidence supports an information-availability mechanism: bias is strongest when U.S. media coverage of Chinese firms is limited and attenuates for cross-listed firms. Crucially, injecting Chinese news eliminates the prediction gap. Both models produce similar forecasts for U.S. firms, consistent with broader worldwide coverage. LLMs trained in different information environments can create divergent signals, with implications for investors and policymakers as AI increasingly intermediates global markets.

In recent decades, over 40% of dollar-denominated corporate bonds have been issued by non-US firms. Strikingly, these foreign issuers face an extra discount of 20 bps than their US counterparts. While standard risks fail to account for the discount, the Economic Policy Uncertainty index from Baker, Bloom, and Davis (2016) can explain a substantial portion of this discrepancy, consistent with uncertainty-based model calibrations. Moreover, such foreign discount (USA effect) dominates the dollar safety premium (USD effect). My findings highlight the foreign discount effect in interna- tional corporate bonds, particularly amidst escalating global economic instability and uncertainty.