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Trading Mechanisms in Securities Markets.

Journal of Finance 1992 47(2), 607-41
This paper analyzes price formation under two trading mechanisms: a continuous quote-driven system where dealers post prices before order submission and an order-driven system where traders submit orders before prices are determined. The order-driven system operates either as a continuous auction, with immediate order execution, or as a periodic auction, where orders are stored for simultaneous execution. With free entry into market making, the continuous systems are equivalent. While a periodic auction offers greater price efficiency and can function where continuous mechanisms fail, traders must sacrifice continuity and bear higher information costs.

Trading Mechanisms in Securities Markets

Journal of Finance 1992 47(2), 607-641
ABSTRACT This paper analyzes price formation under two trading mechanisms: a continuous quote‐driven system where dealers post prices before order submission and an order‐driven system where traders submit orders before prices are determined. The order‐driven system operates either as a continuous auction , with immediate order execution, or as a periodic auction , where orders are stored for simultaneous execution. With free entry into market making, the continuous systems are equivalent. While a periodic auction offers greater price efficiency and can function where continuous mechanisms fail, traders must sacrifice continuity and bear higher information costs.

Intertemporal price discovery by market makers: Active versus passive learning

Journal of Financial Intermediation 1992 2(2), 207-235
This paper demonstrates that market makers have the ability and incentive to facilitate price discovery in securities markets. Market makers can expedite the process of intertemporal price formation by setting prices to induce statistically more informative order flow. Such actions constitute an investment in the production of information. Under certain conditions, market makers can recoup the cost of this investment by making better pricing decisions in the future with more precise information. These conditions are analyzed in a general model and several examples that illustrate the complex nature of price discovery are presented.