A theory of repurchase agreements, collateral re-use, and repo intermediation

Gottardi, Piero; Maurin, Vincent; Monnet, Cyril

doi:10.1016/j.red.2019.04.009

Cited by 62 publications

(24 citation statements)

References 25 publications

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“…We extend their original insight by considering when the risky asset can in fact "require less collateral" than alternatives. In our model, tranching and pyramiding are ways of stretching collateral, which is similar to their insight that financial innovation is a response to scarce collateral (see also Gottardi et al, 2019, regarding collateral re-use). Our theory rooted in collateral can explain positive bases by emphasizing financial innovations that stretch collateral.…”

Section: Related Literaturesupporting

confidence: 70%

Collateral Constraints, Tranching, and Price Bases

Gong¹,

Phelan²

2020

Preprint

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Tranching an asset increases its basis; tranching a CDS, as occurs with the CDX index, increases the basis on the underlying asset. We consider a general equilibrium model with collateralized financial promises and multiple states of uncertainty to study how allowing an asset to back multiple financial contracts (i.e., tranching) affects price bases. A positive basis emerges when risky assets and their derivative contracts can be used as collateral for financial promises. We provide an empirical test of our theory using inclusion in the CDX and find that inclusion in the CDX increases the CDS basis.

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Section: Related Literaturesupporting

confidence: 70%

Collateral Constraints, Tranching, and Price Bases

Gong¹,

Phelan²

2020

Preprint

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“…Our work contributes to the recent theoretical literature on the consequences of collateral rehypothecation (see e.g. Bottazzi et al, 2012;Andolfatto et al, 2017;Gottardi et al, 2017;Singh, 2016). This literature has highlighted the role of rehypothecation in determining repo rates (e.g.…”

mentioning

confidence: 61%

Collateral Unchained: Rehypothecation Networks, Concentration and Systemic Effects

et al. 2018

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We study how network structure affects the dynamics of collateral in presence of rehypothecation. We build a simple model wherein banks interact via chains of repo contracts and use their proprietary collateral or re-use the collateral obtained by other banks via reverse repos. In this framework, we show that total collateral volume and its velocity are affected by characteristics of the network like the length of rehypothecation chains, the presence or not of chains having a cyclic structure, the direction of collateral flows, the density of the network. In addition, we show that structures where collateral flows are concentrated among few nodes (like in core-periphery networks) allow large increases in collateral volumes already with small network density. Furthermore, we introduce in the model collateral hoarding rates determined according to a Value-at-Risk (VaR) criterion, and we then study the emergence of collateral hoarding cascades in different networks. Our results highlight that network structures with highly concentrated collateral flows are also more exposed to large collateral hoarding cascades following local shocks. These networks are therefore characterized by a trade-off between liquidity and systemic risk. This paper investigates the collateral dynamics when banks are connected in a network of financial contracts and they have the ability to rehypothecate the collateral along chains of contracts.

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“…Also this paper incorporates lender default and how collateral, which is supposed to insulate counterparty risk, can still remain as a contagion channel. Eren (2014), Gottardi et al (2017), Infante and Vardoulakis (2018), Infante (2019), and Park and Kahn (2019) investigated the lender default problem in collateralized lending and relevant deadweight loss, in addition to contract and intermediation dynamics. This paper incorporates the lender default feature into the endogenous network structure.…”

Section: Related Literaturementioning

confidence: 99%

“…Therefore, lending or leverage at any point in the lending chain has a multiplier effect on the economy. This leverage multiplier effect due to reuse of collateral has been examined in Gottardi et al (2017) as well. A distinct feature from theorem 1 is that different level in the lending chain has different multiplier effects.…”

Section: For Any Counterpartiesmentioning

confidence: 99%

Collateralized Debt Networks with Lender Default

Chang

2019

FEDS

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The Lehman Brothers' bankruptcy triggered the failure of the collateralized debt markets, which was a major contributor of the financial crisis in 2008. Such collateralized debt markets have both collateral price channel and counterparty (borrower and lender) channel of contagion. I propose a general equilibrium network model, which incorporates the two channels of contagion by endogenizing leverage (margin), asset prices, and network formation. Agents face a tradeoff between leverage and counterparty risk. Diversification of counterparty risk generates positive externalities by reducing systemic risk, but comes at the cost of lower leverage. Thus, any decentralized equilibrium is inefficient due to under-diversification. I use this framework to show that the loss coverage by a central counterparty (CCP) exacerbates the externality problem and the introduction of CCP can rather increase systemic risk.

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A theory of repurchase agreements, collateral re-use, and repo intermediation

Cited by 62 publications

References 25 publications

Collateral Constraints, Tranching, and Price Bases

Collateral Constraints, Tranching, and Price Bases

Collateral Unchained: Rehypothecation Networks, Concentration and Systemic Effects

Collateralized Debt Networks with Lender Default

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