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on Risk Management |
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Issue of 2015‒08‒19
fourteen papers chosen by |
| By: | Raupach, Peter |
| Abstract: | Regulatory capital for trading book positions includes two components that cover different risks but apply to the same portfolio, one for market risk and one for credit risk. Similar approaches are common in banks' internal models for economic capital. Although it is known that joint market and credit risk of certain investments can be larger than the sum of risks, the problematic cases identified so far have been relatively exotic. I show that very common investments - corporate bond holdings or CDS portfolios - are also affected. There are realistic conditions under which credit risk (represented by ratings and default) and spread risk (represented by rating specific spread indices) combine to a total value-at-risk (VaR) 50 percent larger than the sum of spread and credit VaR; this effect is even stronger for the expected shortfall. If migration risk is segregated from default risk and incorporated into spread risk, as recently put forward by the Basel Committee, total risk is no longer underestimated. Furthermore, I improve a theoretic result of Breuer et al. (2010) that defines a sufficient condition under which risk separation is harmless. |
| Keywords: | Economic capital,Bank capital requirements,Risk measures,Risk aggregation,Trading book |
| JEL: | G32 G21 C15 |
| Date: | 2015 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:bubdps:192015&r=rmg |
| By: | Paul Larsen |
| Abstract: | Operational risk models commonly employ maximum likelihood estimation (MLE) to fit loss data to heavy-tailed distributions. Yet several desirable properties of MLE (e.g. asymptotic normality) are generally valid only for large sample-sizes, a situation rarely encountered in operational risk. We study MLE in operational risk models for small sample-sizes across a range of loss severity distributions. We apply these results to assess (1) the approximation of parameter confidence intervals by asymptotic normality, and (2) value-at-risk (VaR) stability as a function of sample-size. Finally, we discuss implications for operational risk modeling. |
| Date: | 2015–08 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1508.02824&r=rmg |
| By: | Maarten van Oordt; Chen Zhou |
| Abstract: | Rules and regulations may have different impacts on risk-taking by individual banks and on banks' systemic risk levels. That is why implementing prudential rules and policies requires careful consideration of their impact on bank risk and systemic risk. This chapter assesses whether market-based measures of systemic risk and recent regulatory indicators provide similar rankings on the systemically importance of large European banks. We find evidence that regulatory indicators of systemic importance are positively related to systemic risk. In particular, banks with higher scores on regulatory indicators have a stronger link to the system in the event of financial stress, rather than having a higher level of bank risk. |
| Keywords: | G-SIBs; financial stability; macroprudential regulation; systemic importance |
| JEL: | G01 G21 G28 |
| Date: | 2015–07 |
| URL: | http://d.repec.org/n?u=RePEc:dnb:dnbwpp:478&r=rmg |
| By: | Anisa Caja (SAF - Laboratoire de Sciences Actuarielle et Financière - UCBL - Université Claude Bernard Lyon 1); Quentin Guibert (SAF - Laboratoire de Sciences Actuarielle et Financière - UCBL - Université Claude Bernard Lyon 1); Frédéric Planchet (SAF - Laboratoire de Sciences Actuarielle et Financière - UCBL - Université Claude Bernard Lyon 1) |
| Abstract: | This paper presents a model for the determination and forecast of the number of defaults and credit changes by estimating a reduced-form ordered regression model with a large data set from a credit insurance portfolio. Similarly to banks with their classical credit risk management techniques, credit insurers measure the credit quality of buyers with rating transition matrices depending on the economical environment. Our approach consists in modeling stochastic transition matrices for homogeneous groups of firms depending on macroeconomic risk factors. One of the main features of this business is the close monitoring of covered firms and the insurer’s ability to cancel or reduce guarantees when the risk changes. As our primary goal is a risk management analysis, we try to account for this leeway and study how this helps mitigate risks in case of shocks. This specification is particularly useful as an input for the Own Risk Solvency Assessment (ORSA) since it illustrates the kind of management actions that can be implemented by an insurer when the credit environment is stressed. |
| Date: | 2015–07–20 |
| URL: | http://d.repec.org/n?u=RePEc:hal:wpaper:hal-01178812&r=rmg |
| By: | Javier G. Gómez-Pineda; Dominique Guillaume; Kadir Tanyeri |
| Abstract: | The paper presents a global model for analysis and projections. The model features a handful of elements that make it suitable for analyzing three broad sets of topics; first, systemic risk and its transmission to country risk premiums; second, the transmission from country risk premiums to demand-related variables such as the output gap, the trade balance, and unemployment; and third, the transmission from commodity prices to country inflation. The model incorporates one systemic risk channel and two foreign channels, specifically, a foreign aggregate demand channel and a foreign exchange rate channel. The model is estimated with Bayesian methods. In addition, the effect of risk on aggregate demand is calibrated with the aid of a VAR. Among the results are that the episodes of surges in systemic risk identified in the paper were transmitted to country risk premiums and aggregate demand--related variables; that the effect of systemic risk shocks on world economic activity is large, and that the busts in the world output gap correspond with the major financial events identified by the estimated time series for the unobserved systemic risk. In addition, systemic risk shocks are important drivers of output gaps while country risk premium shocks can have important effects on the trade balance. Surprisingly, commodity prices, in particular the price of oil, are shown to be demand driven; hence, demand related factors may play a nontrivial role in explaining noncore inflation. The model performed well at one- and four-quarter horizons compared to a survey of analysts' forecasts. In addition, systemic risk shocks were important at explaining the forecast variance of the world output gap, country output gaps, the price of oil, and country risk premiums. The breath of reach of systemic risk shocks back the efforts for financial surveillance with a systemic focus. |
| Keywords: | Systemic risk, Financial linkages, Capital flows, Global imbalances Commodity prices |
| JEL: | F32 F37 F41 F31 F47 E58 |
| Date: | 2015–07–23 |
| URL: | http://d.repec.org/n?u=RePEc:col:000094:013327&r=rmg |
| By: | Hatfield, Jerry |
| Keywords: | Agricultural and Food Policy, Risk and Uncertainty, |
| Date: | 2015–02–19 |
| URL: | http://d.repec.org/n?u=RePEc:ags:usao15:204998&r=rmg |
| By: | Jean-Charles Croix (SAF - Laboratoire de Sciences Actuarielle et Financière - UCBL - Université Claude Bernard Lyon 1); Frédéric Planchet (SAF - Laboratoire de Sciences Actuarielle et Financière - UCBL - Université Claude Bernard Lyon 1); Pierre-Emmanuel Thérond (SAF - Laboratoire de Sciences Actuarielle et Financière - UCBL - Université Claude Bernard Lyon 1) |
| Abstract: | The Solvency 2 advent and the best-estimate methodology in future cash-flows valuation lead insurers to focus particularly on their assumptions. In mortality, hypothesis are critical as insurers use best-estimate laws instead of standard mortality tables. Backtesting methods, i.e. ex-post modelling validation processes , are encouraged by regulators and rise an increasing interest among practitioners and academics. In this paper, we propose a statistical approach (both parametric and non-parametric models compliant) for mortality laws backtesting under model risk. Afterwards, a specification risk is introduced assuming that the mortality law is subject to random variations. Finally, the suitability of the proposed method will be assessed within this framework. |
| Date: | 2015 |
| URL: | http://d.repec.org/n?u=RePEc:hal:journl:hal-01149396&r=rmg |
| By: | Natalya Martynova; Enrico Perotti |
| Abstract: | We study how contingent capital that converts in equity ahead of default affects bank risk-shifting. Going concern conversion restores equity value in highly levered states, thus reducing heightened risk incentives. In contrast, conversion at default for traditional bail-inable debt has no effect on endogenous risk. The main beneficial effect comes from reduced leverage at conversion. In contrast to traditional convertible debt, equity dilution under going concern conversion has the opposite effect. The negative effect of dilution is tempered by any value transfer at conversion. We find that CoCo capital may be less risky than bail-inable debt when lower priority is compensated by lower endogenous risk, which is beneficial as a lower bond yield improves incentives. The risk reduction effect of CoCo debt depends critically on the informativeness of the trigger, but is always inferior to pure equity. |
| Keywords: | Banks; Contingent Capital; Risk-shifting; Financial Leverage |
| JEL: | G13 G21 G28 |
| Date: | 2015–08 |
| URL: | http://d.repec.org/n?u=RePEc:dnb:dnbwpp:480&r=rmg |
| By: | Alexis Louaas (Department of Economics, Ecole Polytechnique - CNRS - Polytechnique - X); Pierre Picard (Department of Economics, Ecole Polytechnique - CNRS - Polytechnique - X) |
| Abstract: | We analyze the optimal insurance coverage for high severity-low probability accidents, both from theoretical and applied standpoints. Such accidents qualify as catastrophic when their risk premium is a non-negligible proportion of the victims’ wealth, although the probability of occurrence is very small. We show that this may be the case when the individual’s absolute risk aversion is very large in the accident case. We characterize the optimal insurance contract firstly for an individual, and secondly for a firm that may be at the origin of an accident that affects the whole population. The optimal indemnity schedule converges to a limit when the probability of the accident tends to zero. In the case of corporate civil liability, this limit schedule is a straight deductible contract that corresponds to an indemnification of victims ranked in order of priority according to the severity of their losses. We also show that the size of the deductible depends on the individuals’ risk aversion and also on the cost of contingent risk capital that is required to sustain the indemnity payment, should an accident occur. The empirical part of the paper is an application of these general principles to the case of nuclear accidents. Large scale nuclear accidents are typical examples of high severity-low probability risks. We calibrate a model on French data in order to estimate the optimal liability ceiling of an electricity producer in the nuclear energy sector. We use data drawn from the cat-bond markets to estimate the cost of contingent capital for low probability events, and we show that the minimal corporate liability adopted in 2004 through the revision of the Paris Convention is probably lower than the level that would correspond to an optimal risk coverage of the population. |
| Date: | 2014–12–22 |
| URL: | http://d.repec.org/n?u=RePEc:hal:wpaper:hal-01097897&r=rmg |
| By: | Hacène Djellout (Laboratoire de Mathématiques - UBP - Université Blaise Pascal - Clermont-Ferrand 2 - CNRS); Arnaud Guillin (Institut Universitaire de France-IUF - Institut Universitaire de France-IUF, Laboratoire de Mathématiques - UBP - Université Blaise Pascal - Clermont-Ferrand 2 - CNRS); Yacouba Samoura (Laboratoire de Mathématiques - UBP - Université Blaise Pascal - Clermont-Ferrand 2 - CNRS) |
| Abstract: | Realized statistics based on high frequency returns have become very popular in financial economics. In recent years, different non-parametric estimators of the variation of a log-price process have appeared. These were developed by many authors and were motivated by the existence of complete records of price data. Among them are the realized quadratic (co-)variation which is perhaps the most well known example, providing a consistent estimator of the integrated (co-)volatility when the logarithmic price process is continuous. Limit results such as the weak law of large numbers or the central limit theorem have been proved in different contexts. In this paper, we propose to study the large deviation properties of realized (co-)volatility (i.e., when the number of high frequency observations in a fixed time interval increases to infinity. More specifically, we consider a bivariate model with synchronous observation schemes and correlated Brownian motions of the following form: $dX_{\ell,t} = \sigma_{\ell,t}dB_{\ell,t}+b_{\ell}(t,\omega)dt$ for $\ell=1,2$, where $X_{\ell}$ denotes the log-price, we are concerned with the large deviation estimation of the vector $V_t^n(X)=\left(Q_{1,t}^n(X), Q_{2,t}^n(X), C_{t}^n(X)\right)$ where $Q_{\ell,t}^n(X)$ and $C_{t}^n(X)$ represente the estimator of the quadratic variational processes $Q_{\ell,t}=\int_0^t\sigma_{\ell,s}^2ds$ and the integrated covariance $C_t=\int_0^t\sigma_{1,s}\sigma_{2,s}\rho_sds$ respectively, with $\rho_t=cov(B_{1,t}, B_{2,t})$. Our main motivation is to improve upon the existing limit theorems. Our large deviations results can be used to evaluate and approximate tail probabilities of realized (co-)volatility. As an application we provide the large deviation for the standard dependence measures between the two assets returns such as the realized regression coefficients up to time $t$, or the realized correlation. Our study should contribute to the recent trend of research on the (co-)variance estimation problems, which are quite often discussed in high-frequency financial data analysis. |
| Date: | 2014–11–14 |
| URL: | http://d.repec.org/n?u=RePEc:hal:wpaper:hal-01082903&r=rmg |
| By: | Josselin Garnier; George Papanicolaou; Tzu-Wei Yang |
| Abstract: | We formulate and analyze a multi-agent model for the evolution of individual and systemic risk in which the local agents interact with each other through a central agent who, in turn, is influenced by the mean field of the local agents. The central agent is stabilized by a bistable potential, the only stabilizing force in the system. The local agents derive their stability only from the central agent. In the mean field limit of a large number of local agents we show that the systemic risk decreases when the strength of the interaction of the local agents with the central agent increases. This means that the probability of transition from one of the two stable quasi-equilibria to the other one decreases. We also show that the systemic risk increases when the strength of the interaction of the central agent with the mean field of the local agents increases. Following the financial interpretation of such models and their behavior given in our previous paper (Garnier, Papanicolaou and Yang, SIAM J. Fin. Math. 4, 2013, 151-184), we may interpret the results of this paper in the following way. From the point of view of systemic risk, and while keeping the perceived risk of the local agents approximately constant, it is better to strengthen the interaction of the local agents with the central agent than the other way around. |
| Date: | 2015–07 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1507.08333&r=rmg |
| By: | Guillaume Carlier (Institute for Fiscal Studies); Victor Chernozhukov (Institute for Fiscal Studies and MIT); Alfred Galichon (Institute for Fiscal Studies and Science Po, Paris) |
| Abstract: | We propose a notion of conditional vector quantile function and a vector quantile regression. A conditional vector quantile function (CVQF) of a random vector Y, taking values in Rd given covariates Z=z, taking values in Rk, is a map u --> QY|Z(u,z), which is monotone, in the sense of being a gradient of a convex function, and such that given that vector U follows a reference non-atomic distribution FU, for instance uniform distribution on a unit cube in Rd, the random vector QY|Z(u,z) has the distribution of Y conditional on Z=z. Moreover, we have a strong representation, Y =QY|Z(U,Z) almost surely, for some version of U. The vector quantile regression (VQR) is a linear model for CVQF of Y given Z. Under correct specification, the notion produces strong representation, Y=ß(U)Tf(Z),for f(Z) denoting a known set of transformations of Z, where u --> ß(u)T f(Z) is a monotone map, the gradient of a convex function, and the quantile regression coefficients u --> ß(u) have the interpretations analogous to that of the standard scalar quantile regression. As f(Z) becomes a richer class of transformations of Z, the model becomes nonparametric, as in series modelling. A key property of VQR is the embedding of the classical Monge-Kantorovich's optimal transportation problem at its core as a special case. In the classical case, where Y is scalar, VQR reduces to a version of the classical QR, and CVQF reduces to the scalar conditional quantile function. Several applications to diverse problems such as multiple Engel curve estimation, and measurement of financial risk, are considered. |
| Date: | 2014–12 |
| URL: | http://d.repec.org/n?u=RePEc:ifs:cemmap:48/14&r=rmg |
| By: | Amélie Charles (Audencia Recherche - Audencia); Olivier Darné (LEMNA - Laboratoire d'économie et de management de Nantes Atlantique - UN - Université de Nantes) |
| Abstract: | We determine the events that cause large shocks in volatility of the DJIA index over the period 1928–2013, using a new semi-parametric test based on conditional heteroscedasticity models. We find that these large shocks can be associated with particular events (financial crashes, elections, wars, monetary policies, etc.). We show that some shocks are not identified as extraordinary movements by the investors due to their occurring during high volatility episodes, especially the 1929–1934, 1937–1938 and 2007–2011 periods. |
| Date: | 2014 |
| URL: | http://d.repec.org/n?u=RePEc:hal:journl:hal-01122507&r=rmg |
| By: | Svetlana Andrianova (University of Leicester); Badi Baltagi (Syracuse University); Thorsten Beck (Cass Business School); Panicos Demetriades (University of Leicester); David Fielding (University of Otago); Stephen G. Hall; Steven F. Koch (Department of Economics, University of Pretoria); Robert Lensink (University of Groningen); Johan Rewilak (University of Huddersfield); Peter Rousseau (Vanderbilt University) |
| Abstract: | We present a new database on financial fragility for 124 countries over 1998 to 2012. In addition to commercial banks, our database incorporates investment banks and real estate and mortgage banks, which are thought to have played a central role in the recent financial crisis. Furthermore, it also includes cooperative banks, savings banks and Islamic banks, that are often thought to have different risk appetites than do commercial banks. As a result, the total value of financial assets in our database is around 50% higher than that accounted for by commercial banks alone. We provide eight different measures of financial fragility, each focussing on a different aspect of vulnerability in the financial system. Alternative selection rules for our variables distinguish between institutions with different levels of reporting frequency. |
| Keywords: | Health Production, Contraception Efficiency, Nonparametric Analysis |
| Date: | 2015–08 |
| URL: | http://d.repec.org/n?u=RePEc:pre:wpaper:201557&r=rmg |