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Financial Stability

Paper Session

Sunday, Jan. 3, 2021 3:45 PM - 5:45 PM (EST)

Hosted By: American Finance Association
  • Chair: Dasol Kim, U.S. Office of Financial Research

Funding Liquidity and Market Liquidity: The Broker-Dealer Perspective

Marco Machiavelli
,
Federal Reserve Board
Alex Zhou
,
Federal Reserve Board

Abstract

We provide direct evidence of how dealers' funding liquidity affects their liquidity provision in securities markets. Dealers' repo trading terms, including both haircuts and repo spreads, and their ability to finance their bond inventories through repos affect their bid-ask spreads and transaction costs in corporate bonds. Using dealers' exposure to the SEC 2016 money market fund reform as an instrument, we show that funding liquidity indeed has a causal effect on market liquidity. Dealers with lower funding liquidity tend to have smaller market shares and they execute more trades on an agency basis.

A Theory of Collateral Requirements for Central Counterparties

Jessie Jiaxu Wang
,
Arizona State University
Agostino Capponi
,
Columbia University
Hongzhong Zhang
,
Columbia University

Abstract

This paper develops a framework for designing collateral requirements in a centrally cleared market. Clearing members post collateral---initial margins and default funds---to increase their pledgeable income, thereby committing to risk management. The two types of collateral, however, are not perfect substitutes. Due to its loss-mutualization role, the default fund is more effective than initial margin in aligning members' incentives ex-ante. The optimal mix of collateral allocated as initial margin and default fund balances their relative effectiveness in providing incentives with their relative opportunity costs. Our model predicts increasing use of initial margin when capital requirements become more stringent, and of default funds under distressed market scenarios.

Designing Stress Scenarios

Cecilia Parlatore
,
New York University
Thomas Philippon
,
New York University

Abstract

We develop a tractable framework to study the optimal design stress scenarios. A risk-averse principal (e.g, a manager, a regulator) seeks to learn about the exposures of a group of agents (e.g., traders, banks) to a set of risk factors. The principal asks the agents to report their outcomes (e.g., credit losses) under a variety of scenarios that she designs. She can then take remedial actions (e.g., mandate reductions in risk exposures). The principal's program has of two parts. For a given set of scenarios, we show how to apply a Kalman filter to solve the learning problem. The optimal design is then a function of what she wants to learn and how she intends to intervene if she uncovers excessive exposures. The choice of optimal scenarios depends on the principal's prior's about risk exposures, the cost of ex-post interventions, and the potential correlation of exposures across agents.
Discussant(s)
Lasse Pedersen
,
Copenhagen Business School, New York University, AQR, and CEPR
Haoxiang Zhu
,
Massachusetts Institute of Technology
Itay Goldstein
,
University of Pennsylvania
JEL Classifications
  • G2 - Financial Institutions and Services