
on Risk Management 
By:  Pankoke, David 
Abstract:  This paper evaluates whether sophisticated or simple systemic risk measures are more suitable in identifying which institutions contribute to systemic risk. In this investigation, DCoVaR, Marginal Expected Shortfall (MES), SRISK and GrangerCausality Networks are considered as sophisticated systemic risk measures. Market capitalization, total debt, leverage, the stock market returns of an institution, and the correlation between the stock market returns of an institution and the market, are considered as simple systemic risk measures. Systemic relevance is approximated by the receipt of financial support during the financial crisis and the classification, as a systemically important institution, by national or international regulators. The analyses are performed for all companies included in the S&P 500 composite index. The findings suggest that simple systemic risk measures have more explanatory power than sophisticated risk measures. In particular, total debt is found to be the most suitable indicator to detect institutions which contribute to systemic risk, according to the explanatory power and model fit. The most suitable sophisticated risk measure seems to be SRISK. 
Keywords:  Systemic Risk, DCoVaR, Marginal Expected Shortfall, SRISK, GrangerCausality Networks 
Date:  2014–12 
URL:  http://d.repec.org/n?u=RePEc:usg:sfwpfi:2014:22&r=rmg 
By:  Tomasz Skoczylas (Faculty of Economic Sciences, University of Warsaw) 
Abstract:  In this paper an alternative approach to modelling and forecasting single asset returns volatility is presented. A new, bivariate, flexible framework, which may be considered as a development of singleequation ARCHtype models, is proposed. This approach focuses on joint distribution of returns and observed volatility, measured by GarmanKlass variance estimator, and it enables to examine simultaneous dependencies between them. Proposed models are compared with benchmark GARCH and rangebased GARCH (RGARCH) models in terms of prediction accuracy. All models are estimated with maximum likelihood method, using time series of EUR/PLN spot rate quotations and WIG20 index. Results are very encouraging especially for foreasting ValueatRisk. Bivariate models achieved lesser rates of VaR exception, as well as lower coverage tests statistics, without being more conservative than its singleequation counterparts, as their forecasts errors measures are rather similar. 
Keywords:  bivariate volatility models, joint distribution, rangebased volatility estimators, GarmanKlass estimator, observed volatility, volatility modelling, GARCH, leverage, ValueatRisk, volatility forecasting 
JEL:  C13 C32 C53 C58 G10 G17 
Date:  2015 
URL:  http://d.repec.org/n?u=RePEc:war:wpaper:201503&r=rmg 
By:  Hugonnier, Julien; Morellec, Erwan 
Abstract:  We develop a dynamic model to assess the effects of liquidity and leverage requirements on banks' insolvency risk. The model features endogenous capital structure, liquid asset holdings, payout, and default decisions. In the model, banks face taxation, flotation costs of securities, and default costs. They are financed with equity, insured deposits, and risky debt. Using the model, we show that liquidity requirements have no longrun effects on default risk but may increase it in the shortrun; leverage requirements reduce default risk but may significantly reduce bank value; mispriced deposit insurance fuels default risk while depositor preference in default decreases it. 
Keywords:  banks; capital structure; insolvency risk; liquidity buffers; regulation 
JEL:  G21 G28 G32 G33 
Date:  2015–02 
URL:  http://d.repec.org/n?u=RePEc:cpr:ceprdp:10378&r=rmg 
By:  Gropp, Reint 
Abstract:  Before the 200709 crisis, standard risk measurement methods substantially underestimated the threat to the financial system. One reason was that these methods didn't account for how closely commercial banks, investment banks, hedge funds, and insurance companies were linked. As financial conditions worsened in one type of institution, the effects spread to others. A new method that more accurately accounts for these spillover effects suggests that hedge funds may have been central in generating systemic risk during the crisis. 
Keywords:  systemic risk analysis,statistical risk measurement,spillover effects 
Date:  2014 
URL:  http://d.repec.org/n?u=RePEc:zbw:safepl:23&r=rmg 
By:  Brandtner, Mario; Kürsten, Wolfgang 
Abstract:  We analyze spectral risk measures with respect to comparative risk aversion following Arrow (1965) and Pratt (1964) on the one hand, and Ross (1981) on the other hand. The implications for two standard financial decision problems, namely the willingness to pay for insurance and portfolio selection, are studied. Within the framework of Arrow and Pratt, we show that the widelyapplied spectral ArrowPrattmeasure is not a consistent measure of ArrowPrattrisk aversion. A decision maker with a greater spectral ArrowPrattmeasure may only be willing to pay less for insurance or to invest more in the risky asset than a decision maker with a smaller spectral ArrowPrattmeasure. We further show how a proper measure of ArrowPrattrisk aversion should look like instead. Within the framework of Ross, we show that the popular subclasses of Conditional ValueatRisk, and exponential and power spectral risk measures cannot be completely ordered with respect to Rossrisk aversion. As a consequence, these subclasses also exhibit counterintuitive comparative static results. In the insurance problem, the willingness to pay for insurance may be decreasing with increasing risk parameter. In the portfolio selection problem, the investment in the risky asset may be increasing with increasing risk parameter. These shortcomings have to be considered before spectral risk measures can be applied for the purpose of optimal decision making and regulatory issues. 
JEL:  D81 G11 G21 
Date:  2014 
URL:  http://d.repec.org/n?u=RePEc:zbw:vfsc14:100615&r=rmg 
By:  García Muñoz, Luis Manuel; de Lope Contreras, Fernando; Palomar Burdeus, Juan Esteban 
Abstract:  As a byproduct of the 20072008 credit crunch, derivatives pricing and risk management are experiencing a dramatic transformation. Assumptions that were widely accepted not long ago, like absence of counterparty credit risk and the existence of a unique risk free curve available for every derivatives hedger in the derivatives replication process, are no longer accepted. Financial institutions are changing the way in which counterparty credit risk and funding risk are managed. We find ourselves in a world with multiple discounting curves for any given currency and with different adjustments to apply to the price of financial derivatives that seem difficult to hedge. The target of this book is to make a deep review of how these effects impact the derivatives valuation theory. 
Keywords:  Derivatives pricing, Collateral, OIS Discounting, CVA, DVA, FVA, Counterparty Credit Risk, Funding Risk 
JEL:  G10 G12 G13 
Date:  2015–02–01 
URL:  http://d.repec.org/n?u=RePEc:pra:mprapa:62086&r=rmg 
By:  Hott, Christian 
Abstract:  We develop a theoretical model of mortgage loss rates that evaluates their main underlying risk factors. Following the model, loss rates are positively influenced by the house price level, the loantovalue of mortgages, interest rates, and the unemployment rate. They are negatively influenced by the growth of house prices and the income level. The calibration of the model for the US and Switzerland demonstrates that it is able to describe the overall development of actual mortgage loss rates. In addition, we show potential applications of the model for different macroprudential instruments: stress tests, countercyclical buffer, and setting risk weights for mortgages with different loantovalue and loantoincome ratios. 
JEL:  E51 G21 G28 
Date:  2014 
URL:  http://d.repec.org/n?u=RePEc:zbw:vfsc14:100553&r=rmg 
By:  Eisl, Alexander; Elendner, Hermann W.; Lingo, Manuel 
Abstract:  Rating agencies report ordinal ratings in discrete classes. We question the marketâ€™s implicit assumption that agencies define their classes on identical scales, e.g., that AAA by Standard & Poorâ€™s is equivalent to Aaa by Moodyâ€™s. To this end, we develop a nonparametric method to estimate the relation between rating scales for pairs of raters. For every rating class of one rater this, scale relation identifies the extent to which it corresponds to any rating class of another rater, and hence enables a ratingclass specific remapping of one agencyâ€™s ratings to anotherâ€™s. Our method is based purely on ordinal coratings to obviate errorprone estimation of default probabilities and the disputable assumptions involved in treating ratings as metric data. It estimates all rating classesâ€™ relations from a pair of raters jointly, and thus exploits the information content from ordinality. We find evidence against the presumption of identical scales for the three major rating agencies Fitch, Moodyâ€™s and Standard & Poorâ€™s, provide the relations of their rating classes and illustrate the importance of correcting for scale relations in benchmarking. 
Keywords:  credit rating; rating agencies; rating scales; comparison of ratings 
JEL:  C14 G24 
Date:  2015 
URL:  http://d.repec.org/n?u=RePEc:trf:wpaper:492&r=rmg 
By:  Markus Bibinger; Moritz Jirak; Mathias Vetter; 
Abstract:  This work develops changepoint methods for statistics of highfrequency data. The main interest is the volatility of an Itˆo semimartingale, which is discretely observed over a fixed time horizon. We construct a minimaxoptimal test to discriminate different smoothness classes of the underlying stochastic volatility process. In a highfrequency framework we prove weak convergence of the test statistic under the hypothesis to an extreme value distribution. As a key example, under extremely mild smoothness assumptions on the stochastic volatility we thereby derive a consistent test for volatility jumps. A simulation study demonstrates the practical value in finitesample applications. 
Keywords:  highfrequency data, nonparametric changepoint test, minimaxoptimal test, stochastic volatility, volatility jumps 
JEL:  C12 C14 
Date:  2015–02 
URL:  http://d.repec.org/n?u=RePEc:hum:wpaper:sfb649dp2015008&r=rmg 
By:  Décamps, JeanPaul; Gryglewicz, S.; Morellec, E.; Villeneuve, Stéphane 
Abstract:  We develop a dynamic model of investment, cash holdings, financing, and risk management policies in which firms face financing frictions and are subject to permanent and temporary cash ow shocks. In this model, target cash holdings depend on the longterm prospects of the firm, implying that the payout policy of the firm, its financing policy, and its cashow sensitivity of cash display a more realistic behavior than in prior models with financing frictions. In addition, risk management policies are richer and depend on the nature of cash ow shocks and potential collateral constraints. Lastly, the timing of investment and the firms initial asset mix both reect financing frictions and the joint effects of permanent and temporary shocks. 
Keywords:  Corporate policies; permanent vs. temporary shocks; financing frictions. 
Date:  2015–01 
URL:  http://d.repec.org/n?u=RePEc:ide:wpaper:28978&r=rmg 