nep-ban New Economics Papers
on Banking
Issue of 2019‒07‒22
thirteen papers chosen by
Christian Calmès, Université du Québec en Outaouais


  1. Have the LVR restrictions improved the resilience of the banking system? By Chris Bloor; Bruce Lu
  2. Liquidity Backup from Commercial Banks to Shadow Banks By Zhou, Zhongzheng
  3. Competition and Bank Risk the Role of Securitization and Bank Capital By Yener Altunbas; David Marques‐Ibanez; Michiel van Leuvensteijn; Tianshu Zhao
  4. Monetary policy expectations and risk-taking among U.S. banks By Byrne, David; Kelly, Robert
  5. Banking Panic Risk and Macroeconomic Uncertainty By Mikkelsen, Jakob; Poeschl, Johannes
  6. Charge-offs, Defaults and U.S. Business Cycles By Christopher M. Gunn; Alok Johri; Marc-Andre Letendre
  7. Externalities and financial crisis – enough to cause collapse? By Miller, Marcus; Zhang, Lei
  8. Mitigating the Cost of Stricter Macroprudential Policies By Pervin Dadashova; Magnus Jonsson
  9. The Transmission of Shocks in Endogenous Financial Networks: A Structural Approach By Jonas Heipertz; Amine Ouazad; Romain Rancière
  10. P2P Loan acceptance and default prediction with Artificial Intelligence By Jeremy D. Turiel; Tomaso Aste
  11. Benchmarking Operational Risk Stress Testing Models By Filippo Curti; Marco Migueis; Rob T. Stewart
  12. American dream delayed: shifting determinants of homeownership By Khorunzhina, Natalia; Miller, Robert
  13. Canadian Securities Lending Market Ecology By Jesse Johal; Joanna Roberts; John Sim

  1. By: Chris Bloor; Bruce Lu (Reserve Bank of New Zealand)
    Abstract: As part of sound regulatory practice, the Reserve Bank wants to further its understanding, and the public’s understanding, of how the policy has influenced financial stability. This paper contributes to this objective by developing a modelling framework that quantifies the extent that the loan-to-value ratio (LVR) policy has improved the resilience of the banking system to a severe downturn in house prices. We find that the LVR restrictions have significantly improved the resilience of the banking system. The LVR policy has reduced the scale of mortgage defaults and credit losses that would occur in a housing downturn, due to a reduction in risky loans on bank balance sheets and the mitigation of a potential house price decline. This resilience benefit has been partly offset by a fall in capital requirements that results from lower credit risk, reducing the banks’ buffer for absorbing credit losses. Nevertheless, the LVR policy is estimated to have reduced mortgage losses – as a share of the capital banks hold against their housing loans – by 12 percentage points. The policy is found to have mitigated about half of the deterioration in bank resilience from 2013 that would have occurred in the absence of the policy. Our estimates are sensitive to judgements on key variables and inputs. The resilience benefit of the LVR policy is contingent on the level of housing market risk that would exist without the policy. This suggests a stronger case to deploy the LVR tool when the risk of a house price decline is high. We were unable to model the resilience benefit of restricting property investor lending with confidence, although a provisional estimate suggests that the benefit may be large. Therefore, the headline estimate may understate the resilience benefit of the LVR intervention. A comprehensive assessment of the policy’s efficacy needs to consider the cost of the policy, which is outside the scope of this paper.
    Date: 2019–05
    URL: http://d.repec.org/n?u=RePEc:nzb:nzbans:2019/07&r=all
  2. By: Zhou, Zhongzheng
    Abstract: During the Great Recession, liquidity did not flow out of the banking sector but transferred internally. Deposits increased, but the volumes of all other short-term debt financing instruments except for T-Bills decreased. Commercial banks, which have stable funding sources from deposits, did not render liquidity backup to shadow banks but held the increased deposits as cash on hand. This paper uses deposits and financial commercial paper outstanding as proxies for commercial and shadow banking financing instruments because they are unique liabilities of commercial and shadow banks, respectively. I provide evidence that when liquidity falls in shadow banks, commercial banks experience funding inflows. In normal times, commercial banks render liquidity backup to shadow banks in the following weeks using the increased deposits. However, the dynamic correlation breaks down in crisis times.
    Keywords: Shadow Banking; Deposit; Commercial Paper; Liquidity; Crisis
    JEL: G01 G21 G28
    Date: 2019–04–30
    URL: http://d.repec.org/n?u=RePEc:pra:mprapa:94713&r=all
  3. By: Yener Altunbas; David Marques‐Ibanez; Michiel van Leuvensteijn; Tianshu Zhao
    Abstract: We examine how bank competition in the run-up to the 2007–2009 crisis affects banks’ systemic risk during the crisis. We then investigate whether this effect is influenced by two key bank characteristics: securitization and bank capital. Using a sample of the largest listed banks from 15 countries, we find that greater market power at the bank level and higher competition at the industry level lead to higher realized systemic risk. The results suggest that the use of securitization exacerbates the effects of market power on the systemic dimension of bank risk, while capitalization partially mitigates its impact.
    Date: 2019–07–02
    URL: http://d.repec.org/n?u=RePEc:imf:imfwpa:19/140&r=all
  4. By: Byrne, David (Central Bank of Ireland); Kelly, Robert (Central Bank of Ireland)
    Abstract: We investigate the role that monetary policy plays in influencing the riskiness of bank lending via the “risk-taking channel” of the transmission mechanism. This affects banks’ perception of, and preference for, extendingnewrelatively risky lending. Using data on the lending of US banks to different risk categories of borrowers, we show that unanticipated increases in expected future interest rates, as measured by the term spread, induce banks to increase the riskiness of their lending. They do this both on an intensive margin, decreasing their lending to less risky borrowers in favour of riskier borrowers, and on an extensive margin also. We show that a one percentage point increase in the term spread leads banks to increase the relative share of riskier lending by 12.6 percent. Our results are relevant for understanding the channels of the monetary policy transmission mechanism and for thinking about the linkages between monetary policy and financial stability.
    Keywords: Monetary Policy, Risk Taking, Bank Lending
    JEL: E51 E52 E58 G21
    Date: 2019–06
    URL: http://d.repec.org/n?u=RePEc:cbi:wpaper:6/rt/19&r=all
  5. By: Mikkelsen, Jakob; Poeschl, Johannes
    Abstract: We show that systemic risk in the banking sector breeds macroeconomic uncertainty. In a production economy with a banking sector, financial constraints of banks can lead to disastrous banking panics. We find that a higher probability of a banking panic increases uncertainty in the aggregate economy. We explore the implications of this banking panic-driven uncertainty for business cycles, asset prices and macroprudential regulation. Banking panic-driven uncertainty amplifies business cycle volatility, increases risk premia on asset prices and yields a new benefit from countercyclical bank capital buffers.
    Keywords: Banking Panics, Systemic Risk, Endogenous Uncertainty, Macroprudential Policy
    JEL: E44 G12 G21 G28
    Date: 2019–06–27
    URL: http://d.repec.org/n?u=RePEc:pra:mprapa:94729&r=all
  6. By: Christopher M. Gunn; Alok Johri; Marc-Andre Letendre
    Abstract: We uncover a new fact: U.S. banks counter-cyclically vary the ratio of charge-offs to defaulted loans. The variance of this ratio is roughly 15 times larger than that of GDP. Canonical financial accelerator models cannot explain this variance. We show that introducing stochastic default costs into the model helps to resolve the discrepancy with the data. Estimating the augmented model using Bayesian techniques reveals that the estimated default cost shocks not only help account for the variance of the banking data but also help account for a significant fraction of the U.S. business cycle between 1984 and 2015.
    Keywords: Charge-offs and defaults, default cost shocks, financial accelerator models, business cycles.
    JEL: E3 E44
    Date: 2019–07
    URL: http://d.repec.org/n?u=RePEc:mcm:deptwp:2019-06&r=all
  7. By: Miller, Marcus (University of Warwick and CEPR); Zhang, Lei (Sichuan University)
    Abstract: After the boom in US subprime lending came the bust - with a run on US shadow banks. The magnitude of boom and bust were, it seems, amplified by two significant externalities triggered by aggregate shocks: the endogeneity of bank equity due to mark-to-market accounting and of bank liquidity due to ‘fire-sales’ of securitised assets. We show how adding a systemic ‘bank run’ to the canonical model of Adrian and Shin allows for a tractable analytical treatment - including the counterfactual of complete collapse that forces the Treasury and the Fed to intervene
    Keywords: pecuniary externalities ; bank runs ; illiquidity ; Lender of Last Resort ; cross-border banking Jel Classification: G01 ; G11 ; G24
    Date: 2019
    URL: http://d.repec.org/n?u=RePEc:wrk:wcreta:51&r=all
  8. By: Pervin Dadashova (National Bank of Ukraine); Magnus Jonsson (Sveriges Riksbank)
    Abstract: We examine how to implement macroprudential policies – stricter capital requirements and loan-tovalue limits – in order to mitigate the output loss of corporate debt deleveraging. The analysis is performed in a dynamic general equilibrium model calibrated to fit the U.S. economy. Stricter capital requirements are generally costlier in terms of output losses than stricter loan-to-value limits. For both instruments, the output loss is a convex function of the debt-to-GDP ratio. Finally, the output loss can be significantly reduced by implementing the requirements gradually, and by activating a countercyclical capital buffer.
    Keywords: capital requirements, loan-to-value requirements, output loss, gradual implementation
    JEL: C54 E44 G28 G38
    Date: 2019–06
    URL: http://d.repec.org/n?u=RePEc:ukb:wpaper:02/2019&r=all
  9. By: Jonas Heipertz; Amine Ouazad; Romain Rancière
    Abstract: The paper uses bank- and instrument-level data on asset holdings and liabilities to identify and estimate a general equilibrium model of trade in financial instruments. Bilateral ties are formed as each bank selects the size and the diversification of its assets and liabilities. Shocks propagate due to the response, rather than the size, of bilateral ties to such shocks. This general equilibrium propagation of shocks reveals a financial network where the strength of a tie is determined by the sensitivity of an instrument’s return to other instruments’ returns. General equilibrium analysis predicts the propagation of real, financial and policy shocks. The network’s shape adjusts endogenously in response to shocks, to either amplify or mitigate partial equilibrium shocks. The network exhibits key theoretical properties: (i) more connected networks lead to less amplification of partial equilibrium shocks, (ii) the influence of a bank’s equity is independent of the size of its holdings; (ii) more risk-averse banks are more diversified, lowering their own volatility but increasing their influence on other banks. The general equilibrium based network model is structurally estimated on disaggregated data for the universe of French banks. We used the estimated network to assess the effects of ECB quantitative easing policy on asset prices, balance-sheets, individual bank distress risk, and networks systemicness.
    JEL: E44 E52 G11 G12 G21
    Date: 2019–07
    URL: http://d.repec.org/n?u=RePEc:nbr:nberwo:26049&r=all
  10. By: Jeremy D. Turiel; Tomaso Aste
    Abstract: Logistic Regression and Support Vector Machine algorithms, together with Linear and Non-Linear Deep Neural Networks, are applied to lending data in order to replicate lender acceptance of loans and predict the likelihood of default of issued loans. A two phase model is proposed; the first phase predicts loan rejection, while the second one predicts default risk for approved loans. Logistic Regression was found to be the best performer for the first phase, with test set recall macro score of $77.4 \%$. Deep Neural Networks were applied to the second phase only, were they achieved best performance, with validation set recall score of $72 \%$, for defaults. This shows that AI can improve current credit risk models reducing the default risk of issued loans by as much as $70 \%$. The models were also applied to loans taken for small businesses alone. The first phase of the model performs significantly better when trained on the whole dataset. Instead, the second phase performs significantly better when trained on the small business subset. This suggests a potential discrepancy between how these loans are screened and how they should be analysed in terms of default prediction.
    Date: 2019–07
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1907.01800&r=all
  11. By: Filippo Curti; Marco Migueis; Rob T. Stewart
    Abstract: The Federal Reserve’s Comprehensive Capital Analysis and Review (CCAR) requires large bank holding companies (BHCs) to project losses under stress scenarios. In this paper, we propose multiple benchmarks for operational loss projections and document the industry distribution relative to these benchmarks. The proposed benchmarks link BHCs’ loss projections with both financial characteristics and metrics of historical loss experience. These benchmarks capture different measures of exposure and together provide a comprehensive view of the reasonability of model outcomes. Furthermore, we employ several approaches to assess the conservatism of BHCs’ stress loss projections and our estimates for the conservatism of loss projections for the median bank range from the 90th percentile to above the 99th percentile of the operational loss distribution.
    Keywords: Benchmarking ; Operational Risk ; Stress Testing
    JEL: G28 G21 G32
    Date: 2019–05–28
    URL: http://d.repec.org/n?u=RePEc:fip:fedgfe:2019-38&r=all
  12. By: Khorunzhina, Natalia; Miller, Robert
    Abstract: This paper develops and estimates a dynamic model of discrete choice for labor supply, fertility and transition from tenant to homeowner, to investigate the secular decline in homeownership over the past several decades, wholly attributable to households postponing the purchase of their first home. House prices only partly explain the decline; higher base level wages led to lower fertility also contributing to the decline, because households with children are more likely to own a home than those without. Somewhat surprisingly we find higher levels of female education ameliorated this trend, highly educated women placing greater value on homeownership.
    Keywords: Housing Demand, Fertility, Labor Supply
    JEL: D14 D91 J13 J22 R21
    Date: 2019–07–03
    URL: http://d.repec.org/n?u=RePEc:pra:mprapa:94832&r=all
  13. By: Jesse Johal; Joanna Roberts; John Sim
    Abstract: This is the fourth of the Financial Markets Department’s descriptions of Canadian financial industrial organization. The paper discusses the organization of the securities lending market in Canada. We outline key characteristics of securities lending contracts, participants in the securities lending market, the market infrastructures that support securities lending activities, and aggregated statistics describing the Canadian market. We also describe trading practices, risks and regulation relating to the securities lending market. A securities lending transaction is the collateralized and temporary transfer of ownership of a security for a fee. One party to the transaction lends securities and collects a fee for the loan. The other party borrows securities and pays the fee. The securities borrower secures the loan by pledging collateral, such as cash or other securities. The main participants in the Canadian securities lending market are banks, dealers, investment funds (e.g., pension funds, mutual funds) and custodian banks. Securities lending supports a variety of market activities and trading strategies; it can be used for market making, collateral transformation, speculation, hedging and arbitrage. Securities lending can generate and spread risks in the financial system because of the levered interconnections it creates among participants; these risks are mitigated and managed through a range of regulation.
    Keywords: Financial Institutions; Financial markets; Financial system regulation and policies; Market structure and pricing
    JEL: G18 G21 G23
    Date: 2019–07
    URL: http://d.repec.org/n?u=RePEc:bca:bocadp:19-5&r=all

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