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on Risk Management |
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Issue of 2012‒08‒23
23 papers chosen by |
| By: | Dominique Guegan (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Paris I - Panthéon Sorbonne, EEP-PSE - Ecole d'Économie de Paris - Paris School of Economics - Ecole d'Économie de Paris); Wayne Tarrant (Wingate University - Department of Mathematics) |
| 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; Basel II accord |
| Date: | 2012–07–27 |
| URL: | http://d.repec.org/n?u=RePEc:hal:cesptp:halshs-00721350&r=rmg |
| By: | Dominique Guegan (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Paris I - Panthéon Sorbonne, EEP-PSE - Ecole d'Économie de Paris - Paris School of Economics - Ecole d'Économie de Paris); Wayne Tarrant (Wingate University - Department of Mathematics) |
| Abstract: | The banking systems that deal with risk management depend on underlying risk measures. Following the recommendation of the Basel II accord, most banks have developed internal models to determine their capital requirement. The Value at Risk measure plays an important role in computing this capital. In this paper we analyze in detail the errors produced by use of this measure. We then discuss other measures, pointing out their strengths and shortcomings. We give detailed examples, showing the need for five risk measures in order to compute a capital in relation to the risk to which the bank is exposed. In the end, we suggest using five different risk measures for computing capital requirements. |
| Keywords: | Risk measure; Value at Risk; Bank capital; Basel II Accord |
| Date: | 2012–07–27 |
| URL: | http://d.repec.org/n?u=RePEc:hal:cesptp:halshs-00721339&r=rmg |
| By: | Dominique Guegan (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Paris I - Panthéon Sorbonne, EEP-PSE - Ecole d'Économie de Paris - Paris School of Economics - Ecole d'Économie de Paris); Bertrand Hassani (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Paris I - Panthéon Sorbonne, BPCE - BPCE) |
| 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 as follows. 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. This paper proposes several solutions and attracts the regulators and managers attention on two crucial points : the granularity and the risk measures. |
| Keywords: | Operational risks; Loss Distribution Function; risk measures; EVT; Vine copula |
| Date: | 2012–07–31 |
| URL: | http://d.repec.org/n?u=RePEc:hal:cesptp:halshs-00722029&r=rmg |
| By: | Germán López-Espinosa (School of Economics and Business Administration, University of Navarra); Antonio Moreno (School of Economics and Business Administration, University of Navarra); Antonio Rubia (Department of Financial Economics, University of Alicante); Laura Valderrama (International Monetary Fund (IMF)) |
| Abstract: | We use the CoVaR approach to identify the main factors behind systemic risk in a set of large international banks. We find that short-term wholesale funding is a key determinant in triggering systemic risk episodes. In contrast, we find weaker evidence that either size or leverage contributes to systemic risk within the class of large international banks. We also show that asymmetries based on the sign of bank returns play an important role in capturing the sensitivity of system-wide risk to individual bank returns. Since short-term wholesale funding emerges as the most relevant systemic factor, our results support the Basel Committee’s proposal to introduce a net stable funding ratio, penalizing excessive exposure to liquidity risk. |
| Keywords: | Systemic importance; liquidity risk; macroprudential regulation |
| JEL: | C30 G01 G20 |
| Date: | 2012–07–31 |
| URL: | http://d.repec.org/n?u=RePEc:una:unccee:wp0212&r=rmg |
| By: | D. Yıldırım, Burcu; Coskun, Yener; Caglar, Ozan; Yıldırak, Kasırga |
| Abstract: | Recent developments in Turkish derivatives markets demonstrate the increasing importance of risk management not only for individual banks but also for the entire system. In this context, this study analyzes the counterparty credit risk of OTC derivatives. The analysis is based on a hypothetical portfolio that is characterized by key aspects of the instruments banks hold. Thus, the portfolio consists of vanilla swaps, which dominate banks’ transactions. By simulating market risk factors, we come up with proxy risk exposure figures for the whole banking system. After a proper adjustment, these figures have been compared with the risk weighted assets, which includes credit risk,as well as with the capital. Consequently, we observe that the counterparty credit risk resulting from the use of OTC derivatives is relatively small for the Turkish banking system. Nevertheless, in light of the new regulatory framework introduced by Basel III, the importance of credit and market liquidity risk for the OTC instruments in trading portfolios is expected to increase in the near future. |
| Keywords: | Counterparty credit risk; OTC derivatives; swaps; Basel II; valuation |
| JEL: | C15 E44 G32 G21 |
| Date: | 2012–08–08 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:40600&r=rmg |
| By: | Veysov, Alexander |
| Abstract: | This draft working paper is to summarize theoretical contributions in the field of measuring systemic risk and contagion of financial systems. Broad theoretical framework is analyzed and empiric approach to a macroeconomic model of global banking system systemic risk and contagion is offered. The model is to use BIS locational statistics as well as national consolidated balance sheets of banking systems to provide some insight into the vulnerability of modern banking system. As to theoretical contributions, three branches of literature are analyzed: correlation-based measures, network-based measures and various systemic risk measures. |
| Keywords: | financial contagion; systemic risk; banking system; modeling |
| JEL: | E21 |
| Date: | 2012–06–14 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:40612&r=rmg |
| By: | Blakespoor, Elizabeth (Stanford University); Linsmeier, Thomas J. (Financial Accounting Standards Board); Petroni, Kathy (MI State University); Shakespeare, Catherine (University of MI) |
| Abstract: | Many have argued that financial statements created under an accounting model that measures financial instruments at fair value would not fairly represent a bank's business model. In this study we examine whether financial statements using fair values for financial instruments better describe banks' credit risk than less fair-value-based financial statements. Specifically, we assess the extent to which leverage ratios that are derived using financial instruments measured along a fair value continuum are associated with various measures of credit risk. Our leverage ratios include financial instruments measured at 1) fair value; 2) US GAAP mixed-attribute values; and 3) Tier 1 bank capital values. The credit risk measures we consider are bond yield spreads and future bank failure. We find that leverage measured using the fair values of financial instruments explains significantly more variation in bond yield spreads and bank failure than the other less fair-value-based leverage ratios in both univariate and multivariate analyses. We also find that the fair value of loans and secondarily deposits appear to be the primary sources of incremental explanatory power. |
| Date: | 2012–06 |
| URL: | http://d.repec.org/n?u=RePEc:ecl:stabus:2107&r=rmg |
| By: | Laura Valderrama; Germán López-Espinosa; Antonio Moreno; Antonio Rubia |
| Abstract: | To date, an operational measure of systemic risk capturing non-linear tail comovement between system-wide and individual bank returns has not yet been developed. This paper proposes an extension of the so-called CoVaR measure that captures the asymmetric response of the banking system to positive and negative shocks to the market-valued balance sheets of individual banks. For the median of our sample of U.S. banks, the relative impact on the system of a fall in individual market value is sevenfold that of an increase. Moreover, the downward bias in systemic risk from ignoring this asymmetric pattern increases with bank size. The conditional tail comovement between the banking system and a top decile bank which is losing market value is 5.4 larger than the unconditional tail comovement versus only 2.2 for banks in the bottom decile. The asymmetric model also produces much better estimates and fitting, and thus improves the capacity to monitor systemic risk. Our results suggest that ignoring asymmetries in tail interdependence may lead to a severe underestimation of systemic risk in a downward market. |
| Keywords: | Banking systems , Commercial banks , Economic models , Financial risk , Risk management , |
| Date: | 2012–06–12 |
| URL: | http://d.repec.org/n?u=RePEc:imf:imfwpa:12/152&r=rmg |
| By: | Yener, Coskun |
| Abstract: | Financial failures observed during global financial crisis have again underlined the importance of effective risk management. In this article, the author analyzes the best instrument, namely self discipline, official discipline and market discipline, for the effective risk management. In the light of literature review and lessons of firm/system wide financial failures, we also analyze degree of efficieny of disciplinary methods. We first conclude, however it may not provide optimal solutions to the risk management problems of financial intermediaries, better risk management standards should be developed. We also conclude that firm wide risk management processes may be managed by pragmatic regulatory policies without get into negative impacts of market mechanism and big financial firms’ pressures. |
| Keywords: | Financial failure; risk management; regulation; self regulation |
| JEL: | G32 G01 G21 |
| Date: | 2012–08–08 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:40594&r=rmg |
| By: | Andre Lucas (VU University Amsterdam, and Duisenberg school of finance); Bastiaan Verhoef (Royal Bank of Scotland) |
| Abstract: | We investigate the effect of model specification on the aggregation of (correlated) market and credit risk. We focus on the functional form linking systematic credit risk drivers to default probabilities. Examples include the normal based probit link function for typical structural models, or the exponential (Poisson) link function for typical reduced form models. We first show analytically how model specification impacts 'diversification benefits' for aggregated market and credit risk. The specification effect can lead to Value-at-Risk (VaR) reductions in the range of 3 percent to 47 percent, particularly at high confidence level VaRs. We also illustrate the effects using a fully calibrated empirical model for US data. The empirical effects corroborate our analytic results. |
| Keywords: | risk aggregation; credit risk; market risk; link function; diversification; reduced form models; structural models |
| JEL: | G32 G21 C58 |
| Date: | 2012–05–31 |
| URL: | http://d.repec.org/n?u=RePEc:dgr:uvatin:20120057&r=rmg |
| By: | Nassim N. Taleb; Raphael Douady |
| Abstract: | We provide a mathematical definition of fragility and antifragility as negative or positive sensitivity to a semi-measure of dispersion and volatility (a variant of negative or positive "vega") and examine the link to nonlinear effects. We integrate model error (and biases) into the fragile or antifragile context. Unlike risk, which is linked to psychological notions such as subjective preferences (hence cannot apply to a coffee cup) we offer a measure that is universal and concerns any object that has a probability distribution (whether such distribution is known or, critically, unknown). We propose a detection of fragility, robustness, and antifragility using a single "fast-and-frugal", model-free, probability free heuristic that also picks up exposure to model error. The heuristic lends itself to immediate implementation, and uncovers hidden risks related to company size, forecasting problems, and bank tail exposures (it explains the forecasting biases). While simple to implement, it outperforms stress testing and other such methods such as Value-at-Risk. |
| Date: | 2012–08 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1208.1189&r=rmg |
| By: | Kasper Lund-Jensen |
| Abstract: | Successful implementation of macroprudential policy is contingent on the ability to identify and estimate systemic risk in real time. In this paper, systemic risk is defined as the conditional probability of a systemic banking crisis and this conditional probability is modeled in a fixed effect binary response model framework. The model structure is dynamic and is designed for monitoring as the systemic risk forecasts only depend on data that are available in real time. Several risk factors are identified and it is hereby shown that the level of systemic risk contains a predictable component which varies through time. Furthermore, it is shown how the systemic risk forecasts map into crisis signals and how policy thresholds are derived in this framework. Finally, in an out-of-sample exercise, it is shown that the systemic risk estimates provided reliable early warning signals ahead of the recent financial crisis for several economies. |
| Keywords: | Banking crisis , Banking sector , Economic models , Financial risk , |
| Date: | 2012–06–18 |
| URL: | http://d.repec.org/n?u=RePEc:imf:imfwpa:12/159&r=rmg |
| By: | Piu Banerjee; José J. Canals-Cerdá |
| Abstract: | We develop an empirical framework for the credit risk analysis of a generic portfolio of revolving credit accounts and apply it to analyze a representative panel data set of credit card accounts from a credit bureau. These data cover the period of the most recent deep recession and provide the opportunity to analyze the performance of such a portfolio under significant economic stress conditions. We consider a traditional framework for the analysis of credit risk where the probability of default (PD), loss given default (LGD), and exposure at default (EAD) are explicitly considered. The unsecure and revolving nature of credit card lending is naturally modeled in this framework. Our results indicate that unemployment, and in particular the level and change in unemployment, plays a significant role in the probability of transition across delinquency states in general and the probability of default in particular. The effect is heterogeneous and proportionally has a more significant impact for high credit score and for high-utilization accounts. Our results also indicate that unemployment and a downturn in economic conditions play a quantitatively small, or even irrelevant, role in the changes in account balance associated with changes in an account’s delinquency status, and in the exposure at default specifically. The impact of a downturn in economic conditions and, in particular, changes in unemployment on the recovery rate and loss given default is found to be large. These findings are of particular relevance for the analysis of credit risk regulatory capital under the IRB |
| Keywords: | Credit ; Unemployment |
| Date: | 2012 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fedpwp:12-18&r=rmg |
| By: | Antonio Trujillo-Ponce (Department of Financial Economics and Accounting, Pablo de Olavide University, Seville, Spain); Reyes Samaniego-Medina (Department of Financial Economics and Accounting, Pablo de Olavide University, Seville, Spain); Clara Cardone-Riportella (Department of Business Administration, Universidad Carlos III de Madrid) |
| Abstract: | Using a sample of 2,186 credit default swap (CDS) spreads quoted in the European market during the period 2002-2009, this paper empirically analyzes which model – accounting- or market-based – better explains corporate credit risk. We find that there is little difference in the explanatory power of the two approaches. Our results suggest that both accounting and market data complement one other and thus that a comprehensive model that includes both types of variables appears to be the best option for explaining credit risk. We also show that the explanatory power of accounting- and market-based variables for measuring credit risk is particularly strong during periods of high uncertainty, as experienced in the recent financial crisis, and that it decreases as the CDS contract matures. Finally, the comprehensive model continues to show the best results when using the credit rating as the proxy for credit risk, but accounting variables currently appear to have a more important role than the market variables |
| Keywords: | Bankruptcy; credit default swaps; credit risk; distance-to-default |
| Date: | 2012–05 |
| URL: | http://d.repec.org/n?u=RePEc:pab:fiecac:12.03&r=rmg |
| By: | Marco Bardoscia |
| Abstract: | Operational risk is the risk relative to monetary losses caused by failures of bank internal processes due to heterogeneous causes. A dynamical model including both spontaneous generation of losses and generation via interactions between different processes is presented; the efforts made by the bank to avoid the occurrence of losses is also taken into account. Under certain hypotheses, the model can be exactly solved and, in principle, the solution can be exploited to estimate most of the model parameters from real data. The forecasting power of the model is also investigated and proved to be surprisingly remarkable. |
| Date: | 2012–07 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1207.6186&r=rmg |
| By: | Lorenzo Ricci (ECARES); David Veredas (ECARES) |
| Abstract: | We introduce TailCoR, a new measure for tail correlation that is a function of linear and non-linear correlations, the latter characterized by the tail index. TailCoR can be exploited in a number of financial applications, such as portfolio selection where the investor faces risks of a linear and tail nature. Moreover, it has the following advantages: i) it is exact for any probability level as it is not based on tail asymptotic arguments (contrary to tail dependence coefficients), ii) it can be used in all tail scenarios (fatter, equal to or thinner than those of the Gaussian distribution), iii), it is distribution free, and iv) it is simple and no optimizations are needed. Monte Carlo simulations and calibrations reveal its goodness in finite samples. An empirical illustration using a panel of Euro area sovereign bonds shows that prior to 2009 linear correlations were in the vicinity of one and non-linear correlations were inexistent. Since the beginning of the crisis the linear correlations have decreased sharply, and non-linear correlations appeared and increased significantly in 2010-2011 |
| Keywords: | Tail correlation, quantile, ellipticity, risk |
| JEL: | C32 C51 G01 |
| Date: | 2012–07 |
| URL: | http://d.repec.org/n?u=RePEc:bde:wpaper:1227&r=rmg |
| By: | Zhen Shi (University of Melbourne, and Netspar); Bas J.M. Werker (CentER, Tilburg University, Duisenberg School of Finance, and Netspar) |
| Abstract: | Regulators often set value-at-risk (VaR) constraints to limit the portfolio risk of institutional investors. For some investors, notably pension funds, the VaR constraint is enforced over a horizon which is significantly shorter than the investment horizon of the investor. Our paper aims to investigate the economic costs and benefits of this kind of regulation. Shorter regulatory constraint, on one hand, enables an institutional investor, like a pension fund, to avoid large losses when the investment environment worsens but, on the other hand, also limits the institutional |
| Keywords: | Portfolio Choice; Value-at-Risk; Pension Funds |
| JEL: | G11 G23 |
| Date: | 2011–03–17 |
| URL: | http://d.repec.org/n?u=RePEc:dgr:uvatin:20110053&r=rmg |
| By: | Luiz A. Pereira da Silva; Adriana Soares Sales; Wagner Piazza Gaglianone |
| Abstract: | This paper proposes a working definition for “financial stability” related to systemic risk. Systemic risk is then measured as the probability of disruption of financial services taking into account its time and cross-sectional dimensions and several risk factors. The paper discusses the implications of this definition for Brazil in the aftermath of the recent global financial crisis. A comparison with the United States and the Euro zone is provided. In addition, systemic risk in the Brazilian credit market is investigated given its crucial role as main financial stability driver. Finally, synthetic indicators of systemic risk are used to monitor financial stability. The link between systemic risk and synthetic indicators and/or well-correlated proxies (e.g., a credit-to-GDP gap) allows the calculation of the probability of disruption of the financial system across its time dimension. Therefore, if a Financial Stability Committee and/or the prudential regulator define its tolerance level for “financial stability” as a threshold measured by this probability of disruption, it might have the capability of determining the precise moment when it should strengthen its set of adequate macroprudential responses and policies. |
| Date: | 2012–08 |
| URL: | http://d.repec.org/n?u=RePEc:bcb:wpaper:289&r=rmg |
| By: | Lönnbark, Carl (Department of Economics, Umeå University) |
| Abstract: | In the estimation of risk measures such as Value at Risk and Expected shortfall relatively short estimation windows are typically used rendering the estimation error a possibly non-negligible component. In this paper we build upon previous results for the Value at Risk and discuss how the estimation error comes into play for the Expected Shortfall. We identify two important aspects where it may be of importance. On the one hand there is in the evaluation of predictors of the measure. On the other there is in the interpretation and communication of it. We illustrate magnitudes numerically and emphasize the practical importance of the latter aspect in an empirical application with stock market index data. |
| Keywords: | Backtesting; Delta method; Finance; GARCH; Risk Management |
| JEL: | C52 C53 C58 G10 G19 |
| Date: | 2012–08–16 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:umnees:0844&r=rmg |
| By: | Alessandro Ramponi |
| Abstract: | In this paper we consider the problem of calculating the quantiles of a risky position, the dynamic of which is described as a continuous time regime-switching jump-diffusion, by using Fourier Transform methods. Furthermore, we study a classical option-based portfolio strategy which minimizes the Value-at-Risk of the hedged position and show the impact of jumps and switching regimes on the optimal strategy in a numerical example. However, the analysis of this hedging strategy, as well as the computational technique for its implementation, is fairly general, i.e. it can be applied to any dynamical model for which Fourier transform methods are viable. |
| Date: | 2012–07 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1207.6759&r=rmg |
| By: | Tim J. Brereton; Dirk P. Kroese; Joshua C. Chan |
| Abstract: | The financial crisis of 2007 – 2009 began with a major failure in credit markets. The causes of this failure stretch far beyond inadequate mathematical modeling (see Donnelly and Embrechts [2010] and Brigo et al. [2009] for detailed discussions from a mathematical finance perspective). Nevertheless, it is clear that some of the more popular models of credit risk were shown to be flawed. Many of these models were and are popular because they are mathematically tractable, allowing easy computation of various risk measures. More realistic (and complex) models come at a significant computational cost, often requiring Monte Carlo methods to estimate quantities of interest. |
| Date: | 2012–07 |
| URL: | http://d.repec.org/n?u=RePEc:acb:cbeeco:2012-579&r=rmg |
| By: | Tianxiao Wang |
| Abstract: | In this paper, we investigate risk minimization problem of derivatives based on non-tradable underlyings by means of dynamic g-expectations which are slight different from conditional g-expectations. In this framework, inspired by [1] and [16], we introduce risk indifference price, marginal risk price and derivative hedge and obtain their corresponding explicit expressions. The interesting thing is that their expressions have nothing to do with nonlinear generator g, and one deep reason for this is due to the completeness of financial market. By giving three useful special risk minimization problems, we obtain the explicit optimal strategies with initial wealth involved, demonstrate some qualitative analysis among optimal strategies, risk aversion parameter and market price of risk, together with some economic interpretations. |
| Date: | 2012–08 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1208.2068&r=rmg |
| By: | Goodwin, Barry K. |
| Abstract: | Three specific aspects of agricultural risk management are addressed 1. Recent developments in price volatility and yield risk 2. The role of policy: - Subsidized crop insurance with examples from the massive US program ($115 billion in liability in 2011) - The 2012 US Farm Bill, which is currently being debated in Congress (with disturbing developments) 3. review of recent research on developments in the empirical modeling of risk with a focus on revenue insurance (combining aspects of dependent yield and price risks) |
| Keywords: | Agricultural and Food Policy, Risk and Uncertainty, |
| Date: | 2012–06 |
| URL: | http://d.repec.org/n?u=RePEc:ags:eaa126:128207&r=rmg |