Aggregate Bank Capital and Credit Dynamics

Klimenko, Nataliya; Pfeil, Sebastian; Rochet, Jean‐Charles; Nicoló, Gianni De

doi:10.2139/ssrn.2801995

Cited by 22 publications

(18 citation statements)

References 37 publications

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“…An additional related paper is Klimenko et al. (), in which risk‐neutral banks face a downward‐sloping demand for credit, and supply more credit when they have more capital. Banks in that paper parallel arbitrageurs in ours, and banks' borrowers parallel our hedgers.…”

mentioning

confidence: 99%

“…We also show results analytically (rather than via numerical examples), and we do so for general parameter values within which logarithmic preferences are a restrictive special case. An additional related paper is Klimenko et al (2016), in which risk-neutral banks face a downward-sloping demand for credit, and supply more credit when they have more capital. Banks in that paper parallel arbitrageurs in ours, and banks' borrowers parallel our hedgers.…”

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confidence: 99%

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Liquidity Risk and the Dynamics of Arbitrage Capital

Kondor¹,

Vayanos

2019

The Journal of Finance

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We develop a continuous‐time model of liquidity provision in which hedgers can trade multiple risky assets with arbitrageurs. Arbitrageurs have constant relative risk‐aversion (CRRA) utility, while hedgers' asset demand is independent of wealth. An increase in hedgers' risk aversion can make arbitrageurs endogenously more risk‐averse. Because arbitrageurs generate endogenous risk, an increase in their wealth or a reduction in their CRRA coefficient can raise risk premia despite Sharpe ratios declining. Arbitrageur wealth is a priced risk factor because assets held by arbitrageurs offer high expected returns but suffer the most when wealth drops. Aggregate illiquidity, which declines in wealth, captures that factor.

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confidence: 99%

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confidence: 99%

Liquidity Risk and the Dynamics of Arbitrage Capital

Kondor¹,

Vayanos

2019

The Journal of Finance

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“…6 Most recently, 6 A breakdown of the amounts allocated by banks to different asset classes is presented by the Market Klimenko et al (2016) develop a dynamic general equilibrium model to analyze the role of banking capital as a loss absorbing buffer in an economy populated by the real and the banking sectors. As compared with the solution of a social planner, they find that banks lend too much, excessively exposing themselves to risk when the equity is low, and banks lend too little when the equity is high.…”

Section: Literature Reviewmentioning

confidence: 99%

Managing Counterparty Risk in OTC Markets

Frei

Capponi

Brunetti

2017

FEDS

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We study how banks manage their default risk before bilaterally negotiating the quantities and prices of over-the-counter (OTC) contracts resembling credit default swaps (CDSs). We show that the costly actions exerted by banks to reduce their default probabilities are not socially optimal. Depending on the imposed trade size limits, risk-management costs and sellers' bargaining power, banks may switch from choosing default risk levels above the social optimum to reducing them even below the social optimum. We use a unique and comprehensive data set of bilateral exposures from the CDS market to test the main model implications on the OTC market structure: (i) intermediation is done by low-risk banks with medium credit exposure; (ii) all banks with high credit exposures are net buyers of CDSs, and low-risk banks with low credit exposures are the main net sellers; and (iii) heterogeneity in post-trade credit exposures is higher for riskier banks and smaller for safer banks.

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“…The literature was initiated by Bernanke and Gertler (1989) and Bernanke et al (1999), and it has been revived and extended since the advent the financial crisis. Continuoustime models have been featured in He and Krishnamurthy (2013), Brunnermeier and Sannikov (2014), Di Tella (2015), Moreira and Savov (2016), Adrian and Boyarchenko (2012), or Klimenko et al (2016). Differential equation methods give the equilibrium solutions, and the resulting dynamics exhibit quantitatively substantial nonlinearity.…”

Section: Models With Financial Constraints In Continuous Timementioning

confidence: 99%

Term Structure of Uncertainty in the Macroeconomy

Borovička

Hansen

2016

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Dynamic economic models make predictions about impulse responses that characterize how macroeconomic processes respond to alternative shocks over different horizons. From the perspective of asset pricing, impulse responses quantify the exposure of macroeconomic processes and other cash flows to macroeconomic shocks. Financial markets provide compensations to investors who are exposed to these shocks. Adopting an asset pricing vantage point, we describe and apply methods for computing exposures to macroeconomic shocks and the implied compensations represented as elasticities over alternative payoff horizons. The outcome is a term structure of macroeconomic uncertainty.

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Aggregate Bank Capital and Credit Dynamics

Cited by 22 publications

References 37 publications

Liquidity Risk and the Dynamics of Arbitrage Capital

Liquidity Risk and the Dynamics of Arbitrage Capital

Managing Counterparty Risk in OTC Markets

Term Structure of Uncertainty in the Macroeconomy

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