nep-rmg New Economics Papers
on Risk Management
Issue of 2017‒07‒02
eighteen papers chosen by
Stan Miles
Thompson Rivers University

  1. Updating the Long Term Rate in Time: A Possible Approach By Fabrice Borel-Mathurin; Stéphane Loisel; Johan Segers
  2. The leverage ratio, risk-taking and bank stability By Smith, Jonathan Acosta; Grill, Michael; Lang, Jan Hannes
  3. Smoothing Algorithms by Constrained Maximum Likelihood By Yang, Bill Huajian
  4. Information Contagion and Systemic Risk By Toni Ahnertand; Co-Pierre Georg
  5. Assessing Systemic Risk of the European Insurance Industry By Elia Berdin; Matteo Sottocornola
  6. Identification of Credit Risk Based on Cluster Analysis of Account Behaviours By Maha Bakoben; Tony Bellotti; Niall Adams
  7. Systemic risk for financial institutions of major petroleum-based economies: The role of oil By Khalifa, Ahmed; Caporin, Massimiliano; Costola, Michele; Hammoudeh, Shawkat
  8. Risk Model Based on General Compound Hawkes Process By Anatoliy Swishchuk
  9. Extreme portfolio loss correlations in credit risk By Andreas M\"uhlbacher; Thomas Guhr
  10. Realized Stochastic Volatility with General Asymmetry and Long Memory By Manabu Asai; Chia-Lin Chang; Michael McAleer
  11. Welfare analysis of bank capital requirements with endogenous default By Fernando Garcia-Barragan; Guangling Liu
  12. Subprime Mortgages and Banking in a DSGE Model By Martino, Ricci; Patrizio, Tirelli
  13. Bitcoin and Global Financial Stress: A Copula-Based Approach to Dependence and Causality-in-Quantiles By Elie Bouri; Rangan Gupta; Chi Keung Marco Lau; David Roubaud; Shixuan Wang
  14. Modeling and forecasting electricity price jumps in the Nord Pool power market By Oskar Knapik
  15. Die Genossenschaftliche Institutssicherung – ein notwendiges Instrument zur Stärkung des Kundenvertrauens und des Risikomanagements im dezentralen Bankenverbund By Gleber, Peter
  16. Primary Dealers' Behavior during the 2007-08 Crisis : Part I, Repo Runs By Rajkamal Iyer; Marco Macchiavelli
  17. Risk indicators for financial market infrastructure: from high frequency transaction data to a traffic light signal By Ron Berndsen; Ronald Heijmans
  18. Mortgage Default in an Estimated Model of the U.S. Housing Market By Lambertini Luisa; Nuguer Victoria; Uysal Pinar

  1. By: Fabrice Borel-Mathurin; Stéphane Loisel; Johan Segers (EIOPA)
    Abstract: Motivated by the recent introduction of regulatory stress tests in the Solvency II framework, we study the impact of the re-estimation of the tail risk and of loss absorbing capacities on post-stress solvency ratios. Our contribution is threefold. First, we build the first stylised model for re-estimated solvency ratio in insurance. Second, this leads us to solve a new theoretical problem in statistics: what is the asymptotic impact of a record on the re-estimation of tail quantiles and tail probabilities for classical extreme value estimators? Third, we quantify the impact of the re-estimation of tail quantiles and of loss absorbing capacities on real-world solvency ratios thanks to regulator data from Banque de France – ACPR. Our analysis sheds a first light on the role of the loss absorbing capacity and its paramount importance in the Solvency II capital charge computations. We conclude with a number of policy recommendations for insurance regulators.
    Keywords: Insurance, Extreme Value Theory, Financial Regulation, Solvency II, Solvency Capital Requirement, Loss Absorbing Capacities, Stress Tests, Enterprise Risk Management
    JEL: G01 G22 G32
    Date: 2017–06
  2. By: Smith, Jonathan Acosta; Grill, Michael; Lang, Jan Hannes
    Abstract: This paper addresses the trade-off between additional loss-absorbing capacity and potentially higher bank risk-taking associated with the introduction of the Basel III Leverage Ratio. This is addressed in both a theoretical and empirical setting. Using a theoretical micro model, we show that a leverage ratio requirement can incentivise banks that are bound by it to increase their risk-taking. This increase in risk-taking however, should be more than outweighed by the benefits of higher capital and therefore increased loss-absorbing capacity, thereby leading to more stable banks. These theoretical predictions are tested and confirmed in an empirical analysis on a large sample of EU banks. Our baseline empirical model suggests that a leverage ratio requirement would lead to a significant decline in the distress probability of highly leveraged banks. JEL Classification: G01, G21, G28
    Keywords: bank capital, Basel III, leverage ratio, risk-taking
    Date: 2017–06
  3. By: Yang, Bill Huajian
    Abstract: In the process of loan pricing, stress testing, capital allocation, modeling of PD term structure, and IFRS9 expected credit loss estimation, it is widely expected that higher risk grades carry higher default risks, and that an entity is more likely to migrate to a closer non-default rating than a farther away non-default rating. In practice, sample estimates for rating level default rate or rating migration probability do not always respect this monotonicity rule, and hence the need for smoothing approaches. Regression and interpolation techniques are widely used for this purpose. A common issue with these approaches is that the risk scale for the estimates is not fully justified, leading to a possible bias in credit loss estimates. In this paper, we propose smoothing algorithms for rating level PD and rating migration probability. The smoothed estimates obtained by these approaches are optimal in the sense of constrained maximum likelihood, with a fair risk scale determined by constrained maximum likelihood, leading to more robust credit loss estimation. The proposed algorithms can be easily implemented by a modeller using, for example, the SAS procedure PROC NLMIXED. The approaches proposed in this paper will provide an effective and useful smoothing tool for practitioners in the field of risk modeling.
    Keywords: Credit loss estimation, risk scale, constrained maximum likelihood, PD term structure, rating migration probability
    JEL: C1 C13 C18 C5 C51 C52 C53 C54 C61 C63 E5 G31 G38 O32 O33 O38
    Date: 2017–06
  4. By: Toni Ahnertand; Co-Pierre Georg
    Abstract: We examine the effect of ex-post information contagion on the ex-ante optimal portfolio choices of banks and the welfare losses due to joint default. Because of counterparty risk and common exposures, bad news about one bank reveals valuable information about another bank, thereby triggering information contagion. Systemic risk is defined as the ex-ante probability of joint bank default ex post. We find that information contagion increases systemic risk when banks are subject to common exposures since portfolio adjustments are small. In contrast, when banks are subject to counterparty risk, information contagion induces a large shift toward more prudential portfolios and therefore reduces systemic risk.
    Keywords: information contagion, counterparty risk, common exposure, systemic risk
    JEL: G01 G21
    Date: 2017–06
  5. By: Elia Berdin; Matteo Sottocornola (EIOPA)
    Abstract: This paper investigates the systemic relevance of the insurance industry. We do it by analysing the systemic contribution of the insurance industry vis-á-vis other industries by applying three measures, namely the linear Granger causality test, conditional value at risk and marginal expected shortfall, to three groups, namely banks, insurers and non-financial companies listed in Europe over the last 14 years. Our evidence suggests that the insurance industry shows i) a persistent systemic relevance over time, ii) it plays a subordinate role in causing systemic risk compared to banks. In addition, iii) we do not find clear evidence on the higher systemic relevance of SIFI insurers compared to non-SIFIs.
    Keywords: Insurance, Systemic Risk, financial stability
    JEL: G22 G28 E27
    Date: 2015–12
  6. By: Maha Bakoben; Tony Bellotti; Niall Adams
    Abstract: Assessment of risk levels for existing credit accounts is important to the implementation of bank policies and offering financial products. This paper uses cluster analysis of behaviour of credit card accounts to help assess credit risk level. Account behaviour is modelled parametrically and we then implement the behavioural cluster analysis using a recently proposed dissimilarity measure of statistical model parameters. The advantage of this new measure is the explicit exploitation of uncertainty associated with parameters estimated from statistical models. Interesting clusters of real credit card behaviours data are obtained, in addition to superior prediction and forecasting of account default based on the clustering outcomes.
    Date: 2017–05
  7. By: Khalifa, Ahmed; Caporin, Massimiliano; Costola, Michele; Hammoudeh, Shawkat
    Abstract: This paper examines the relationship between systemic risk measures across 546 financial institutions in major petroleum-based economies and oil movements. In this paper, we follow two steps. In the first step, we estimate the delta conditional VaR (CoVaR) for the financial institutions and verify the interdependence between the systemic risk and oil, both on a graphical basis and by means of statistical tests. Further, we analyse the financial companies' connectedness through Granger causality-based networks, augmented with oil exposures. We observe the presence of elevated increases in the CoVaR levels, corresponding to the subprime and global crises, which are exogenous shocks to the financial institutions located in the GCC countries. In the second step, we consider the CoVaR by introducing oil returns as a state variable to detect if there is an improvement in the systemic risk measurement. The results provide evidence in favour of risk measurement improvements by accounting for oil returns in the risk functions, as monitored by coverage tests.
    Keywords: systemic risk,risk measurement,VaR,CoVaR,Oil,financial institutions,petroleum-based economies
    JEL: C22 C58 G01 G17 G20 G21 G32
    Date: 2017
  8. By: Anatoliy Swishchuk
    Abstract: In this paper, we introduce a new model for the risk process based on general compound Hawkes process (GCHP) for the arrival of claims. We call it risk model based on general compound Hawkes process (RMGCHP). The Law of Large Numbers (LLN) and the Functional Central Limit Theorem (FCLT) are proved. We also study the main properties of this new risk model, net profit condition, premium principle and ruin time (including ultimate ruin time) applying the LLN and FCLT for the RMGCHP. We show, as applications of our results, similar results for risk model based on compound Hawkes process (RMCHP) and apply them to the classical risk model based on compound Poisson process (RMCPP).
    Date: 2017–06
  9. By: Andreas M\"uhlbacher; Thomas Guhr
    Abstract: The stability of the financial system is associated with systemic risk factors such as the concurrent default of numerous small obligors. Hence it is of utmost importance to study the mutual dependence of losses for different creditors in the case of large, overlapping credit portfolios. We analytically calculate the multivariate joint loss distribution of several credit portfolios on a non-stationary market. To take fluctuating asset correlations into account we use an random matrix approach which preserves, as a much appreciated side effect, analytical tractability and drastically reduces the number of parameters. We show that for two disjoint credit portfolios diversification does not work in a correlated market. Additionally we find large concurrent portfolio losses to be rather likely. We show that significant correlations of the losses emerge not only for large portfolios with thousands of credit contracts but also for small portfolios consisting of a few credit contracts only. Furthermore we include subordination levels, which were established in collateralized debt obligations to protect the more senior tranches from high losses. We analytically corroborate the observation that an extreme loss of the subordinated creditor is likely to also yield a large loss of the senior creditor.
    Date: 2017–06
  10. By: Manabu Asai (Soka University, Japan); Chia-Lin Chang (National Chung Hsing University, Taiwan); Michael McAleer (National Tsing Hua University, Taiwan; Erasmus University Rotterdam, The Netherlands;Complutense University of Madrid, Spain; Yokohama National University, Japan)
    Abstract: The paper develops a novel realized stochastic volatility model of asset returns and realized volatility that incorporates general asymmetry and long memory (hereafter the RSV-GALM model). The contribution of the paper ties in with Robert Basmann’s seminal work in terms of the estimation of highly non-linear model specifications (“Causality tests and observationally equivalent representations of econometric models”, Journal of Econometrics, 1988), especially for specifying causal effects from returns to future volatility. This paper discusses asymptotic results of a Whittle likelihood estimator for the RSV-GALM model and a test for general asymmetry, and analyses the finite sample properties. The paper also develops an approach to obtain volatility estimates and out-of-sample forecasts. Using high frequency data for three US financial assets, the new model is estimated and evaluated. The paper compares the forecasting performance of the new model with a realized conditional volatility model.
    Keywords: Stochastic Volatility; Realized Measure; Long Memory; Asymmetry; Whittle likelihood
    JEL: C13 C22
    Date: 2017–04–10
  11. By: Fernando Garcia-Barragan; Guangling Liu
    Abstract: This paper presents a tractable framework with endogenous default and evaluates the welfare implication of bank capital requirements. We analyze the response of social welfare to a negative technology shock under different capital requirement regimes with and without default. We show that including default as an additional indicator of capital requirements is welfare improving. When implementing capital requirements, a more aggressive reaction to the default rate is more effective for weakening the negative effect of the shock on welfare. Compared with output gap, the credit-to-output gap is a better indicator for implementing the countercyclical capital buffer.
    Keywords: Bank capital requirement, Default, Welfare, DSGE
    JEL: E44 E47 E58 G28
    Date: 2017–06
  12. By: Martino, Ricci; Patrizio, Tirelli
    Abstract: Can a DSGE model replicate the financial crisis effects without assuming unprecedented and implausibly large shocks? Starting from the assumption that the subprime crisis triggered the financial crisis, we introduce balance-sheet effects for housing market borrowers and for commercial banks in an otherwise standard DSGE model. Our crisis experiment is initiated by a shock to subprime lending risk, which is calibrated to match the observed increase in subprime delinquency rates. Due to contagion of prime borrowers and to the ensuing adverse effect on banks balance sheets, this apparently small shock is sufficient to trigger a decline in housing investment comparable to what was observed during the financial crisis. The adverse effect of subprimers risk on commercial banks' agency problem is a crucial driver of our results.
    Keywords: Housing, Mortgage default, subprime risk, DSGE
    JEL: E32 E44 G01 R31
    Date: 2017–06–22
  13. By: Elie Bouri (USEK Business School, Holy Spirit University of Kaslik, Jounieh, Lebanon); Rangan Gupta (Department of Economics, University of Pretoria, Pretoria, South Africa); Chi Keung Marco Lau (Newcastle Business School, Northumbria University, Newcastle, UK); David Roubaud (Energy and Sustainable Development (ESD), Montpellier Business School, Montpellier, France); Shixuan Wang (Cardiff Business School, Cardiff University, CF10 3EU, United Kingdom)
    Abstract: We apply different techniques and uncover the quantile conditional dependence between the global financial stress index and Bitcoin returns from March 18, 2011, to October 7, 2016. The results from the copula-based dependence show evidence of right-tail dependence between the global financial stress index and Bitcoin returns. We focus on the conditional quantile dependence and indicate that the global financial stress index strongly Granger-causes Bitcoin returns at the left and middle tail of the distribution of the Bitcoin returns, conditional on the global financial stress index. Finally, we use a bivariate cross-quantilogram approach and show only limited directional predictability from the global financial stress index to Bitcoin returns in the medium term, for which Bitcoin can act as a safe haven against global financial stress.
    Keywords: Bitcoin; global financial stress index; dependence; copula; quantiles
    JEL: C22 G15
    Date: 2017–06
  14. By: Oskar Knapik (Aarhus University and CREATES)
    Abstract: For risk management traders in the electricity market are mainly interested in the risk of negative (drops) or of positive (spikes) price jumps, i.e. the sellers face the risk of negative price jumps while the buyers face the risk of positive price jumps. Understanding the mechanism that drive extreme prices and forecasting of the price jumps is crucial for risk management and market design. In this paper, we consider the problem of the impact of fundamental price drivers on forecasting of price jumps in NordPool intraday market. We develop categorical time series models which take into account i) price drivers, ii) persistence, iii) seasonality of electricity prices. The models are shown to outperform commonly-used benchmark. The paper shows how crucial for price jumps forecasting is to incorporate additional knowledge on price drivers like loads, temperature and water reservoir level as well as take into account the persistence in the jumps occurrence process.
    Keywords: autoregressive order probit model, categorical time series, seasonality, electricity prices, Nord Pool power market, forecasting, autoregressive multinomial model, fundamental price drivers
    JEL: C1 C5 C53 Q4
    Date: 2017–02–01
  15. By: Gleber, Peter
    Abstract: Cooperative Institutional Protection – a Necessary Instrument for Strengthening Customer Trust and Risk Management in Local Banking Groups: The protection scheme of the cooperative financial network goes back to the guarantee funds of the German ‹Volksbanken›, the world's oldest privately-financed protection system for banks. The core task of institutional protection is to protect the cooperative banks and hence the protection of the member's and customers' deposits, investments and savings. The local roots of the credit cooperatives rest in the 19th century. During the so-called formative phase, protection schemes were established for the newly-created cooperative lending networks of ‹Volksbanken› and rural cooperative banks, which have been a joint cooperative financial network since 1972. Since that time, the cooperative banks' combined protection scheme has developed into a unique protection system with complex tools for risk management.
    JEL: G21 N14 N24 N34 N94 P13
    Date: 2017
  16. By: Rajkamal Iyer; Marco Macchiavelli
    Abstract: This is the first of two notes that empirically document the behavior of U.S. Primary Dealers during the 2007-08 financial crisis. In this note we show that dealers' exposure to risky assets drives the observed repo funding squeeze; moreover, as evident from Lehman's experience, we show that repos become subject to counterparty risk during periods of stress, even when collateralized by the safest assets.
    Date: 2017–06–22
  17. By: Ron Berndsen; Ronald Heijmans
    Abstract: This paper identifies quantitative risks in financial market infrastructures (FMIs), which are inspired by the Principles for Financial Market Infrastructures. We convert transaction level data into indicators that provide information on operational risk, changes in the network structure and interdependencies. As a proof of concept we use TARGET2 level data. The indicators are based on legislation, guidelines and their own history. Indicators that are based on their own history are corrected for cyclical patterns. We also define a method for setting the signaling threshold of relevant changes. For the signaling, we opt for a traffic light approach: a green, yellow or red light for a small, moderate or substantial change in the indicator, respectively. The indicators developed in this paper can be used by overseers and operators of FMIs and by financial stability experts.
    Keywords: risk indicator; central bank; granular data; TARGET2; oversight; financial stability; forecasting
    JEL: E42 E50 E58 E59
    Date: 2017–06
  18. By: Lambertini Luisa; Nuguer Victoria; Uysal Pinar
    Abstract: This paper models the housing sector, mortgages and endogenous default in a DSGE setting with nominal and real rigidities. We use data for the period 1981-2006 to estimate our model using Bayesian techniques. We analyze how an increase in risk in the mortgage market raises the default rate and spreads to the rest of the economy, creating a recession. In our model two shocks are well suited to replicate the subprime crisis and the Great Recession: the mortgage risk shock and the housing demand shock. Next we use our estimated model to evaluate a policy that reduces the principal of underwater mortgages. This policy is successful in stabilizing the mortgage market and makes all agents better off.
    Keywords: Housing;Mortgage Default;DSGE model;Bayesian Estimation
    JEL: G01 E44 G21 C11
    Date: 2017–06

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