nep-rmg New Economics Papers
on Risk Management
Issue of 2022‒09‒12
34 papers chosen by

  1. Assessing Structure-Related Systemic Risk in Advanced Economies By O'Brien, Martin; Wosser, Michael
  2. Risk Weights on Non-Financial Corporate Lending by Irish Retail Banks By Lyons, Paul; Rice, Jonathan
  3. Rightsizing Bank Capital for Small, Open Economies By McInerney, Niall; O'Brien, Martin; Wosser, Michael; Zavalloni, Luca
  4. Saddlepoint approximations for credit portfolios with stochastic recoveries By Herbertsson, Alexander
  5. Deep Hedging: Continuous Reinforcement Learning for Hedging of General Portfolios across Multiple Risk Aversions By Phillip Murray; Ben Wood; Hans Buehler; Magnus Wiese; Mikko S. Pakkanen
  6. Latent fragility: conditioning banks' joint probability of default on the financial cycle By Bochmann, Paul; Hiebert, Paul; Schüler, Yves S.; Segoviano, Miguel
  7. ECB Monetary Policy and the Term Structure of Bank Default Risk By Tom Beernaert; Nicolas Soenen; Rudi Vander Vennet
  8. Does Disaster Risk Relate to Banks’ Loan Loss Provision Estimates? By Lorenzo Dal Maso; Kiridaran Kanagaretnam; Gerald Lobo; Francesco Mazzi
  9. Interbank credit exposures and financial stability By Schneorson, Oren
  10. Estimation of Historical volatility and Allocation strategies using Variance Swaps By Lucio Fiorin
  11. Bartlett's Delta revisited: Variance-optimal hedging in the lognormal SABR and in the rough Bergomi model By Martin Keller-Ressel
  12. Bank exposure to climate-related physical risk In Italy: an assessment based on AnaCredit data on loans to non-financial corporations By Giorgio Meucci; Francesca Rinaldi
  13. Systemic-risk and evolutionary stable strategies in a financial network By Indrajit Saha; Veeraruna Kavitha
  14. Skewed SVARs: tracking the structural sources of macroeconomic tail risks By Carlos Montes-Galdón; Eva Ortega
  15. Proposal for a 6C model of maturity of integrated risk management in the service sector By Saida Amansou; Hajar Benjana
  16. On Empirical Challenges in Forecasting Market Betas in Crypto Markets By Jan Sila; Michael Mark; Ladislav Kristoufek
  17. The certification role of the EU-wide stress testing exercises in the stock market. What can we learn from the stress tests (2014-2021)? By Durrani, Agha; Ongena, Steven; Ponte Marques, Aurea
  18. Quantum Encoding and Analysis on Continuous Stochastic Process By Xi-Ning Zhuang; Zhao-Yun Chen; Cheng Xue; Yu-Chun Wu; Guo-Ping Guo
  19. Rational Sentiments and Financial Frictions By Paymon Khorrami; Fernando Mendo
  20. Do EU-Wide Stress Tests Affect Insurers´ Dividend Policies? By Petr Jakubik; Saida Teleu
  21. Funding deposit insurance By Oosthuizen, Dick; Zalla, Ryan
  22. Hawkes processes framework with a Gamma density as excitation function: application to natural disasters for insurance By Laurent Lesage; Madalina Deaconu; Antoine Lejay; Jorge Augusto Meira; Geoffrey Nichil; Radu State
  23. Privatizing Disability Insurance By Arthur Seibold; Sebastian Seitz; Sebastian Siegloch
  24. Intensified competition and the impact on credit ratings in the RMBS market By van Breemen, Vivian M.; Fabozzi, Frank J.; Vink, Dennis
  25. Can a Machine Correct Option Pricing Models? By Caio Almeida; Jianqing Fan; Gustavo Freire; Francesca Tang
  26. Can EU bonds serve as euro-denominated safe assets? By Bletzinger, Tilman; Greif, William; Schwaab, Bernd
  27. Renewable energy and portfolio volatility spillover effects of GCC oil exporting countries By Bigerna, Simona; D'Errico, Maria Chiara; Polinori, Paolo; Simshauer, Paul
  28. The trade-off between public health and the economy in the early stage of the COVID-19 pandemic By Jaccard, Ivan
  29. Competition and Risk-Taking By Oliver Gürtler; Lennart Struth; Max Thon
  30. Recurrent property taxes and house price risks By O'Brien, Martin; Staunton, David; Wosser, Michael
  31. Scoring Aave Accounts for Creditworthiness By Will Wolf; Aaron Henry; Hamza Al Fadel; Xavier Quintuna; Julian Gay
  32. How well can experts predict farmers’ risk preferences? By Schaak, Henning
  33. Generic Price Model for Commodity Derivatives By Lee, David
  34. Risk and State-Dependent Financial Frictions By Martin Harding; Rafael Wouters

  1. By: O'Brien, Martin (Central Bank of Ireland); Wosser, Michael (Central Bank of Ireland)
    Abstract: We examine the role that economic size, the degree of trade and financial openness, dependancy on inward foreign direct investment and various aspects of banking system concentration play in determining systemic risk across advanced economies. Across the three systemic risk measures evaluated, we find that small, financially open and FD Idependent economies with more concentrated banking systems are more susceptible to severe tail risk outcomes and higher costs of crises than the average advanced economy. Small and financially open economies appear more likely to experience a systemic banking crisis than their counterparts. In most instances, the joint presence of these structural characteristics combine to further increase systemic risk levels and do not offset each other. Our findings suggest that a more activist macroprudential policy stance may be warranted for countries sharing these characteristics, so that the level of resilience is commensurate to the higher level of risk.
    Keywords: Systemic Risk, systemic banking crises, macroprudential policy, macrof inancial structure, macroprudential policy, financial stability.
    JEL: E5 G01 G21 G28
    Date: 2022–06
  2. By: Lyons, Paul (Central Bank of Ireland); Rice, Jonathan (Central Bank of Ireland)
    Abstract: Risk weighted assets reflect the risk profile of a bank’s lending. In this Note, we look at the risk weighted assets of the non-financial corporate (NFC) exposures of Irish and European banks. We find that Irish NFC risk weights are higher than those in most other European countries. Factors that explain these higher risk weights include the measurement approach used and the higher default rates for Irish NFC loans, particularly during crisis periods. Overall, the evidence suggests that the current risk weights on Irish NFC lending are reflective of the relatively higher risk of Irish retail banks’ NFC exposures.
    Date: 2022–06
  3. By: McInerney, Niall (Central Bank of Ireland); O'Brien, Martin (Central Bank of Ireland); Wosser, Michael (Central Bank of Ireland); Zavalloni, Luca (Central Bank of Ireland)
    Abstract: In a macroeconomic cost versus benefit framework, we determine the appropriate Tier 1 capital ratio for the banking system of advanced economies. Of particular interest is the appropriate bank capital range for countries sharing similar macrofinancial structural characteristics, during times of normal prevailing risk conditions. The characteristics considered include the relative size of the economy, trade and financial openness, the degree to which the country is FDI-dependent and various measures of banking system concentration. We find that, when the prevailing systemic risk environment is neither elevated nor subdued and other critical modelling parameters are set to plausible levels, an appropriate level for the Tier 1 capital ratio in advanced economies can lie in the range of 12% to 20%, with our benchmark estimate being 16%. When considering the additional risk inherent with being a small, open, FDI-reliant economy with a concentrated banking system, this range and benchmark can be up to 1.25 percentage points higher.
    Keywords: optimal bank capital, macroprudential policy, macro-financial structure, systemic risk, financial crises, financial regulation.
    JEL: E5 G01 G17 G28 R39
    Date: 2022–06
  4. By: Herbertsson, Alexander (Department of Economics, School of Business, Economics and Law, Göteborg University)
    Abstract: We study saddlepoint approximations to the tail-distribution for different credit portfolio losses in continuous time intensity based models which stochastic recoveries, under conditional independent homogeneous settings. In such models, conditional on the filtration generated by the individual default intensity up to time t, the conditional number of defaults distribution (in the portfolio) will be a binomial distribution that is a function of a factor Z_t which typically is the integrated default intensity up to time t. This will lead to an explicit closed-form solution of the saddlepoint equation for each point used in the number of defaults distribution when conditioning on the factor Z_t, and we hence do not have to solve the saddlepoint equation numerically. The ordo-complexity of our algorithm computing the whole distribution for the number of defaults will be linear in the portfolio size, which is a dramatic improvement compared to e.g. recursive methods which have a quadratic ordo-complexity in the portfolio size. The individual default intensities can be arbitrary as long as they are conditionally independent given the factor Z_t in a homogeneous portfolio. We also outline how our method for computing the number of defaults distribution can be extend to heterogeneous portfolios. Furthermore, we study the credit portfolio loss distribution with random recoveries. In particular, under the assumption that the stochastic recoveries are conditional binomial distributions correlated with the default times conditional on the factor Z_t, we derive very convenient semi closed-form expression for the credit portfolio loss distribution. Our algorithm for computing the tail-distribution at a point x for the credit portfolio loss with these random recoveries will have a ordo-complexity which is linear in x. Furthermore, we show that all our results, both for the number of defaults distribution and portfolio loss distribution with random recoveries, can be extended to hold for any factor copula model. In the case when the stochastic recoveries are independent of the default times, we give an example of how our method with random recoveries can be adapted to intensity based contagion models (which falls outside the family of conditional independent credit portfolio models). Finally, we give several numerical applications and in particular, in a setting where the individual default intensities follow a CIR process we study the time evolution of Value-at-Risk (i.e. VaR as function of time) both with constant and stochastic recoveries correlated with the default times. We then repeat similar numerical studies in a one-factor Gaussian copula model. We also numerically benchmark our method to other computational methods.
    Keywords: portfolio credit risk; intensity-based models; factor models; Value-at-Risk; conditional independent dependence modelling; saddlepoint-methods; Fourier-transform methods; numerical methods
    JEL: C02 C63 G13 G32 G33
    Date: 2022–08
  5. By: Phillip Murray; Ben Wood; Hans Buehler; Magnus Wiese; Mikko S. Pakkanen
    Abstract: We present a method for finding optimal hedging policies for arbitrary initial portfolios and market states. We develop a novel actor-critic algorithm for solving general risk-averse stochastic control problems and use it to learn hedging strategies across multiple risk aversion levels simultaneously. We demonstrate the effectiveness of the approach with a numerical example in a stochastic volatility environment.
    Date: 2022–07
  6. By: Bochmann, Paul; Hiebert, Paul; Schüler, Yves S.; Segoviano, Miguel
    Abstract: We propose the CoJPoD, a novel framework explicitly linking the cross-sectional and cyclical dimensions of systemic risk. In this framework, banking sector distress in the form of the joint probability of default of financial intermediaries (reflecting contagion from both direct and indirect interconnectedness) is conditioned on the financial cycle (reflecting the buildup and unwinding of system-wide balance sheet leverage). An empirical application to large systemic banks in the euro area, US and UK illustrates how the unravelling of excess leverage can magnify banking sector distress. Capturing this dependence of banking sector distress on prevailing financial imbalances can enhance risk surveillance and stress testing alike. An empirical signaling exercise confirms that the CoJPoD outperforms the individual capacity of either its unconditional counterpart or the financial cycle in signaling financial crises particularly around their onset - suggesting scope to increase the precision with which macroprudential policies are calibrated. JEL Classification: C19, C54, E58, G01, G21
    Keywords: financial crises, financial cycle, multivariate density optimization, portfolio credit risk, systemic risk
    Date: 2022–08
  7. By: Tom Beernaert; Nicolas Soenen; Rudi Vander Vennet (-)
    Abstract: Euro Area banks have been confronted with unprecedented monetary policy actions by the ECB. Monetary policy may affect bank risk profiles, but the consequences may differ for short-term risk versus long-term or structural bank risk. We empirically investigate the association between the ECB’s monetary policy stance and market-perceived shortterm and long-term bank risk, using the term structure of default risk captured by bank CDS spreads. The results demonstrate that, during the period 2009-2020, ECB expansionary monetary policy diminished bank default risk in the short term. However, we do not observe a similar decline in long-term bank default risk, since we document that monetary stimulus is associated with a steepening of the bank default risk curve. The reduction of bank default risk is most pronounced during the sovereign debt crisis and for periphery Euro Area banks. From 2018 onwards, monetary policy accommodation is associated with increased bank default risk, both short term and structurally, which is consistent with the risk-taking hypothesis under which banks engage in excessive risk-taking behavior in their loan and securities portfolios to compensate profitability pressure caused by persistently low rates. The increase in perceived default risk is especially visible for banks with a high reliance on deposit funding.
    Keywords: Monetary policy, ECB, Bank default risk, Term structure of credit risk
    JEL: C58 G21 G32 E52
    Date: 2022–08
  8. By: Lorenzo Dal Maso (University of Bologna); Kiridaran Kanagaretnam (Schulich School of Business); Gerald Lobo (University of Houston); Francesco Mazzi (University of Florence)
    Abstract: We examine the relation between disaster risk and banks’ loan loss provision (LLP) estimates. We propose a disaster risk measure based on the natural disasters declared as major disasters by the Federal Emergency Management Agency over the past fifteen years. We theoretically support and empirically validate our measure using three different approaches, including the UN Sendai Framework for disaster risk reduction, which relates disaster risk to natural hazard exposure, vulnerability and capacity, and hazard characteristics. Using more than 445,000 bank-quarter observations, we document that banks located in counties with higher disaster risk recognize larger LLP after controlling for other bank-level factors related to LLP estimates. We employ several techniques to ensure the robustness of our findings, including difference-in-differences estimation and matched samples. In additional analysis, we propose three alternative measures of disaster risk, explore the characteristics that better enable banks to recognize disaster risk in their LLP estimates, and investigate the consequences of managing disaster risk through LLP. Our results are important, especially because of the increasing concern about disaster risk and because they inform the growing debate on the economic consequences of disaster risk and the ability of the banking system to proactively manage the resulting credit risk through LLPs.
    Keywords: Disaster Risk, Loan Loss Provisions, Future Charge-offs, Future Risk-Taking, Banks
    JEL: M40 M41 G20 G21 E50 E59
    Date: 2022
  9. By: Schneorson, Oren
    Abstract: This paper investigates how interbank credit exposures affect financial stability. Policy makers often see such exposures as undermining stability by exacerbating cascading losses through the financial system. I develop a model that features a trade-off between cascading losses and risk-sharing. In contrast to previous studies I find that reducing interbank connectivity may destabilize the financial system via the bank-run channel. This is because it decreases the risk-sharing benefits of interbank connectivity. A bank-run model features two islands that are connected via a long term debt claim. Varying the size of this claim (interbank connectivity), I study how the decision to `run on the bank' is affected. I run a simulation of the model, calibrated to the U.S. banking system between 1997-2007. I find that large bankruptcy costs are required to trump the risk-sharing benefits of interbank credit exposures. JEL Classification: G01, G21, G28
    Keywords: bank runs, credit risk, derivatives, financial stability
    Date: 2022–08
  10. By: Lucio Fiorin
    Abstract: In this memorie de fin d'etudes, we review some techniques to estimate historical volatility and to price Variance Swaps
    Date: 2022–08
  11. By: Martin Keller-Ressel
    Abstract: We derive analytic expressions for the variance-optimal hedging strategy and its mean-square hedging error in the lognormal SABR and in the rough Bergomi model. In the SABR model, we show that the variance-optimal hedging strategy coincides with the Delta adjustment of Bartlett [Wilmott magazine 4/6 (2006)]. We show both mathematically and in simulation that the efficiency of the variance-optimal strategy (in comparison to simple Delta hedging) depends strongly on the leverage parameter rho and - in a weaker sense - also on the roughness parameter H of the model, and give a precise quantification of this dependency.
    Date: 2022–07
  12. By: Giorgio Meucci (Bank of Italy); Francesca Rinaldi (Bank of Italy)
    Abstract: This study provides a first assessment of Italian banks' exposure to physical risk arising from climate change in relation to lending to non-financial corporates. Based on granular data on loans and on the likelihood of climate-related events, we quantify to what extent physical risk could impair the loan portfolios both by lowering borrowers’ capacity to pay and by decreasing the value of collateral. The analysis shows that Italian banks' exposure to physical risk is limited overall. In general, only a few small intermediaries seem to face severe potential exposure to physical risk. More than half of the risky loans are secured by collateral. However, there is a large overlap between the location of the debtor companies and the real estate collateral offered as a guarantee. Hence, the exposure through loans is highly correlated with the exposure through collateral, leading to a potential positive correlation between the probability of default (PD) and the loss given default (LGD) of exposures in the event that climate risk materializes.
    Keywords: climate change, climate risk, physical risk, credit risk
    JEL: Q54
    Date: 2022–07
  13. By: Indrajit Saha; Veeraruna Kavitha
    Abstract: We consider a financial network represented at any time instance by a random liability graph which evolves over time. The agents connect through credit instruments borrowed from each other or through direct lending, and these create the liability edges. These random edges are modified (locally) by the agents over time, as they learn from their experiences and (possibly imperfect) observations. The settlement of the liabilities of various agents at the end of the contract period (at any time instance) can be expressed as solutions of random fixed point equations. Our first step is to derive the solutions of these equations (asymptotically and one for each time instance), using a recent result on random fixed point equations. The agents, at any time instance, adopt one of the two available strategies, risky or risk-free investments, with an aim to maximize their returns. We aim to study the emerging strategies of such replicator dynamics that drives the financial network. We theoretically reduce the analysis of the complex system to that of an appropriate ordinary differential equation (ODE). Using the attractors of the resulting ODE we showed that the replicator dynamics converges to one of the two pure evolutionary stable strategies (all risky or all risk-free agents); one can have mixed limit only when the observations are imperfect. We verified our theoretical findings using exhaustive Monte Carlo simulations. We established that the dynamics avoid the emergence of the systemic-risk regime (where majority default).
    Date: 2022–06
  14. By: Carlos Montes-Galdón (European Central Bank); Eva Ortega (Banco de España)
    Abstract: This paper proposes a vector autoregressive model with structural shocks (SVAR) that are identified using sign restrictions and whose distribution is subject to time-varying skewness. It also presents an efficient Bayesian algorithm to estimate the model. The model allows for the joint tracking of asymmetric risks to macroeconomic variables included in the SVAR. It also provides a narrative about the structural reasons for the changes over time in those risks. Using euro area data, our estimation suggests that there has been a significant variation in the skewness of demand, supply and monetary policy shocks between 1999 and 2019. This variation lies behind a significant proportion of the joint dynamics of real GDP growth and inflation in the euro area over this period, and also generates important asymmetric tail risks in these macroeconomic variables. Finally, compared to the literature on growth- and inflation-at-risk, we found that financial stress indicators do not suffice to explain all the macroeconomic tail risks.
    Keywords: Bayesian SVAR, skewness, growth-at-risk, inflation-at-risk
    JEL: C11 C32 C51 E31 E32
    Date: 2022–03
  15. By: Saida Amansou (Université Mohammed Premier [Oujda]); Hajar Benjana (Université Mohammed Premier [Oujda])
    Abstract: Risk is a probable event in terms of its probability of occurrence, it is omnipresent which makes its management an imperative for organizations. As a result, many researchers have fallen in love with developing models to study the degree of maturity inherent in its management. Such models are essential as they allow organizations to test their level of awareness of risks and their ability to manage them. The objective of this research is not only to propose a model for measuring the maturity of integrated risk management but also to analyze the specificities specific to companies belonging to the bosom of the service sector in Morocco. In doing so, it is essential to underline the growing role of services in the Gross Domestic Product (GDP) and in the Moroccan economy as a whole. The service sector created an added value of around 56.5% in 2017, a share largely exceeding that secreted by the secondary (29.5%) and primary (14%) sectors. However, this sector remains, despite the great opportunities seized, threatened by several risks that could jeopardize its performance or even the sustainability of its companies
    Abstract: Le risque est un évènement probable quant à sa probabilité d'occurrence, il est omniprésent ce qui rend sa gestion un impératif pour les organisations. De ce fait, certains chercheurs se sont épris d'élaborer des modèles en vue d'étudier le degré de maturité inhérent à sa gestion. Tels modèles s'avèrent indispensables puisqu'ils permettent aux organisations de tester leur niveau de sensibilisation par rapport aux risques et leurs aptitudes à les gérer. L'objectif de cette recherche n'est pas seulement de proposer un modèle de maturité de la gestion intégrée des risques mais d'analyser en outre les spécificités propres aux entreprises appartenant au giron du secteur des services au Maroc. Ce faisant, il est indispensable de souligner la place grandissante des services dans le Produit Intérieur Brut (PIB) et dans l'économie marocaine dans son ensemble. Le secteur des services a créé une valeur ajoutée de l'ordre de 56,5% en 2017, une part dépassant largement celle sécrétée par le secteur secondaire (29,5%) et celui primaire (14%). Cependant, ce secteur reste, en dépit des grandes opportunités saisies, menacé par plusieurs risques pouvant mettre en péril sa performance voire la pérennité de ses entreprises.
    Keywords: Risk,Maturity model,Integrated risk management,6C,Services sector,Risque,Modèle de maturité,Gestion intégrée des risques,Secteur des services.
    Date: 2021
  16. By: Jan Sila (Institute of Economic Studies, Faculty of Social Sciences, Charles University & The Czech Academy of Sciences, Institute of Information Theory and Automation, Prague, Czech Republic); Michael Mark (Chair of Operations, Economics and Strategy, Ecole Polytechnique Federale de Lausanne, Station 5, CH-1015 Lausanne, Switzerland); Ladislav Kristoufek (Institute of Economic Studies, Faculty of Social Sciences, Charles University & The Czech Academy of Sciences, Institute of Information Theory and Automation, Prague, Czech Republic)
    Abstract: This paper investigates the predictability of market betas for crypto assets. The market beta is the optimal weight of a short position in a simple two-asset portfolio hedging the market risk. Investors are therefore keen to forecast the market beta accurately. Estimating the market beta is a fundamental financial problem and we document pervasive empirical issues that arise in the emerging market of crypto assets. Although recent empirical results about US stocks suggest predictability of the future realized betas about 55%, predictability for the universe of crypto assets is at most 20%. Our results suggest that the crypto market betas are highly sensitive not only to the beta estimation method but also to the selection of the market index. Thus we also contribute to the discussion on the appropriate market representation.
    Keywords: C21,C53,C58,G12
    Date: 2022–08
  17. By: Durrani, Agha; Ongena, Steven; Ponte Marques, Aurea
    Abstract: What is the impact of stress tests on bank stock prices? To answer this question we study the impact of the publication of the EU-wide stress tests in 2014, 2016, 2018, and 2021 on the first (λ) and second (δ) moment of equity returns. First, we study the effect of the disclosure of stress tests on (cumulative) excess/abnormal returns through a one-factor market model. Second, we study whether both returns and volatility of bank stock prices changes upon the disclosure of stress tests through a structural GARCH model, developed by Engle and Siriwardane (2018). Our results suggest that the publication of stress tests provides new information to markets. Banks performing poorly in stress tests experience, on average, a reduction in returns and an increase in volatility, while the reverse holds true for banks performing well. Banks performing moderately have rather a small effect on both mean and variance process. Our findings are corroborated by the observed rank correlation between bank abnormal returns or equity volatility and stress test performance, which experiences a steady increase after each publication event. These results suggest that the publication of stress tests improves price discrimination between 'good' and 'bad' banks, which can be interpreted as a certification role of the stress tests in the stock market. JEL Classification: G11, G14, G21, G28
    Keywords: excess return, financial stability, stock markets, stress tests, volatility
    Date: 2022–08
  18. By: Xi-Ning Zhuang; Zhao-Yun Chen; Cheng Xue; Yu-Chun Wu; Guo-Ping Guo
    Abstract: The continuous time stochastic process is a mainstream mathematical instrument modeling the random world with a wide range of applications involving finance, statistics, physics, and time series analysis, while the simulation and analysis of the continuous time stochastic process is a challenging problem for classical computers. In this work, a general framework is established to prepare the path of a continuous time stochastic process in a quantum computer efficiently. The storage and computation resource is exponentially reduced on the key parameter of holding time, as the qubit number and the circuit depth are both optimized via our compressed state preparation method. The desired information, including the path-dependent and history-sensitive information that is essential for financial problems, can be extracted efficiently from the compressed sampling path, and admits a further quadratic speed-up. Moreover, this extraction method is more sensitive to those discontinuous jumps capturing extreme market events. Two applications of option pricing in Merton jump diffusion model and ruin probability computing in the collective risk model are given.
    Date: 2022–08
  19. By: Paymon Khorrami; Fernando Mendo
    Abstract: We provide a complete analysis of previously undocumented sunspot equilibria in a canonical dynamic economy with imperfect risk sharing. Methodologically, we employ stochastic stability theory to establish existence of this broad class of sunspot equilibria. Economically, self-fulfilling fluctuations are characterized by uncertainty shocks: changing beliefs about volatility trigger asset trades, which impacts productive efficiency and justifies the degree of uncertainty. We show how rational sentiment helps resolve two puzzles in the macro-finance literature: (i) financial crises emerge suddenly, featuring (quantitatively) hard-to-explain volatility spikes and asset-price declines; (ii) asset-price booms, with below-average risk premia, predict busts and financial crises.
    Date: 2021–10
  20. By: Petr Jakubik (European Insurance and Occupational Pensions Authority (EI-OPA), Germany & Charles University in Prague, Faculty of Social Sciences, Institute of Economic Studies, Czech Republic); Saida Teleu (Central Bank of Malta, Malta & Charles University in Prague, Faculty of Social Sciences, Institute of Economic Studies, Czech Republic)
    Abstract: The article employs panel data to investigate whether stress test results and other characteristics associated with European insurers vulnerabilities affect dividend distributions and share buybacks. We focus on the EU wide insurance stress test conducted in 2018 and 2021 as in this way we can also capture a behaviour of insurers during the COVID-19 crisis. Our empirical results suggest that two stress tests considered had no significant impact on changes in dividend distributions. However, more resilient insurers measured by assets-over-liabilities ratio seem to have higher dividend payout ratios including share buybacks. On the contrary, higher generated profit tend to be reflected in lower payout ratio.
    Keywords: dividend distributions; dividends and share buybacks; European insurers; EU-wide insurance stress test, COVID-19
    Date: 2022–08
  21. By: Oosthuizen, Dick; Zalla, Ryan
    Abstract: We present a quantitative model of deposit insurance. We characterize the policymaker’s optimal choices of coverage for depositors and premiums raised from banks. Premiums contribute to a deposit insurance fund that lowers taxpayers’ resolution cost of bank failures. We find that risk-adjusted premiums reduce moral hazard, enabling the policymaker to increase deposit insurance coverage by 3 percentage points and decrease the share of expected annual bank failures from 0.66% to 0.16%. The model predicts a fund-to-covered-deposits ratio that matches the data and declines in taxpayers’ income due to taxpayers’ risk aversion. JEL Classification: G21, G28
    Keywords: bank regulation, bank runs, deposit insurance
    Date: 2022–08
  22. By: Laurent Lesage (IECL - Institut Élie Cartan de Lorraine - UL - Université de Lorraine - CNRS - Centre National de la Recherche Scientifique, SnT - Interdisciplinary Centre for Security, Reliability and Trust [Luxembourg] - - Université du Luxembourg, Foyer Assurances [Leudelange], PASTA - Processus aléatoires spatio-temporels et leurs applications - Inria Nancy - Grand Est - Inria - Institut National de Recherche en Informatique et en Automatique - IECL - Institut Élie Cartan de Lorraine - UL - Université de Lorraine - CNRS - Centre National de la Recherche Scientifique); Madalina Deaconu (IECL - Institut Élie Cartan de Lorraine - UL - Université de Lorraine - CNRS - Centre National de la Recherche Scientifique, PASTA - Processus aléatoires spatio-temporels et leurs applications - Inria Nancy - Grand Est - Inria - Institut National de Recherche en Informatique et en Automatique - IECL - Institut Élie Cartan de Lorraine - UL - Université de Lorraine - CNRS - Centre National de la Recherche Scientifique, TOSCA-NGE-POST - Simuler et calibrer des modèles stochastiques - Inria Nancy - Grand Est - Inria - Institut National de Recherche en Informatique et en Automatique); Antoine Lejay (IECL - Institut Élie Cartan de Lorraine - UL - Université de Lorraine - CNRS - Centre National de la Recherche Scientifique, PASTA - Processus aléatoires spatio-temporels et leurs applications - Inria Nancy - Grand Est - Inria - Institut National de Recherche en Informatique et en Automatique - IECL - Institut Élie Cartan de Lorraine - UL - Université de Lorraine - CNRS - Centre National de la Recherche Scientifique, TOSCA-NGE-POST - Simuler et calibrer des modèles stochastiques - Inria Nancy - Grand Est - Inria - Institut National de Recherche en Informatique et en Automatique); Jorge Augusto Meira (SnT - Interdisciplinary Centre for Security, Reliability and Trust [Luxembourg] - - Université du Luxembourg); Geoffrey Nichil (Foyer Assurances [Leudelange]); Radu State (SnT - Interdisciplinary Centre for Security, Reliability and Trust [Luxembourg] - - Université du Luxembourg)
    Abstract: Hawkes process are temporal self-exciting point processes. They are well established in earthquake modelling or finance and their application is spreading to diverse areas. Most models from the literature have two major drawbacks regarding their potential application to insurance. First, they use an exponentially-decaying form of excitation, which does not allow a delay between the occurrence of an event and its excitation effect on the process and does not fit well on insurance data consequently. Second, theoretical results developed from these models are valid only when time of observation tends to infinity, whereas the time horizon for an insurance use case is of several months or years. In this paper, we define a complete framework of Hawkes processes with a Gamma density excitation function (i.e. estimation, simulation, goodness-of-fit) instead of an exponential-decaying function and we demonstrate some mathematical properties (i.e. expectation, variance) about the transient regime of the process. We illustrate our results with real insurance data about natural disasters in Luxembourg.
    Keywords: Point processes,Hawkes processes,insurance,EM algorithm,natural disasters
    Date: 2022–03–05
  23. By: Arthur Seibold (University of Mannheim and CEPR); Sebastian Seitz (University of Manchester); Sebastian Siegloch (University of Cologne, ZEW and CEPR)
    Abstract: Public disability insurance (DI) programs in many countries face pressure to reduce their generosity in order to remain sustainable. In this paper, we investigate the welfare effects of giving a larger role to private insurance markets in the face of public DI cuts. Exploiting a unique reform that abolished one part of the German public DI system for younger workers, we find that despite significant crowding-in effects, overall private DI take-up remains modest. We do not find any evidence of adverse selection on unpriced risk. On the contrary, private DI tends to be concentrated among high-income, high-education and low-risk individuals. Using a revealed preferences approach, we estimate individual DI valuations, a key input for welfare calculations. We find that observed willingness-to-pay of many individuals is low, such that providing DI partly via a private insurance market with choice improves welfare. However, we show that distributional concerns as well as individual risk misperceptions can provide grounds for justifying a full public DI mandate.
    Keywords: disability insurance, social insurance, mandate, privatization, risk-based selection, welfare
    JEL: H55 G22 G52
    Date: 2022–08
  24. By: van Breemen, Vivian M.; Fabozzi, Frank J.; Vink, Dennis
    Abstract: In this paper, we empirically investigate the impact of intensified competition on rating quality in the credit rating market for residential mortgage-backed securities (RMBS) in the period 2017-2020. We provide evidence that competition between large credit rating agencies (CRAs) (Moody’s and Standard & Poor’s) and newer smaller ones (Dominion Bond Rating Service Morningstar and Kroll Bond Rating Agency) creates credit rating inconsistencies in the RMBS market. While a credit rating should solely represent the underlying credit risk of a RMBS, irrespective of the competition in the market, our results show that this is not the case. When competitive pressure increases, both large and small CRAs tend to adjust their rating standards (smaller CRAs react to large CRAs and vice versa). JEL Classification: G15, G21, G24, G28
    Keywords: competitive pressure, credit rating agencies, rating quality
    Date: 2022–07
  25. By: Caio Almeida (Princeton University); Jianqing Fan (Princeton University); Gustavo Freire (Erasmus School of Economics); Francesca Tang (Princeton University)
    Abstract: We introduce a novel two-step approach to predict implied volatility surfaces. Given any fitted parametric option pricing model, we train a feedforward neural network on the model-implied pricing errors to correct for mispricing and boost performance. Using a large dataset of S&P 500 options, we test our nonparametric correction on several parametric models ranging from ad-hoc Black-Scholes to structural stochastic volatility models and demonstrate the boosted performance for each model. Out-of-sample prediction exercises in the cross-section and in the option panel show that machine-corrected models always outperform their respective original ones, often by a large extent. Our method is relatively indiscriminate, bringing pricing errors down to a similar magnitude regardless of the misspecification of the original parametric model. Even so, correcting models that are less misspecified usually leads to additional improvements in performance and also outperforms a neural network fitted directly to the implied volatility surface.
    Keywords: Deep Learning, Boosting, Implied Volatility, Stochastic Volatility, Model Correction
    JEL: C45 C58 G13
    Date: 2022–07
  26. By: Bletzinger, Tilman; Greif, William; Schwaab, Bernd
    Abstract: A safe asset is of high credit quality, retains its value in bad times, and is traded in liquid markets. We show that bonds issued by the European Union (EU) are widely considered to be of high credit quality, and that their yield spread over German Bunds remained contained during the 2020 Covid-19 pandemic recession. Recent issuances and taps under the EU’s SURE and NGEU initiatives helped improve EU bonds' market liquidity from previously low levels, also reducing liquidity risk premia. Eurosystem purchases and holdings of EU bonds did not impair market liquidity. Currently, one obstacle to EU bonds achieving a genuine euro-denominated safe asset status, approaching that of Bunds, lies in the one-off, time-limited nature of the EU’s Covid-19-related policy responses. JEL Classification: E58, G12, H63
    Keywords: EU-issued bonds, European Central Bank, European Union, market liquidity, NextGenerationEU (NGEU), Pandemic Emergency Purchase Programme (PEPP)
    Date: 2022–08
  27. By: Bigerna, Simona; D'Errico, Maria Chiara; Polinori, Paolo; Simshauer, Paul
    Abstract: Over time, Gulf Cooperation Council (GCC) countries have accumulated large oil portfolio revenues. But the world economy is seeking to reduce greenhouse gas emissions and in turn, its reliance on fossil fuel resources through ongoing investments in renewable energy resources. In this article, we construct oil portfolios for four of the GCC countries (viz. Kuwait, Saudi Arabia, United Arab Emirates, Oman) and focus on their top five importing counterparties. Portfolio returns (quantity and price) have been derived between 2008-2018 with volatility spillovers computed via Diebold and Yilmaz’s dynamic spillover index approach. The spillover analysis shows a consistent reallocation effect amongst spillover directions together with their generalized increases. The structural rigidity of oil demand was confirmed with ‘quantity’ Total Volatility Spillovers being lower than ‘price’ Total Volatility Spillovers. Analysis of net contributors for both kinds of volatility found China to be a “net transferer” in quantity spillovers, and India seemingly absorbing quantity and price shocks. We find economic policy uncertainty and rising renewable market shares significantly affects volatility spillovers in oil export portfolios. Although some degree of heterogeneity exists, greater deployment of renewables in importing nations reduces adverse impacts of oil market fluctuations. This result and broader ‘net-zero’ policy commitments means rising renewable market shares are predictable. For GCC countries, two consequential long run risks arise, viz. loss of revenues and stranded oil reserves, which has its own policy implications.
    Keywords: Gulf Cooperation Council countries; oil exports; total volatility spillovers; renewables; volatility determinants, energy security
    JEL: C32 C58 G32 O53 Q41
    Date: 2022–08–11
  28. By: Jaccard, Ivan
    Abstract: How does contagion risk affect the business cycle? We find that the presence of contagion risk significantly alters the transmission of standard macroeconomic shocks. Relative to the first-best equilibrium, the contagion externality significantly reduces the response of output to a technology shock. We also argue that the magnitude of the trade-off between health and the economy crucially depends on how the probability of infection is specified. If the probability of infection only depends on agents’ endogenous choices, a weaker trade-off emerges. In such a framework, and relative to the laissez-faire equilibrium, suboptimal policies such as zero COVID strategies, health insurance, or mandatory testing substantially attenuate recessions that are caused by epidemics. Therefore, policies primarily aimed at preserving public health do not necessarily come at the cost of deeper recessions. JEL Classification: E1, H0, I1
    Keywords: Contagion Externality, Incomplete Markets, Lockdown Policies, Risk Sharing
    Date: 2022–07
  29. By: Oliver Gürtler (University of Cologne); Lennart Struth (University of Cologne); Max Thon (University of Cologne)
    Abstract: In many situations, agents take risks by choosing an action that increases their performance immediately, but that potentially leads to a large loss. The current paper studies how such risk-taking behavior depends on the level of competition that the agents face. We study a tournament model and we find that more intense competition, measured by the number of competitors as well as their relative standing, induces agents to take higher risks. We use a rich panel data set on professional biathlon competitions as well as survey data from professional biathletes to confirm the model predictions. Finally, we discuss managerial implications.
    Keywords: Risk-taking, competition, tournament, incentives, biathlon
    JEL: M51 M52 Z22
    Date: 2022–08
  30. By: O'Brien, Martin (Central Bank of Ireland); Staunton, David (Central Bank of Ireland); Wosser, Michael (Central Bank of Ireland)
    Abstract: Recurrent property taxes form part of the tax system in most advanced economies. In this Letter we examine whether these taxes have broader benefits in terms of reducing down-side risk to house prices, and the volatility of potential house price outcomes overall. The results suggest that such benefits do exist. Combined with the steadiness of these tax revenues through the economic cycle, fiscal authorities could benefit from appropriately calibrated recurrent property taxes while also contributing to wider economic and financial stability.
    Date: 2022–07
  31. By: Will Wolf; Aaron Henry; Hamza Al Fadel; Xavier Quintuna; Julian Gay
    Abstract: Scoring the creditworthiness of accounts that interact with decentralized financial (DeFi) protocols remains an important yet unsolved problem. In this paper, we propose a credit scoring system for those accounts that have interacted with the Aave v2 liquidity protocol. The key component of this system is a tree-based binary classifier that predicts "position delinquency." To the community, we provide our method, results, and the (abridged) dataset on which this system is built.
    Date: 2022–07
  32. By: Schaak, Henning
    Keywords: Research Methods/Statistical Methods, Risk and Uncertainty, Agricultural Finance
    Date: 2022–08
  33. By: Lee, David
    Abstract: This article develops a new framework for modeling the dynamics of commodity forward curves and pricing commodity derivatives. The model accommodates a generic calibration procedure to ensure that the model prices for vanilla options match exactly the market prices. Empirically we show that the model prices are within the bid-offer spreads, indicating prima facie that the model performs quite well. We also show that the model prices for non-vanilla options are in good agreement with the market prices and the implied model dynamics are in good agreement with the characteristics of the historical data series.
    Keywords: commodity derivatives, multiple factor model, model calibration, volatility skew
    JEL: C5 C51 C58 G12 G13 G15 G17
    Date: 2022–08–22
  34. By: Martin Harding; Rafael Wouters
    Abstract: We augment a standard New Keynesian model with a financial accelerator mechanism and show that financial frictions generate large state-dependent amplification effects. We fit the model to US data and show that show that, when shocks drive the model far away from the steady state, the nonlinear model produces much stronger propagation of shocks than the linearized model. We document that these amplification effects are due to endogenous variation in financial conditions and not due to other nonlinearities in the model. Motivated by these findings, we propose a regime-switching dynamic stochastic general equilibrium framework where financial frictions endogenously fluctuate between moderate (low risk) and severe (high risk), depending on the state of the economy. This framework allows for efficient estimation with many state variables and improves fit with respect to the linear model.
    Keywords: Central bank research; Credit and credit aggregates; Financial stability; Monetary policy
    JEL: E52 E58
    Date: 2022–08

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.