
on Risk Management 
Issue of 2014‒07‒28
twelve papers chosen by 
By:  JAAP W.B. BOS; MARTIEN LAMERS; VICTORIA PURICE () 
Abstract:  We examine the relationship between bank size and financial stability by viewing the supervisor of a banking system as an ‘investor’ holding a portfolio of banks. Based on this view, we investigate the role of large banks in determining the systemic risk in this portfolio. Our results, based on book data of U.S. banks and Bank Holding Companies, indicate that the largest banks are consistently overrepresented in the current portfolio compared with the minimum variance portfolio. Moreover, the risk level of the portfolio can be reduced by limiting concentration without sacrificing returns. 
Keywords:  Systemic risk; Modern Portfolio Theory; U.S. banking 
Date:  2014–05 
URL:  http://d.repec.org/n?u=RePEc:rug:rugwps:14/882&r=rmg 
By:  Christophe Hurlin (LEO  Laboratoire d'économie d'Orleans  CNRS : UMR6221  Université d'Orléans); Gregoire Iseli (Université de Genève  Université de Genève); Christophe Pérignon (GREGH  Groupement de Recherche et d'Etudes en Gestion à HEC  GROUPE HEC  CNRS : UMR2959); Stanley Yeung (GREGH  Groupement de Recherche et d'Etudes en Gestion à HEC  GROUPE HEC  CNRS : UMR2959) 
Abstract:  As most ExchangeTraded Funds (ETFs) engage in securities lending or are based on total return swaps, they expose their investors to counterparty risk. To mitigate the funds' exposure, their counterparties must pledge collateral. In this paper, we present a framework to study collateral risk and provide empirical estimates for the $40.9 billion collateral portfolios of 164 funds managed by a leading ETF issuer. Overall, our findings contradict the allegations made by international agencies about the high collateral risk of ETFs. Finally, we theoretically show how to construct an optimal collateral portfolio for an ETF. 
Keywords:  Asset management; passive investment ;derivatives ; systemic risk 
Date:  2014–07–05 
URL:  http://d.repec.org/n?u=RePEc:hal:wpaper:halshs01023807&r=rmg 
By:  RIADH ALOUI; MOHAMED SAFOUANE BEN AISSA; DUC KHUONG NGUYEN 
Abstract:  We consider the problem of accurate market risk modeling for agricultural commodity products over heterogeneous investment horizons using copulas and wavelet methods. Our results indicate that the degree and structure of the dependence of daily commodity returns on the three market risk factors (federal funds rate, USD/Euro exchange rate, and world stock market fluctuations) vary according to the time scale. Changes in the USD/EUR exchange rate and the stock market index are the dominant risks for agricultural commodity markets. Moreover, the tail dependence on the daily returns of the three market risk factors is also scaledependent, and frequently asymmetric. Finally, there is evidence to suggest that the application of the waveletcopula model improves the accuracy of VaR estimates, compared to traditional approaches. 
Keywords:  Agricultural commodities, Extremevalue copula, Wavelet, VaR, CVaR 
JEL:  Q14 C52 C58 G11 G17 
Date:  2014–07–15 
URL:  http://d.repec.org/n?u=RePEc:ipg:wpaper:2014412&r=rmg 
By:  Rania HentatiKAFFEL; JeanLuc Prigent 
Abstract:  This paper deals with performance measurement of financial struc tured products. For this purpose, we introduce the SharpeOmega ratio, based on put as downside risk measure. This allows to take account of the asymmetry of the return probability distribution. We provide gen eral results about the optimization of some standard structured portfolios with respect to the SharpeOmega ratio. We determine in particular the optimal combination of risk free, stock and calljput instruments with re spect to this performance measure. We show that, contrary to Sharpe ratio maximization (Goetzmann et al., 2002), the payoff of the optimal structured portfolio is not necessarily increasing and concave. We also discuss about the interest of the asset management industry to reward high Sharpe Omega ratios. 
Date:  2014–07–15 
URL:  http://d.repec.org/n?u=RePEc:ipg:wpaper:2014425&r=rmg 
By:  Ojo, Marianne 
Abstract:  The Basel III Leverage Ratio, as originally agreed upon in December 2010, has recently undergone revisions and updates – both in relation to those proposed by the Basel Committee on Banking Supervision – as well as proposals introduced in the United States. Whilst recent proposals have been introduced by the Basel Committee to improve, particularly, the denominator component of the Leverage Ratio, new requirements have been introduced in the U.S to upgrade and increase these ratios, and it is those updates which relate to the Basel III Supplementary Leverage Ratio that have primarily generated a lot of interests. This is attributed not only to concerns that many subsidiaries of US Bank Holding Companies (BHCs) will find it cumbersome to meet such requirements, but also to potential or possible increases in regulatory capital arbitrage: a phenomenon which plagued the era of the original 1988 Basel Capital Accord and which also partially provided impetus for the introduction of Basel II. This paper is aimed at providing an analysis of the most recent updates which have taken place in respect of the Basel III Leverage Ratio and the Basel III Supplementary Leverage Ratio – both in respect of recent amendments introduced by the Basel Committee and revisions introduced in the United States. Amongst these notable developments, the Final or rather nearly finalised Standard issued by the Basel Committee in January 2014, as well as the 2014 U.S Enhanced Supplementary Leverage Ratios are worth mentioning. Sometimes the competitive disadvantages resulting from over compliance or stringent measures may generate costs which are actually minimal when compared to those costs which could potential arise in a scenario where economic disruptions and crises do occur where such „over compliance“ measures are not implemented. So when do measures become overcompliant? What may be regarded as overcompliance for a particular jurisdiction may not necessarily be the case for another. Conversely what may be required for minimal compliance purposes in certain jurisdictions may prove inadequate for certain major economies. 
Keywords:  credit risk; global systemically important banks (GSIBs); leverage ratios; harmonisation; accounting rules; capital arbitrage; disclosure; stress testing techniques; U.S Basel III Final Rule 
JEL:  E3 E32 G2 G28 K2 
Date:  2014–07–21 
URL:  http://d.repec.org/n?u=RePEc:pra:mprapa:57466&r=rmg 
By:  Christoph Aymanns; J. Doyne Farmer 
Abstract:  We present a simple agentbased model of a financial system composed of leveraged investors such as banks that invest in stocks and manage their risk using a ValueatRisk constraint, based on historical observations of asset prices. The ValueatRisk constraint implies that when perceived risk is low, leverage is high and vice versa, a phenomenon that has been dubbed procyclical leverage. We show that this leads to endogenous irregular oscillations, in which gradual increases in stock prices and leverage are followed by drastic market collapses, i.e. a leverage cycle. This phenomenon is studied using simplified models that give a deeper understanding of the dynamics and the nature of the feedback loops and instabilities underlying the leverage cycle. We introduce a flexible leverage regulation policy in which it is possible to continuously tune from procyclical to countercyclical leverage. When the policy is sufficiently countercyclical and bank risk is sufficiently low the endogenous oscillation disappears and prices go to a fixed point. While there is always a leverage ceiling above which the dynamics are unstable, countercyclical leverage can be used to raise the ceiling. Finally, we investigate fixed limits on leverage and show how they can control the leverage cycle. 
Date:  2014–07 
URL:  http://d.repec.org/n?u=RePEc:arx:papers:1407.5305&r=rmg 
By:  Bell, Peter Newton 
Abstract:  This paper presents a modelling framework for analysis of financial derivatives. The framework analyzes the derivative from the perspective of a producer who has uncertain quantity of production. Quantity has a statistical relationship to an index number, or risk factor, and the producer can buy a derivative on the index number, which provides the producer with an indirect hedge against low quantity. A practical concern is how to create such an index number: one approach is to define the index as an estimated regression equation with maximal explanatory power across some set of possible equations. I use my framework to conduct a simulation experiment that shows picking an index with maximal explanatory power can lead to a financial derivative with suboptimal efficiency. In other words, I show that it is possible for one index to have lower statistical power than another but higher risk management power. This result is due to the fact that statistical power is measured over all values of quantity, whereas losses only occur for low quantity and it is sufficient (in some cases) for the index to have strong explanatory power for low values of quantity to serve as an effective risk management tool. 
Keywords:  Production, uncertainty, financial derivative, index number, statistical power, risk management 
JEL:  C43 D29 D81 G23 G32 M11 
Date:  2014–07–19 
URL:  http://d.repec.org/n?u=RePEc:pra:mprapa:57438&r=rmg 
By:  Juan Arismendi (ICMA Centre, Henley Business School, University of Reading); 
Abstract:  We derived a modelfree analytical approximation of the price of a multiasset option defined over an arbitrary multivariate process, applying a semiparametric expansion of the unknown riskneutral density with the moments. The analytical expansion termed as the Multivariate Generalised Edgeworth Expansion (MGEE) is an infinite series over the derivatives of the known continuous time density. The expected value of the density expansion is calculated to approximate the option price. The expansion could be used to enhance a Monte Carlo pricing methodology incorporating the information about moments of the riskneutral distribution. The numerical efficiency of the approximation is tested over a jump diffusion density. For the known density, we tested the multivariate lognormal (MVLN), even though arbitrary densities could be used, and we provided its derivatives until the fourthorder. The MGEE relates two densities and isolates the effects of multivariate moments over the opt ion prices. Results show that a calibrated approximation provides a good fit when the difference between the moments of the riskneutral density and the auxiliary density are small relative to the density function of the former, and the uncalibrated approximation has immediate implications over risk management and hedging theory. The possibility to select the auxiliary density provides an advantage over classical GramCharlier A, B and C series approximations. The density approximation and the methodology can be applied to other fields of finance like asset pricing, econometrics, and areas of statistical nature 
Keywords:  Multiasset option pricing, Derivatives, Risk Management 
Date:  2014–04 
URL:  http://d.repec.org/n?u=RePEc:rdg:icmadp:icmadp201403&r=rmg 
By:  Petros Dellaportas; Aleksandar Mijatovi\'c 
Abstract:  This paper gives an arbitragefree prediction for future prices of an arbitrary coterminal set of options with a given maturity, based on the observed time series of these option prices. The statistical analysis of such a multidimensional time series of option prices corresponding to $n$ strikes (with $n$ large, e.g. $n\geq 40$) and the same maturity, is a difficult task due to the fact that option prices at any moment in time satisfy nonlinear and nonexplicit noarbitrage restrictions. Hence any $n$dimensional time series model also has to satisfy these implicit restrictions at each time step, a condition that is impossible to meet since the model innovations can take arbitrary values. We solve this problem for any $n\in\NN$ in the context of Foreign Exchange (FX) by first encoding the option prices at each time step in terms of the parameters of the corresponding riskneutral measure and then performing the time series analysis in the parameter space. The option price predictions are obtained from the predicted riskneutral measure by effectively integrating it against the corresponding option payoffs. The nonlinear transformation between option prices and the riskneutral parameters applied here is \textit{not} arbitrary: it is the standard mapping used by market makers in the FX option markets (the SABR parameterisation) and is given explicitly in closed form. Our method is not restricted to the FX asset class nor does it depend on the type of parameterisation used. Statistical analysis of FX market data illustrates that our arbitragefree predictions outperform the naive random walk forecasts, suggesting a potential for building management strategies for portfolios of derivative products, akin to the ones widely used in the underlying equity and futures markets. 
Date:  2014–07 
URL:  http://d.repec.org/n?u=RePEc:arx:papers:1407.5528&r=rmg 
By:  Bertrand Candelon; Jameel Ahmed; Stefan Straetmans 
Abstract:  his paper attempts to predict the bear conditions on the US stock market. To this aim we elaborate simple predictive regressions, static and dynamic binary choice (BCM) as well as Markovswitching models. The in and outofsample prediction ability is evaluated and we compare the forecasting performance of various specifications across as well as within models. It turns out that various dynamic extensions of static versions of probit and logit models reveal additional predictive information for both in and outofsample fit. We also find that binary models outperform the Markovswitching model. With respect to the macrofinancial variables, terms spreads, inflation and money supply turn out to be useful predictors. The results lead to useful implications for investors practicing active portfolio and risk management and for policy makers as tools to get early warning signals. 
Keywords:  Bear stock market, S&P 500 Index, Macrofinancial variables, Dynamic Binary Response models, Markovswitching model, BryBoschan algorithm, Active Trading Strategies. 
JEL:  C22 C25 C53 G11 G17 
Date:  2014–07–15 
URL:  http://d.repec.org/n?u=RePEc:ipg:wpaper:2014409&r=rmg 
By:  Diep Duong (Rutgers University); Norman Swanson (Rutgers University) 
Abstract:  Many recent modelling advances in finance topics ranging from the pricing of volatilitybased derivative products to asset management are predicated on the importance of jumps, or discontinuous movements in asset returns. In light of this, a number of recent papers have addressed volatility predictability, some from the perspective of the usefulness of jumps in forecasting volatility. Key papers in this area include Andersen, Bollerslev, Diebold and Labys (2003), Corsi (2004), Andersen, Bollerslev and Diebold (2007), Corsi, Pirino and Reno (2008), Barndorff, Kinnebrock, and Shephard (2010), Patton and Shephard (2011), and the references cited therein. In this paper, we review the extant literature and then present new empirical evidence on the predictive content of realized measures of jump power variations (including upside and downside risk, jump asymmetry, and truncated jump variables), constructed using instantaneous returns, i.e., r_{t}^{q}, 0≤q≤6, in the spirit of Ding, Granger and Engle (1993) and Ding and Granger (1996). Our prediction experiments use high frequency price returns constructed using S&P500 futures data as well as stocks in the Dow 30; and our empirical implementation involves estimating linear and nonlinear heterogeneous autoregressive realized volatility (HARRV) type models. We find that past "large" jump power variations help less in the prediction of future realized volatility, than past "small" jump power variations. Additionally, we find evidence that past realized signed jump power variations, which have not previously been examined in this literature, are strongly correlated with future volatility, and that past downside jump variations matter in prediction. Finally, incorporation of downside and upside jump power variations does improve predictability, albeit to a limited extent. 
Keywords:  realized volatility, jumps, jump power variations, forecasting, jump test 
JEL:  C58 C53 C22 
Date:  2013–07–27 
URL:  http://d.repec.org/n?u=RePEc:rut:rutres:201321&r=rmg 
By:  Jiranyakul, Komain 
Abstract:  This study investigates the impact of oil price volatility (uncertainty) on the Stock Exchange of Thailand. Monthly data from May 1987 to December 2013 are applied to the twostage procedure. In the first step, a bivariate generalized autoregressive conditional heteroskedastic (GARCH) model is estimated to obtain the volatility series of stock market index and oil price. In the second step, the pairwise Granger causality tests are performed to .determine the direction of volatility transmission between oil to stock markets. It this found that movement in real oil price does not adversely affect real stock market return, but stock price volatility does affect real stock return. In addition, there exists a positive onedirectional volatility transmission running from oil to stock market. It is also found that oil price movement and its uncertainty adversely affect two main subindex returns. These important findings give some implications for risk management and policy measures. 
Keywords:  Real stock price, real oil price, volatility transmission, emerging markets 
JEL:  C22 G15 Q40 
Date:  2014–06 
URL:  http://d.repec.org/n?u=RePEc:pra:mprapa:57350&r=rmg 