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on Risk Management |
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Issue of 2010‒06‒18
eight papers chosen by |
| By: | Magid Maatallah (DPMMS - Statistical Laboratory - University of Cambridge, Financial Mathematics Group / Heriot-Watt university - Heriot-Watt University) |
| Abstract: | We compare the performance of various hedging strategies for index CDO tranches across a variety of models and hedging methods during the recent credit crisis. Our empirical analysis shows evidence for market incompleteness: a large proportion of the risk in CDO tranches appears to be unhedgeable. We also show that, unlike what is commonly assumed, dynamic models do not necessarily perform better the static models, nor do high-dimensional bottom-up models perform better than simpler top-down models. Moreover, top-down and regression-based hedging would have provided significantly better hedges than bottom-up hedging with single name CDS during the Lehman Brothers default event. Our empirical study also reveals that while significantly large moves -” jumps” -do occur in the CDS, index and tranche spreads, these jumps do not necessarily occur on default dates of index constituents, an observation which contradicts the intuition conveyed by some recently proposed credit risk models. |
| Keywords: | portfolio credit risk models, default contagion, spread risk, sensitivity-based hedging |
| Date: | 2010–06–06 |
| URL: | http://d.repec.org/n?u=RePEc:hal:wpaper:hal-00489576_v1&r=rmg |
| By: | Franco Fiordelisi (Faculty of Economics, University of Rome III, Via S. D’Amico 77, 00182, Rome, Italy.); David Marques-Ibanez (European Central Bank, Directorate General Research, Financial Research Division, Kaiserstrasse 29, 60311 Frankfurt am Main, Germany.); Phil Molyneux (European Central Bank, Directorate General Research, Financial Research Division, Kaiserstrasse 29, 60311 Frankfurt am Main, Germany.) |
| Abstract: | We analyze the impact of efficiency on bank risk. We also consider whether bank capital has an effect on this relationship. We model the inter-temporal relationships among efficiency, capital and risk for a large sample of commercial banks operating in the European Union. We find that reductions in cost and revenue efficiencies increase banks’ future risks thus supporting the bad management and efficiency version of the moral hazard hypotheses. In contrast, bank efficiency improvements contribute to shore up bank capital levels. Our findings suggest that banks lagging behind in their efficiency levels might expect higher risk and subdued capital positions in the near future. JEL Classification: G21, D24, C23, E44. |
| Keywords: | banking risk, capital, efficiency. |
| Date: | 2010–06 |
| URL: | http://d.repec.org/n?u=RePEc:ecb:ecbwps:20101211&r=rmg |
| By: | Pablo Antolín; Stéphanie Payet; Juan Yermo |
| Abstract: | This paper assesses the relative performance of different investment strategies for different structures of the payout phase. In particular, it looks at whether the specific glide-path of life-cycle investment strategies and the introduction of dynamic features in the design of default investment strategies affect significantly retirement income outcomes. The analysis concludes that there is no ?one-size-fits-all? default investment option. Life cycle and dynamic investment strategies deliver comparable replacement rates adjusted by risk. However, life cycle strategies that maintain a constant exposure to equities during most of the accumulation period, switching swiftly to bonds in the last decade before retirement seem to produce better results and are easier to explain. Dynamic management strategies can provide somewhat higher replacement rates for a given level of risk than the more deterministic strategies, at least in the case of pay-outs in the form of variable withdrawals. The length of the contribution period also affects the ranking of the different investment strategies with life cycle strategies having a stronger positive impact the shorter is the contribution period.<P>Évaluation des stratégies d’investissement par défaut pour les plans de retraite à cotisations définies<BR>Ce document examine la performance relative de différentes stratégies d’investissement pour différentes structure de la phase de paiement. Il regarde en particulier si la forme spécifique des stratégies d’investissement à cycle de vie et l’introduction de caractéristiques dynamiques dans la conception des stratégies d’investissement par défaut jouent un rôle significatif sur les revenus de retraite résultants. Cette analyse conclue qu’il n’y a pas d’option d’investissement par défaut qui convienne pour toutes les situations. Les stratégies d’investissement à cycle de vie et les stratégies d’investissement dynamiques délivrent des taux de remplacement ajustés du risque comparables. Toutefois, les stratégies à cycle de vie qui maintiennent une exposition aux actions constante pendant la plus grande partie de la période d’accumulation, puis passent progressivement aux obligations, semblent fournir une meilleure performance en général et sont plus aisées à expliquer. Les stratégies à gestion dynamique peuvent fournir des taux de remplacement légèrement meilleurs pour un niveau de risque donné en comparaison avec les stratégies plus déterministes, au moins s’agissant du cas où les paiements se font sous la forme de retraits variables. La durée de la période de cotisation influence le classement des différentes stratégies d’investissement, les stratégies à cycle de vie ayant un impact positif plus important pour les périodes de cotisations plus courtes. |
| Keywords: | investment, regulation, replacement ratios, risk-management, retirement income, defined contribution pension plans, investissement, taux de remplacement, régulation, plans de retraite à cotisations définies, gestion des risques, revenu des retraites |
| JEL: | D14 D91 E21 G11 G38 J14 J26 |
| Date: | 2010–06 |
| URL: | http://d.repec.org/n?u=RePEc:oec:dafaad:2-en&r=rmg |
| By: | Dominique Guegan (Centre d'Economie de la Sorbonne - Paris School of Economics); Pierre-André Maugis (Centre d'Economie de la Sorbonne - Paris School of Economics) |
| Abstract: | We present a new recursive algorithm to construct vine copulas based on an underlying tree structure. This new structure is interesting to compute multivariate distributions for dependent random variables. We proove the asymptotic normality of the vine copula parameter estimator and show that all vine copula parameter estimators have comparable variance. Both results are crucial to motivate any econometrical work based on vine copulas. We provide an application of vine copulas to estimate the VaR of a portfolio, and show they offer significant improvement as compared to a benchmark estimator based on a GARCH model. |
| Keywords: | Vines copulas, conditional copulas, risk management. |
| JEL: | D81 C10 C40 C52 |
| Date: | 2010–05 |
| URL: | http://d.repec.org/n?u=RePEc:mse:cesdoc:10040&r=rmg |
| By: | Chia-Lin Chang; Biing-Wen Huang; Meng-Gu Chen; Michael McAleer (University of Canterbury) |
| Abstract: | Prices in the hog industry in Taiwan are determined according to an auction system. There are significant differences in hog prices before, during and after joining the World Trade Organization (WTO). The paper models growth rates and volatility in daily hog prices in Taiwan from 23 March 1999 to 30 June 2007, which enables an analysis of the effects of joining the WTO. The empirical results have significant implications for risk management and policy in the agricultural industry. The three sub-samples for the periods before, during and after joining the WTO display significantly different volatility persistence of symmetry, asymmetry and leverage, respectively. |
| Keywords: | Hog prices; joining the WTO; conditional volatility models; asymmetry; leverage; moment conditions |
| Date: | 2010–05–01 |
| URL: | http://d.repec.org/n?u=RePEc:cbt:econwp:10/39&r=rmg |
| By: | Wolfgang Karl Härdle; Rouslan Moro; Linda Hoffmann |
| Abstract: | In many economic applications it is desirable to make future predictions about the financial status of a company. The focus of predictions is mainly if a company will default or not. A support vector machine (SVM) is one learning method which uses historical data to establish a classification rule called a score or an SVM. Companies with scores above zero belong to one group and the rest to another group. Estimation of the probability of default (PD) values can be calculated from the scores provided by an SVM. The transformation used in this paper is a combination of weighting ranks and of smoothing the results using the PAV algorithm. The conversion is then monotone. This discussion paper is based on the Creditreform database from 1997 to 2002. The indicator variables were converted to financial ratios; it transpired out that eight of the 25 were useful for the training of the SVM. The results showed that those ratios belong to activity, profitability, liquidity and leverage. Finally, we conclude that SVMs are capable of extracting the necessary information from financial balance sheets and then to predict the future solvency or insolvent of a company. Banks in particular will benefit from these results by allowing them to be more aware of their risk when lending money. |
| Keywords: | Support Vector Machine, Bankruptcy, Default Probabilities Prediction, Profitability |
| JEL: | C14 G33 C45 |
| Date: | 2010–06 |
| URL: | http://d.repec.org/n?u=RePEc:hum:wpaper:sfb649dp2010-032&r=rmg |
| By: | Matteo Barigozzi; Christian T. Brownlees; Giampiero M. Gallo; David Veredas |
| Abstract: | When observed over a large panel, measures of risk (such as realized volatilities) usually exhibit a secular trend around which individual risks cluster. In this article we propose a vector Multiplicative Error Model achieving a decomposition of each risk measure into a common systematic and an idiosyncratic component, while allowing for contemporaneous dependence in the innovation process. As a consequence, we can assess how much of the current asset risk is due to a system wide component, andmeasure the persistence of the deviation of an asset specific risk from that common level. We develop an estimation technique, based on a combination of seminonparametric methods and copula theory, that is suitable for large dimensional panels. The model is applied to two panels of daily realized volatilities between 2001 and 2008: the SPDR Sectoral Indices of the S&P500 and the constituents of the S&P100. Similar results are obtained on the two sets in terms of reverting behavior of the common nonstationary component and the idiosyncratic dynamics to with a variable speed that appears to be sector dependent. |
| Keywords: | Systematic risk; Multiplicative Error Model; idiosyncratic risk; copula; seminonparametric |
| Date: | 2010 |
| URL: | http://d.repec.org/n?u=RePEc:eca:wpaper:2013/57645&r=rmg |
| By: | Zhiguang Wang (South Dakota State University Department of Economics); Scott W. Fausti (South Dakota State University Department of Economics); Bashir A. Qasmi (South Dakota State University Department of Economics) |
| Abstract: | We propose a fear index for corn using the variance swap rate synthesized from out-of-the-money call and put options as a measure of implied variance. Previous studies estimate implied variance based on Black (1976) model or forecast variance using the GARCH models. Our implied variance approach, based on variance swap rate, is model independent. We compute the daily 60-day variance risk premiums based on the difference between the realized variance and implied variance for the period from 1987 to 2009. We find negative and time-varying variance risk premiums in the corn market. Our results contrast with Egelkraut, Garcia, and Sherrick (2007), but are in line with the findings of Simon (2002). We conclude that our synthesized implied variance contains superior information about future realized variance relative to the implied variance estimates based on the Black (1976) model and the variance forecasted using the GARCH(1,1) model. |
| Keywords: | Variance Risk Premium, Variance Swap, Model-free Variance, Implied Variance, Realized Variance, Corn VIX |
| JEL: | Q13 Q14 G13 G14 |
| Date: | 2010–05 |
| URL: | http://d.repec.org/n?u=RePEc:sda:staffp:100001&r=rmg |