Conference Agenda

Asset heterogeneity is widely believed to restrict liquidity in many markets involving important fixed-income assets. We model the impact of quasi-consolidated (QC) trading---a design that allows sellers to deliver heterogeneous assets for identical payments---on over-the-counter (OTC) markets involving assets with varying values. We show that allowing for QC trading reduces market fragmentation but introduces a cheapest-to-deliver (CTD) effect. In consequence, although QC trading increases total trading volume and social welfare, it hurts liquidity for sellers who do not switch to QC trading and lowers profits for both these sellers and some other sellers who switch to QC trading. Consolidating multiple QC contracts increases (decreases) total trading volume and social welfare if the contracts cover assets with similar (distinct) values.

Repo markets suffer from funding misallocations and funding runs. We develop a rollover risk model with collateral to show how repo trading and clearing mechanisms can resolve these inefficiencies. In over-the-counter markets, non-anonymous trading prevents asset liquidations but causes runs on low-quality borrowers. In central-counterparty markets, anonymous trading provides insurance against small funding shocks but causes inefficient asset liquidations for large funding shocks. The privately optimal market structure requires central clearing with a two-tiered guarantee fund to insure against both illiquidity and insolvency. Our findings inform the policy debate on funding crises and explain empirical patterns of collateral premia.

We examine how intermediary capitalization affects asset prices in a framework that allows for intermediary market power. We introduce a model in which capital constrained intermediaries buy or trade an asset in an imperfectly competitive market, and show that weaker capital constraints lead to both higher prices and intermediary markups. In exchange markets, this results in reduced market liquidity, while in primary markets, it leads to higher auction revenues at an implicit cost of larger price distortion. Using data from Canadian Treasury auctions, we demonstrate how our framework can quantify these effects by linking asset demand to individual intermediaries' balance sheet information.