Open Data and Financial Market Quality

Global financial regulators increasingly promote open-data mandates to dismantle information monopolies and improve market transparency. This paper identifies a fundamental equilibrium tension—the open data paradox—arising from the endogenous composition of disseminated information. We develop a theoretical model in which competition among data vendors expands access to fundamental signals, improving price efficiency, but also incentivizes the dissemination of non-fundamental order-flow information that indirectly reduces liquidity provision. While fundamental data reduces informational frictions, non-fundamental data increases adverse selection by facilitating strategic sniping of noise-trader flow, thereby impairing market liquidity. We test the model’s predictions using a quasi-natural experiment generated by China’s 2023 antitrust intervention in the bond-market data industry. Consistent with the theory, dismantling the data monopoly enhances pricing efficiency but reduces market turnover. These results highlight that open-data policies operate through opposing informational channels, implying that optimal data regulation must balance the benefits of information access against the liquidity risks of exposing order-flow privacy, particularly in thin or regulated markets.