Augmenting Markets with Mechanisms

Darrell Duffie and Samuel Antill
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Samuel Antill: Stanford University

Research Papers from Stanford University, Graduate School of Business

Abstract: We compute optimal mechanism designs for each of a sequence of size-discovery sessions, at which traders submit reports of their excess inventories of an asset to a session operator, which allocates transfers of cash and the asset. The mechanism design induces truthful reports of desired trades and efficiently reallocates the asset across traders. Between sessions, in a dynamic exchange double-auction market, traders strategically lower their price impacts by shading their bids, causing socially costly delays in rebalancing the asset across traders. As the expected frequency of size-discovery sessions is increased, market depth is further lowered, offsetting the efficiency gains of the size-discovery sessions. Adding size-discovery sessions to the exchange market has no social value, beyond that of a potential initializing session. If, as in practice, size-discovery sessions rely on price information from the exchange to set the terms of trade, then bidding incentives are further weakened, strictly reducing overall market efficiency. Keywords: mechanism design, price impact, size discovery, allocative efficiency, workup, dark pool, market design.

Date: 2018-05
New Economics Papers: this item is included in nep-des and nep-exp
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Related works:
Journal Article: Augmenting Markets with Mechanisms (2021)
Working Paper: Augmenting Markets with Mechanisms (2017)
Working Paper: Augmenting Markets with Mechanisms (2017)
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Persistent link: https://EconPapers.repec.org/RePEc:ecl:stabus:3623

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