nep-rmg New Economics Papers
on Risk Management
Issue of 2011‒11‒14
seventeen papers chosen by
Stan Miles
Thompson Rivers University

  1. Viewing risk measures as information. By Dominique Guegan; Wayne Tarrant
  2. Counterparty Risk FAQ: Credit VaR, PFE, CVA, DVA, Closeout, Netting, Collateral, Re-hypothecation, WWR, Basel, Funding, CCDS and Margin Lending By Damiano Brigo
  3. A mathematical resurgence of risk management : an extreme modeling of expert opinions. By Dominique Guegan; Bertrand K. Hassani
  4. A multivariate extension of Value-at-Risk and Conditional-Tail-Expectation By Areski Cousin; Elena Di Bernadino
  5. The Rise and Fall of S&P500 Variance Futures By Chia-Lin Chang; Juan-Ángel Jiménez-Martín; Michael McAleer; Teodosio Pérez-Amaral
  6. Operational risk : a Basel II++ step before Basel III. By Dominique Guegan; Bertrand K. Hassani
  7. Stochastic dominance with respect to a capacity and risk measures By Miryana Grigorova
  8. Bank risk during the financial crisis: do business models matter? By Yener Altunbas; Simone Manganelli; David Marques-Ibanez
  9. A Transparency Standard for Derivatives By Viral V. Acharya
  11. How useful is the Marginal Expected Shortfall for the measurement of systemic exposure? A practical assessment By Idier, J.; Lamé, G.; Mésonnier, J S.
  12. Estimation error reduction in portfolio optimization with Conditional Value-at-Risk By Noureddine El Karoui; Andrew E. B. Lim; Gah-Yi Vahn
  13. Three-Benchmarked Risk Minimization for Jump Diffusion Markets By Ke Du; Eckhard Platen
  14. Spending flexibility and safe withdrawal rates By Finke, Michael; Pfau, Wade Donald; Williams, Duncan
  15. SAFE: An early warning system for systemic banking risk By Mikhail V. Oet; Ryan Eiben; Timothy Bianco; Dieter Gramlich; Stephen J. Ong; Jing Wang
  16. Credit scoring and loan default By Geetesh Bhardwaj; Rajdeep Sengupta
  17. Temperature, Aggregate Risk, and Expected Returns By Ravi Bansal; Marcelo Ochoa

  1. By: Dominique Guegan (Centre d'Economie de la Sorbonne); Wayne Tarrant (Department of Mathematics - Wingate University)
    Abstract: Regulation and Risk management in banks depend on underlying risk measures. In general this is the only purpose that is seen for risk measures. In this paper, we suggest that the reporting of risk measures can be used to determine the loss distribution function for a financial entity. We demonstrate that a lack of sufficient information can lead to ambiguous risk situations. We give examples, showing the need for the reporting of multiple risk measures in order to determine a bank's loss distribution. We conclude by suggesting a regulatory requirement of multiple risk measures being reported by banks, giving specific recommendations.
    Keywords: Risk measure, Value at Risk, Bank capital.
    JEL: C16 G18 E52
    Date: 2011–08
  2. By: Damiano Brigo
    Abstract: We present a dialogue on Counterparty Credit Risk touching on Credit Value at Risk (Credit VaR), Potential Future Exposure (PFE), Expected Exposure (EE), Expected Positive Exposure (EPE), Credit Valuation Adjustment (CVA), Debit Valuation Adjustment (DVA), DVA Hedging, Closeout conventions, Netting clauses, Collateral modeling, Gap Risk, Re-hypothecation, Wrong Way Risk, Basel III, inclusion of Funding costs, First to Default risk, Contingent Credit Default Swaps (CCDS) and CVA restructuring possibilities through margin lending. The dialogue is in the form of a Q&A between a CVA expert and a newly hired colleague.
    Date: 2011–11
  3. By: Dominique Guegan (Centre d'Economie de la Sorbonne); Bertrand K. Hassani (BPCE et Centre d'Economie de la Sorbonne)
    Abstract: The Operational Risk Advanced Measurement Approach requires financial institutions to use scenarios to model these risks and to evaluate the pertaining capital charges. Considering that a banking group is composed of numerous entities (branches and subsidiaries), and that each one of them is represented by an Operational Risk Manager (ORM), we propose a novel scenario approach based on ORM expertise to collect information and create new data sets focusing on large losses, and the use of the Extreme Value Theory (EVT) to evaluate the corresponding capital allocation. In this paper, we highlight the importance to consider an a priori knowledge of the experts associated to a a posteriori backtesting based on collected incidents.
    Keywords: Basel II, operational risks, EVT, AMA, expert, Value-at-Risk, excepted shortfall.
    Date: 2011–09
  4. By: Areski Cousin (SAF - Laboratoire de Sciences Actuarielle et Financière - Université Claude Bernard - Lyon I : EA2429); Elena Di Bernadino (SAF - Laboratoire de Sciences Actuarielle et Financière - Université Claude Bernard - Lyon I : EA2429)
    Abstract: In this paper, we introduce a multivariate extension of the classical univariate Value-at-Risk (VaR). This extension may be useful to understand how solvency capital requirement computed for a given financial institution may be affected by the presence of additional risks. We also generalize the bivariate Conditional-Tail-Expectation (CTE), previously introduced by Di Bernardino et al. (2011), in a multivariate setting and we study its behavior. Several properties have been derived. In particular, we show that these two risk measures both satisfy the positive homogeneity and the translation invariance property. Comparison between univariate risk measures and components of multivariate VaR and CTE are provided. We also analyze how they are impacted by a change in marginal distributions, by a change in dependence structure and by a change in risk level. Interestingly, these results turn to be consistent with existing properties on univariate risk measures. Illustrations are given in the class of Archimedean copulas.
    Keywords: Multivariate Risk Measures; Level Sets; Kendall distribution, Copula
    Date: 2011–11–04
  5. By: Chia-Lin Chang (Department of Applied Economics Department of Finance National Chung Hsing University Taichung, Taiwan); Juan-Ángel Jiménez-Martín (Department of Quantitative Economics Complutense University of Madrid); Michael McAleer (Erasmus University Rotterdam, Tinbergen Institute, The Netherlands, Complutense University of Madrid, and Institute of Economic Research, Kyoto University); Teodosio Pérez-Amaral (Department of Quantitative Economics Complutense University of Madrid)
    Abstract: Modelling, monitoring and forecasting volatility are indispensible to sensible portfolio risk management. The volatility of an asset of composite index can be traded by using volatility derivatives, such as volatility and variance swaps, options and futures. The most popular volatility index is VIX, which is a key measure of market expectations of volatility, and hence also an important barometer of investor sentiment and market volatility. Investors interpret the VIX cash index as a “fear” index, and of VIX options and VIX futures as derivatives of the “fear” index. VIX is based on S&P500 call and put options over a wide range of strike prices, and hence is not model based. Speculators can trade on volatility risk with VIX derivatives, with views on whether volatility will increase or decrease in the future, while hedgers can use volatility derivatives to avoid exposure to volatility risk. VIX and its options and futures derivatives has been widely analysed in recent years. An alternative volatility derivative to VIX is the S&P500 variance futures, which is an expectation of the variance of the S&P500 cash index. Variance futures are futures contracts written on realized variance, or standardized variance swaps. The S&P500 variance futures are not model based, so the assumptions underlying the index do not seem to have been clearly understood. As variance futures are typically thinly traded, their returns and volatility are not easy to model accurately using a variety of model specifications. This paper analyses the volatility in S&P500 3-month variance futures before, during and after the GFC, as well as for the full data period, for each of three alternative conditional volatility models and three densities, in order to determine whether exposure to risk can be incorporated into a financial portfolio without taking positions on the S&P500 index itself.
    Keywords: Risk management, financial derivatives, futures, options, swaps, 3-month variance futures, 12-month variance futures, risk exposure, volatility.
    JEL: C22 G32
    Date: 2011–11
  6. By: Dominique Guegan (Centre d'Economie de la Sorbonne); Bertrand K. Hassani (BPCE et Centre d'Economie de la Sorbonne)
    Abstract: Following Banking Committee on Banking Supervision, operational risk quantification is based on the Basel matrix which enables sorting incidents. In this paper, we deeply analyze these incidents and propose strategies for carrying out the supervisory guidelines proposed by the regulators. The objectives are numerous. On the first hand, banks need to provide a univariate capital charge for each cell of the Basel matrix. On the other hand, banks need also to provide a global capital charge corresponding to the whole matrix taking into account dependences. We provide a solution to do so. Finally, we draw regulators and managers attention on two crucial points : the granularity and the risk measure.
    Keywords: Basel II, operational risks, EVT, Copula.
    Date: 2011–09
  7. By: Miryana Grigorova (LPMA - Laboratoire de Probabilités et Modèles Aléatoires - CNRS : UMR7599 - Université Pierre et Marie Curie - Paris VI - Université Paris Diderot - Paris 7)
    Abstract: Pursuing our previous work in which the classical notion of increasing convex stochastic dominance relation with respect to a probability has been extended to the case of a normalised monotone (but not necessarily additive) set function also called a capacity, the present paper gives a generalization to the case of a capacity of the classical notion of increasing stochastic dominance relation. This relation is characterized by using the notions of distribution function and quantile function with respect to the given capacity. Characterizations, involving Choquet integrals with respect to a distorted capacity, are established for the classes of monetary risk measures (defined on the space of bounded real-valued measurable functions) satisfying the properties of comonotonic additivity and consistency with respect to a given generalized stochastic dominance relation. Moreover, under suitable assumptions, a "Kusuoka-type" characterization is proved for the class of monetary risk measures having the properties of comonotonic additivity and consistency with respect to the generalized increasing convex stochastic dominance relation. Generalizations to the case of a capacity of some well-known risk measures (such as the Value at Risk or the Tail Value at Risk) are provided as examples. It is also established that some well-known results about Choquet integrals with respect to a distorted probability do not necessarily hold true in the more general case of a distorted capacity.
    Keywords: Choquet integral ; stochastic orderings with respect to a capacity ; distortion risk measure ; quantile function with respect to a capacity ; distorted capacity ; Choquet expected utility ; ambiguity ; non-additive probability ; Value at Risk ; Rank-dependent expected utility ; behavioural finance ; maximal correlation risk measure ; quantile-based risk measure ; Kusuoka's characterization theorem
    Date: 2011–11–09
  8. By: Yener Altunbas (Centre for Banking and Finance, University of Wales, Bangor, Gwynedd, LL57 2DG, UK.); Simone Manganelli (European Central Bank, Kaiserstrasse 29, D-60311 Frankfurt, Germany.); David Marques-Ibanez (European Central Bank, Kaiserstrasse 29, D-60311 Frankfurt, Germany.)
    Abstract: We exploit the 2007-2009 financial crisis to analyze how risk relates to bank business models. Institutions with higher risk exposure had less capital, larger size, greater reliance on short-term market funding, and aggressive credit growth. Business models related to significantly reduced bank risk were characterized by a strong deposit base and greater income diversification. The effect of business models is non-linear: it has a different impact on riskier banks. Finally, it is difficult to establish in real time whether greater stock market capitalization involves real value creation or the accumulation of latent risk. JEL Classification: G21, G15, E58, G32.
    Keywords: Bank risk, business models, bank regulation, financial crisis, Basle III.
    Date: 2011–11
  9. By: Viral V. Acharya
    Abstract: Derivatives exposures across large financial institutions often contribute to – if not necessarily create – systemic risk. Current reporting standards for derivatives exposures are nevertheless inadequate for assessing these systemic risk contributions. In this paper, I explain how a transparency standard, in contrast to the current standard, would facilitate such risk analysis. I also demonstrate that such a standard is implementable by providing examples of existing disclosures from large dealer firms in their quarterly filings. These disclosures often contain useful firm-level data on derivatives, but due to a lack of standardization, they cannot be aggregated to assess the risk to the system. I highlight the important contribution that reporting the “margin coverage ratio” (MCR), namely the ratio of a derivatives dealer’s cash (or liquidity, more broadly) to its contingent collateral or margin calls in case of a significant downgrade of its credit quality, could make toward assessing systemic risk contributions.
    JEL: G13 G18 G28
    Date: 2011–11
  10. By: Luis García-Álvarez (CEMFI, Centro de Estudios Monetarios y Financieros); Richard Luger (J. Mack Robinson College of Business)
    Abstract: We evaluate alternative multivariate models of dynamic correlations in terms of realized out-of-sample Sharpe ratios for an active portfolio manager who rebalances a portfolio of international equities on a daily basis. The evaluation period covers the recent financial crisis which was marked by increased volatility and correlations across international stock markets. Our results show that international correlations fluctuate considerably from day to day, but we find no evidence of decoupling between emerging and developed stock markets. We also find that the recursively updated dynamic correlation models display remarkably stable parameter estimates over time, but that none yields statistically better portfolio performances than the naive diversification benchmark strategy. The results clearly show the erosive effects of model estimation risk and transactions costs, the benefits of limiting short sales, and the far greater importance of including a risk-free security in the asset mix whether or not market turbulence is high.
    Keywords: Portfolio selection, DC model, international diversification, decoupling hypothesis, estimation risk short-sale constraints.
    JEL: C53 G11 G15
    Date: 2011–04
  11. By: Idier, J.; Lamé, G.; Mésonnier, J S.
    Abstract: We explore the practical relevance from a supervisor's viewpoint of a recent but already popular market-based indicator of the systemic importance of financial institutions, the marginal expected shortfall (MES). The MES of an institution can be defined as its expected equity loss when the market itself is in its left tail. We compute the dynamic MES developed by Brownlees and Engle (2010) for a panel of 65 large US banks over the last decade and a half. Running panel regressions of the MES on bank characteristics, we first find that the MES can be partly rationalized in terms of standard balance sheet indicators of bank health and systemic importance, but also that these relationships changed widely over time. We then ask whether the cross section of the MES can help to identify ex ante, i.e. before a crisis unfolds, which institutions are the more likely to suffer the most severe losses ex post, i.e. once it has unfolded. Unfortunately, using the recent crisis as a natural experiment, we find that standard balance-sheet metrics like the tier one solvency ratio are better able to predict equity losses conditional to a true crisis.
    Keywords: MES, systemic risk, tail correlation, balance sheet ratios, panel.
    JEL: C5 E44 G2
    Date: 2011
  12. By: Noureddine El Karoui; Andrew E. B. Lim; Gah-Yi Vahn
    Abstract: We investigate two methods for reducing estimation error in portfolio optimization with Conditional Value-at-Risk (CVaR). The first method is nonparametric: penalize portfolios with large variances in mean and CVaR estimations. The penalized problem is solvable by a quadratically-constrained quadratic program, and can be interpreted as a chance-constrained program. We show the original and penalized solutions follow the Central Limit Theorem with computable covariance by extending M-estimation results from statistics. The second method is parametric: solve the empirical Markowitz problem instead if the log-return distribution is in the elliptical family (which includes Gaussian and $t$ distributions), as then the population frontiers of the Markowitz and mean-CVaR problems are equivalent. Numerical simulations show both methods improve upon the empirical mean-CVaR solution under an elliptical model, with the Markowitz solution dominating. The penalized solution dominates under a non-elliptical model with heavy one-sided loss.
    Date: 2011–11
  13. By: Ke Du (School of Finance and Economics, University of Technology, Sydney); Eckhard Platen (School of Finance and Economics, University of Technology, Sydney)
    Abstract: The paper discusses the problem of hedging not perfectly replicable contingent claims by using a benchmark, the numerraire portfolio, as reference unit. The proposed concept of benchmarked risk minimization generalizes classical risk minimization, pioneered by Follmer, Sondermann and Schweizer. The latter relies on a quadratic criterion, requesting the square integrability of contingent claims and the existence of an equivalent risk neutral probability measure. The proposed concept of benchmarked risk minimization avoids these restrictive assumptions. It employs the real world probability measure as pricing measure and identifies the minimal possible price for the hedgable part of a contingent claim. Furthermore, the resulting benchmarked profit and loss is only driven by nontraded uncertainty and forms a martingale that starts at zero. Benchmarked profit and losses, when pooled and sufficiently independent, become in total negligible. This property is highly desirable from a risk management point of view. It is making a symptotically benchmarked risk minimization the least expensive method for pricing and hedging for an increasing number of not fully replicable benchmarked contingent claims.
    Keywords: incomplete market; pricing; hedging; numeraire portfolio; risk minimization; benchmark approach
    JEL: G10 G13
    Date: 2011–08–01
  14. By: Finke, Michael; Pfau, Wade Donald; Williams, Duncan
    Abstract: Shortfall risk retirement income analyses offer little insight into how much risk is optimal, and how risk tolerance affects retirement income decisions. This study models retirement income risk in a manner consistent with risk tolerance in portfolio selection in order to estimate optimal asset allocations and withdrawal rates for retirees with different risk attitudes. We find that the 4 percent retirement withdrawal rate strategy may only be appropriate for risk averse clients with moderate guaranteed income sources. The ability to accept greater shortfall probabilities means that risk tolerant investors will prefer a higher withdrawal rate and a riskier retirement portfolio. A risk tolerant client may prefer a withdrawal rate of between 5 and 7 percent with a guaranteed income of $20,000. The optimal retirement portfolio allocation to stock increases by between 10 and 30 percentage points and the optimal withdrawal rate increases by between 1 and 2 percentage points for clients with a guaranteed income of $60,000 instead of $20,000.
    Keywords: retirement planning; utility maximization; retirement spending goals; safe withdrawal rates
    JEL: G11 C15 D14
    Date: 2011–11–05
  15. By: Mikhail V. Oet; Ryan Eiben; Timothy Bianco; Dieter Gramlich; Stephen J. Ong; Jing Wang
    Abstract: This paper builds on existing microprudential and macroprudential early warning systems (EWSs) to develop a new, hybrid class of models for systemic risk, incorporating the structural characteristics of the fi nancial system and a feedback amplification mechanism. The models explain fi nancial stress using both public and proprietary supervisory data from systemically important institutions, regressing institutional imbalances using an optimal lag method. The Systemic Assessment of Financial Environment (SAFE) EWS monitors microprudential information from the largest bank holding companies to anticipate the buildup of macroeconomic stresses in the financial markets. To mitigate inherent uncertainty, SAFE develops a set of medium-term forecasting specifi cations that gives policymakers enough time to take ex-ante policy action and a set of short-term forecasting specifications for verification and adjustment of supervisory actions. This paper highlights the application of these models to stress testing, scenario analysis, and policy.
    Keywords: Systemic risk ; Liquidity (Economics)
    Date: 2011
  16. By: Geetesh Bhardwaj; Rajdeep Sengupta
    Abstract: This paper introduces a measure of credit score performance that abstracts from the influence of “situational factors.” Using this measure, we study the role and effectiveness of credit scoring that underlied subprime securities during the mortgage boom of 2000-2006. Parametric and nonparametric measures of credit score performance reveal different trends, especially on originations with low credit scores. The paper demonstrates an increasing trend of reliance on credit scoring not only as a measure of credit risk but also as a means to offset other riskier attributes of the origination. This reliance led to deterioration in loan performance even though average credit quality—as measured in terms of credit scores— actually improved over the years.
    Keywords: Credit scoring systems ; Mortgage loans
    Date: 2011
  17. By: Ravi Bansal; Marcelo Ochoa
    Abstract: In this paper we show that temperature is an aggregate risk factor that adversely affects economic growth. Our argument is based on evidence from global capital markets which shows that the covariance between country equity returns and temperature (i.e., temperature betas) contains sharp information about the cross-country risk premium; countries closer to the Equator carry a positive temperature risk premium which decreases as one moves farther away from the Equator. The differences in temperature betas mirror exposures to aggregate growth rate risk, which we show is negatively impacted by temperature shocks. That is, portfolios with larger exposure to risk from aggregate growth also have larger temperature betas; hence, a larger risk premium. We further show that increases in global temperature have a negative impact on economic growth in countries closer to the Equator, while its impact is negligible in countries at high latitudes. Consistent with this evidence, we show that there is a parallel between a country's distance to the Equator and the economy's dependence on climate sensitive sectors; in countries closer to the Equator industries with a high exposure to temperature are more prevalent. We provide a Long-Run Risks based model that quantitatively accounts for cross-sectional differences in temperature betas, its link to expected returns, and the connection between aggregate growth and temperature risks.
    JEL: E0 G12 Q0
    Date: 2011–11

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