nep-rmg New Economics Papers
on Risk Management
Issue of 2021‒11‒08
fourteen papers chosen by

  1. Asset concentration risk and insurance solvency regulation By Regele, Fabian; Gründl, Helmut
  2. Does Default Pecking Order Impact Systemic Risk? Evidence from Brazilian data By Michel Alexandre; Thiago Christiano Silva; Krzysztof Michalak; Francisco A. Rodrigues
  3. The Role of (non-)Topological Features as Drivers of Systemic Risk: a machine learning approach By Michel Alexandre; Thiago Christiano Silva; Colm Connaughton; Francisco A. Rodrigues
  4. Heterogeneous Tail Generalized Common Factor Modeling By Simon Hediger; Jeffrey Näf; Marc S. Paolella; Pawel Polak
  5. The Riskiness of Outstanding Mortgages in the United States, 1999 - 2019 By William D. Larson
  6. Liquidity Regulation and Bank Risk By Foly Ananou; Dimitris Chronopoulos; Amine Tarazi; John Wilson
  7. Bank risk-taking and monetary policy transmission : Evidence from China By Li, Xiaoming; Liu, Zheng; Peng, Yuchao; Xu, Zhiwei
  8. Corruption and bank risk-taking: The deterring role of Shari'ah supervision By Mushtaq Hussain Khan; Mohammad Bitar; Amine Tarazi; Arshad Hassan; Ahmad Fraz
  9. Motivated Risk Assessments By Islam, Marco
  10. Characterizing and Communicating the Balance of Risks of Macroeconomic Forecasts: A Predictive Density Approach for Colombia By Juan C. Méndez-Vizcaíno; Alexander Guarin; César Anzola-Bravo; Anderson Grajales-Olarte
  11. Risky Financial Collateral, Firm Heterogeneity, and the Impact of Eligibility Requirements By Matthias Kaldorf; Florian Wicknig
  12. FinTech adoption and household risk-taking By Hong, Claire Yurong; Lu, Xiaomeng; Pan, Jun
  13. Keynes's Treatise on Probability at 100 Years: Its Most Enduring Message By Carlo Zappia
  14. Expectations Concordance and Stock Market Volatility: Knightian Uncertainty in the Year of the Pandemic By Roman Frydman; Nicholas Mangee

  1. By: Regele, Fabian; Gründl, Helmut
    Abstract: Historical evidence like the global financial crisis from 2007-09 highlights that sector concentration risk can play an important role for the solvency of insurers. However, current microprudential frameworks like the US RBC framework and Solvency II consider only name concentration risk explicitly in their solvency capital requirements for asset concentration risk and neglect sector concentration risk. We show by means of US insurers' asset holdings from 2009 to 2018 that substantial sectoral asset concentrations exist in the financial, public and real estate sector, and find indicative evidence for a sectoral search for yield behavior. Based on a theoretical solvency capital allocation scheme, we demonstrate that the current regulatory approaches can lead to inappropriate and biased levels of solvency capital for asset concentration risk, and should be revised. Our findings have also important implications on the ongoing discussion of asset concentration risk in the context of macroprudential insurance regulation.
    Keywords: Microprudential Insurance Regulation,Asset Concentration Risk,Systematic Risk,Idiosyncratic Risk,Sectoral Asset Diversification
    JEL: G01 G11 G22 G28
    Date: 2021
  2. By: Michel Alexandre; Thiago Christiano Silva; Krzysztof Michalak; Francisco A. Rodrigues
    Abstract: In network models of systemic risk, the loss distribution of a distressed debtor among its creditors follows a pro-rata fashion. It is proportional to the loan granted to the debtor. Despite its simplicity, this assumption is unrealistic. In this study, we create a framework for the computation of the systemic risk assuming a heterogeneous pattern of loss distribution, the default pecking order. Distressed debtors employ some criterion (equity, out-degree, or loan extended) to rank the creditors they are willing to default on first. Applying this framework to an extensive Brazilian data set, we found out the adoption of the default pecking order increases significantly the systemic risk. The rise in the systemic risk brought by the heterogeneous distribution over the homogeneous case decreases with the level of the initial shock and is higher for small-sized agents. This result can be interpreted in the light of the dual role of the financial network, which can be a channel for both risk-sharing and shock propagation. We test this hypothesis by assessing the role of interconnectedness (as measured by the network density) in driving the systemic risk. The results corroborate this hypothesis. When the homogeneous loss distribution (which maximizes risk-sharing) is abandoned, the density has a positive impact on the systemic risk. It suggests in this case the financial network acts mainly as a channel for shock propagation rather than for risk-sharing.
    Date: 2021–10
  3. By: Michel Alexandre; Thiago Christiano Silva; Colm Connaughton; Francisco A. Rodrigues
    Abstract: The purpose of this paper is to assess the role of financial and topological variables as determinants of systemic risk (SR). The SR, for different levels of the initial shock, is computed for institutions in the Brazilian interbank market by applying the differential DebtRank methodology. The financial institution(FI)-specific determinants of SR are evaluated through two machine learning techniques: XGBoost and random forest. Shapley values analysis provided a better interpretability for our results. Furthermore, we performed this analysis separately for banks and credit unions. We have found the importance of a given feature in driving SR varies with i) the level of the initial shock, ii) the type of FI, and iii) the dimension of the risk which is being assessed – i.e., potential loss caused by (systemic impact) or imputed to (systemic vulnerability) the FI. Systemic impact is mainly driven by topological features for both types of FIs. However, while the importance of topological features to the prediction of systemic impact of banks increases with the level of the initial shock, it decreases for credit unions. Concerning systemic vulnerability, this is mainly determined by financial features, whose importance increases with the initial shock level for both types of FIs.
    Date: 2021–10
  4. By: Simon Hediger (University of Zurich - Department of Banking and Finance); Jeffrey Näf (ETH Zurich); Marc S. Paolella (University of Zurich - Department of Banking and Finance; Swiss Finance Institute); Pawel Polak (Stony Brook University-Department of Applied Mathematics and Statistics)
    Abstract: A multivariate normal mean-variance heterogeneous tails mixture distribution is proposed for the joint distribution of financial factors and asset returns (referred to as Factor-HGH). The proposed latent variable model incorporates a Cholesky decomposition of the dispersion matrix to ensure a rich dependency structure for capturing the stylized facts of the data. It generalizes several existing model structures, with or without financial factors. It is further applicable in large dimensions due to a fast ECME estimation algorithm of all the model parameters. The advantages of modelling financial factors and asset returns jointly under non-Gaussian errors are illustrated in an empirical comparison study between the proposed Factor-HGH model and classical financial factor models. While the results for the Fama-French 49 industry portfolios are in line with Gaussian-based models, in the case of highly tail heterogeneous cryptocurrencies, the portfolio based on the Factor HGH model doubles the average return while keeping the volatility, the maximum drawdown, the turnover, and the expected-shortfall at a low level.
    Keywords: Asset Pricing Model, Cryptocurrencies, Expectation Maximization Algorithm, Heterogeneous Tails, Mixture Distribution, Portfolio Optimization
    Date: 2021–10
  5. By: William D. Larson (Federal Housing Finance Agency)
    Abstract: This paper introduces summary measures of credit risk for the stock of all outstanding mortgages in the United States for each quarter between 1999 and 2019. Mortgage terminations play a fundamental role in offsetting risk introduced by the flow of new originations because of refinance activity and the often dual nature of home buyers as concurrent sellers. To illustrate these concepts in a policy setting, I show the Home Affordable Refinance Program increased origination risk metrics but reduced overall risk due to the associated terminations of even riskier loans. Generally, book-level risk tends to lag behind originations: while origination risk peaked in 2006, the risk of outstanding mortgages peaked in 2007, and while origination risk bottomed out in 2011 and has been rising since, book-level risk continued its downward trend in 2019. Other results highlight previously rarely-examined market segments, including credit unions, the Federal Home Loan Bank system, and loans guaranteed by the Farm Service Agency/Rural Housing Service.
    Keywords: mortgage risk, systemic risk, housing cycles, stress test
    JEL: E32 G21 G28 H22 R31
    Date: 2021–10
  6. By: Foly Ananou (LAPE - Laboratoire d'Analyse et de Prospective Economique - GIO - Gouvernance des Institutions et des Organisations - UNILIM - Université de Limoges); Dimitris Chronopoulos (University of St Andrews, Centre for Responsible Banking & Finance, Gateway Building, St Andrews, Fife KY16 9RJ, UK); Amine Tarazi (LAPE - Laboratoire d'Analyse et de Prospective Economique - GIO - Gouvernance des Institutions et des Organisations - UNILIM - Université de Limoges); John Wilson (University of St Andrews, Centre for Responsible Banking & Finance, Gateway Building, St Andrews, Fife KY16 9RJ, UK)
    Abstract: In this paper, we investigate the impact of liquidity requirements on bank risk. We take advantage of the implementation of the Liquidity Balance Rule (LBR) in the Netherlands in 2003 and analyze its impact on bank default risk. The LBR was imposed on Dutch banks only and did not apply to other banks operating elsewhere within the Eurozone. Using this differential regulatory treatment to overcome identification concerns, we find that following the introduction of the LBR, the risk of Dutch banks declined relatively to counterparts not affected by the rule. Concomitantly, despite the lower cost of funding driven by the LBR, the profitability of Dutch banks decreased in comparison with other banks in Europe, as a result of a decrease in income accruing from interest-bearing activities. Our findings also indicate that relatively to unaffected banks, Dutch banks might not have actively tried to offset their loss in interest income by increasing interest rates of loans. However, better financing conditions allowed Dutch banks to increase the shares of deposits and capital on the liability side of their balance sheets.
    Keywords: Banking,liquidity regulation,Netherlands,propensity score matching,quasi-natural experiment,risk,stability
    Date: 2021–10–05
  7. By: Li, Xiaoming; Liu, Zheng; Peng, Yuchao; Xu, Zhiwei
    Abstract: We study the impact of China’s 2013 implementation of Basel III on bank risk-taking and its responses to monetary policy shocks using confidential loan-level data from a large Chinese bank. Guided by theory, we use a difference-in-difference identification, exploiting cross-sectional differences in lending behaviors between high-risk and low-risk bank branches before and after the new regulations. We find that, through a risk-weighting channel, changes in regulations significantly reduced bank risk-taking, both on average and conditional on monetary policy easing. However, banks reduce risk-taking by increasing lending to ostensibly low-risk state-owned enterprises (SOEs) under government guarantees, despite their low average productivity.
    JEL: E52 G21 G28
    Date: 2021–10–29
  8. By: Mushtaq Hussain Khan (Department of Management Sciences, University of Azad Jammu & Kashmir, Muzaffarabad, Pakistan); Mohammad Bitar (University of Nottingham Business School, Nottingham, UK); Amine Tarazi (LAPE - Laboratoire d'Analyse et de Prospective Economique - GIO - Gouvernance des Institutions et des Organisations - UNILIM - Université de Limoges); Arshad Hassan (Faculty of Management & Social Sciences, Capital University of Science & Technology, Islamabad, Pakistan); Ahmad Fraz (Pakistan Institute of Development Economics, Islamabad, Pakistan)
    Abstract: This paper investigates whether the risk-taking of Islamic banks is differently affected by corruption compared to conventional banks. Indeed, the presence of Shari'ah supervisory boards (SSBs), as a cornerstone of Islamic banking, is expected to deter the influence of corruption on risk-taking for Islamic banks. We consider a matched sample of 70 Islamic and conventional banks operating in 10 OIC (Organization of Islamic Cooperation) countries over the 2012-2017 period. We find consistent evidence that higher levels of corruption are associated with higher bank risk for both conventional and Islamic banks. However, this association is stronger for conventional banks. Furthermore, for Islamic banks, the impact of corruption on risk-taking is significantly reduced with higher representation of females in Shari'ah supervisory boards and higher academic qualifications of board members. The role played by such board members in mitigating the impact of corruption on risk-taking is more effective for Islamic banks than for conventional banks.
    Keywords: Bank risk taking,Corruption,Ethical banking,Shari'ah supervision
    Date: 2021–10–05
  9. By: Islam, Marco (Department of Economics, Lund University)
    Abstract: How do people assess risks associated with a hedonic but dangerous activity? I conduct a longitudinal field experiment (N=434) exploiting the conditions of the COVID-19 pandemic to investigate whether monetary incentives induce people to motivate their risk assessments. Each participant receives a café voucher with a random value: treated participants receive a 10EUR voucher, and the control group a 1.50EUR voucher. The results show that subjects who receive a high incentive not only visit cafés more often but also reduce their risk assessment relative to subjects with a low incentive. Importantly, the assessment updating happens in anticipation of the visit, suggesting that it justifies a risky activity. This finding is inconsistent with the standard notion of Bayesian updating but consistent with motivated reasoning. It is robust to different risk measures (incentivized and non-incentivized) and does not lend support for alternative explanations, such as visits at less busy times or additional information acquisition. The data further suggests that the formation of motivated risk assessments is supported by selective recall of previous assessments. Treated subjects systematically underestimate former assessments relative to subjects of the control group.
    Keywords: Risk Assessment; Motivated Reasoning; Self-Deception; Field Experiment
    JEL: C93 D03 D91
    Date: 2021–10–28
  10. By: Juan C. Méndez-Vizcaíno; Alexander Guarin; César Anzola-Bravo; Anderson Grajales-Olarte
    Abstract: Since July 2021, Banco de la República strengthened its forecasting process and communication instruments, by involving predictive densities in the projections of its models, PATACON and 4GM. This paper presents the main theoretical and empirical elements of the predictive density approach for macroeconomic forecasting. This model-based methodology allows to characterize the balance of risks of the economy, and to quantify their effects through a joint probability distribution of forecasts. We estimate this distribution based on the simulation of DSGE models, preserving the general equilibrium relationships and their macroeconomic consistency. We also illustrate the technical criteria used to represent prospective factors of risk through the probability distributions of shocks. **** RESUMEN: Desde julio de 2021, el Banco de la República fortaleció su proceso de pronóstico y sus instrumentos de comunicación al incorporar densidades predictivas en las proyecciones de sus modelos, PATACON y 4GM. Este artículo presenta los principales elementos teóricos y empíricos del enfoque de densidad predictiva para los pronósticos macroeconómicos. Esta metodología basada en modelos permite caracterizar el balance de riesgos de la economía y cuantificar sus efectos mediante una distribución de probabilidad conjunta de los pronósticos. Esta distribución se estima mediante la simulación de los modelos DSGE, preservando las relaciones de equilibrio general y la coherencia macroeconómica. También se ilustran los criterios técnicos utilizados para representar los factores de riesgo prospectivos a través de las distribuciones de probabilidad de los choques.
    Keywords: Macroeconomic forecasts, balance of risks, uncertainty, Bayesian forecasting, monetary policy models, Pronósticos macroeconómicos, balance de riesgos, incertidumbre, pronósticos bayesianos, modelos de política monetaria
    JEL: C11 C53 E17 E52
    Date: 2021–10
  11. By: Matthias Kaldorf (University of Cologne, Center for Macroeconomic Research); Florian Wicknig (University of Cologne, Center for Macroeconomic Research)
    Abstract: This paper studies how collateral premia affect the supply and quality of bonds issued by non-financial firms. Banks increase demand for bonds eligible as collateral, to which eligible firms respond by increasing their debt issuance and default risk. We characterize firm responses and aggregate collateral supply in a heterogeneous firm model with collat-eral premia and endogenous default risk. Using a calibration to euro area data, we study the impact of collateral easing, consistent with the ECB’s policy during the 2008 financial crisis and evaluate the quantitative relevance of firm responses. We find that firm responses substantially deteriorate collateral quality and dampen the total increase in collateral sup-ply. Our analysis suggests that an eligibility covenant conditioning eligibility on leverage and current default risk, is a potentially powerful instrument to mitigate the adverse impact of eligibility requirements on collateral quality while maintaining a high level of collateral supply.
    Keywords: Eligibility Premia, Corporate Bonds, Firm Heterogeneity, Collateral Policy
    JEL: E44 E58 G12 G32 G33
    Date: 2021–10
  12. By: Hong, Claire Yurong; Lu, Xiaomeng; Pan, Jun
    Abstract: Using a unique FinTech data containing monthly individual-level consumption, investments, and payments, we examine how FinTech can lower investment barriers and improve risk-taking. Seizing on the rapid expansion of offline usages of Alipay in China, we measure individuals’ FinTech adoption by the speed and intensity with which they adopt the new technology. Our hypothesis is that individuals with high FinTech adoption, through repeated usages of the Alipay app, would build familiarity and trust, reducing the psychological barriers against investing in risky assets. Measuring risk-taking by individuals’ mutual-fund investments on the FinTech platform, we find that higher FinTech adoption results in higher participation and more risk-taking. Using the distance to Hangzhou as an instrument variable to capture the exogenous variation in FinTech adoption yields results of similar economic and statistical significance. Focusing on the welfare-improving aspect of FinTech inclusion, we find that individuals with high risk tolerance, hence more risk-taking capacity, and those living in under-banked cities stand to benefit more from the advent of FinTech.
    JEL: G11 G50
    Date: 2021–10–25
  13. By: Carlo Zappia (Università degli Studi di Siena)
    Abstract: On the occasion of the assessment of the enduring influence of Keynes's Treatise on Probability at 100 years, this paper focuses on its relevance for decision theory. The paper places emphasis on Keynes's introduction of the epistemic notion of probabilities that often are non-numerical, as a theoretical object intended to replace frequency probabilities. The paper argues that, as non-numerical probabilities make it possible to deal with uncertainty as if individuals were endowed with interval-valued probabilities, Keynes's 1921 critique of contemporary frequency probability theory turns out to be relevant also with regard to the yet to be established subjective probability theory. Although non-numerical probabilities were used by Keynes to criticize the contemporary application of probability to conduct, it must be acknowledged that, still today, they may constitute an appropriate tool for decision-making when confronting uncertainty, as he hinted at in his late 1930s correspondence with Hugh Townshend.
    Keywords: probability, uncertainty, decision-making
    JEL: B21 B31 D81
    Date: 2021–10
  14. By: Roman Frydman (New York University); Nicholas Mangee (Georgia Southern University)
    Abstract: This study introduces a novel index based on expectations concordance for explaining stock-price volatility when historically unique events cause unforeseeable change and Knightian uncertainty in the process driving outcomes. Expectations concordance measures the degree to which non-repetitive events are associated with directionally similar expectations of future returns. Narrative analytics of daily news reports allow for assessment of bullish versus bearish views in the stock market. Increases in expectations concordance across all KU events leads to reinforcing effects and an increase in stock market volatility. Lower expectations concordance produces a stabilizing effect wherein the offsetting views reduce market volatility. The empirical findings hold for ex post and ex ante measures of volatility and for OLS and GARCH estimates.
    Keywords: expectations concordance, narrative analytics, volatility, Knightian uncertainty
    JEL: D81 D84 G12 G14
    Date: 2021–09–05

General information on the NEP project can be found at For comments please write to the director of NEP, Marco Novarese at <>. Put “NEP” in the subject, otherwise your mail may be rejected.
NEP’s infrastructure is sponsored by the School of Economics and Finance of Massey University in New Zealand.