
on Risk Management 
Issue of 2014‒12‒03
eighteen papers chosen by 
By:  Dominique Guegan (CES  Centre d'économie de la Sorbonne  CNRS : UMR8174  Université Paris I  PanthéonSorbonne); Bertrand Hassani (CES  Centre d'économie de la Sorbonne  CNRS : UMR8174  Université Paris I  PanthéonSorbonne) 
Abstract:  The particular subject of this paper, is to construct a general framework that can consider and analyse in the same time upside and downside risks. This paper offers a comparative analysis of concept risk measures, we focus on quantile based risk measure (ES and VaR), spectral risk measure and distortion risk measure. After introducing each measure, we investigate their interest and limit. Knowing that quantile based risk measure cannot capture correctly the risk aversion of risk manager and spectral risk measure can be inconsistent to risk aversion, we propose and develop a new distortion risk measure extending the work of Wang (2000) [38] and Sereda et al (2010) [34]. Finally, we provide a comprehensive analysis of the feasibility of this approach using the S&P500 data set from o1/01/1999 to 31/12/2011. 
Keywords:  Risk; VaR; distorsion measures 
Date:  2014–02 
URL:  http://d.repec.org/n?u=RePEc:hal:journl:halshs00969242&r=rmg 
By:  Matros, Philipp; Vilsmeier, Johannes 
Abstract:  We derive multivariate riskneutral asset distributions for major US financial institutions (FIs) using option implied marginal riskneutral asset distributions (RNDs) and probabilities of default (PoDs). The multivariate densities are estimated by combining the entropy approach, dynamic copulas and rank correlations. Our density estimates yield information about the conditional distributions of the individual FIs, and we propose several financial distress measures based on default scenarios in the financial sector. Empirical results around the period of the US subprime crisis show that the proposed risk measures identify in a timely manner: i) the most distressed FIs in the system; ii) the systemically most important FIs; iii) the implicit bailout guarantees given to some FIs; and iv) a "too connected to fail" problem in the US financial sector throughout the year 2008. 
Keywords:  Financial Distress,Conditional Probability of Default,Copulas,Option Prices,Entropy Principle 
JEL:  C14 C32 G01 G21 
Date:  2014 
URL:  http://d.repec.org/n?u=RePEc:zbw:bubdps:202014&r=rmg 
By:  Dominique Guegan (CES  Centre d'économie de la Sorbonne  CNRS : UMR8174  Université Paris I  PanthéonSorbonne); Bertrand Hassani (CES  Centre d'économie de la Sorbonne  CNRS : UMR8174  Université Paris I  PanthéonSorbonne) 
Abstract:  Stress testing is used to determine the stability or the resilience of a given financial institution by deliberately submitting. In this paper, we focus on what may lead a bank to fail and how its resilience can be measured. Two families of triggers are analysed: the first stands in the stands in the impact of external (and / or extreme) events, the second one stands on the impacts of the choice of inadequate models for predictions or risks measurement; more precisely on models becoming inadequate with time because of not being sufficiently flexible to adapt themselves to dynamical changes. 
Keywords:  Stress test; risk; VaR 
Date:  2014–02 
URL:  http://d.repec.org/n?u=RePEc:hal:journl:halshs00951593&r=rmg 
By:  Chao, Wang; Richard, Gerlach 
Abstract:  The realized GARCH framework is extended to incorporate the realized range, and the intraday range, as potentially more efficient series of information than re alized variance or daily returns, for the purpose of volatility and tail risk forecasting in a financial time series. A Bayesian adaptive Markov chain Monte Carlo method is employed for estimation and forecasting. Compared to a range of well known parametric GARCH models, predictive loglikelihood results across six market in dex return series favor the realized GARCH models incorporating the realized range. Further, these same models also compare favourably for tail risk forecasting, both during and after the global financial crisis. 
Keywords:  Tail Risk Forecasting; Predictive Likelihood; Realized GARCH; Realized Variance; Intraday Range; Realized Range 
Date:  2014–11–07 
URL:  http://d.repec.org/n?u=RePEc:syb:wpbsba:2123/12235&r=rmg 
By:  Feng, Xiaoguang; Hayes, Dermot 
Keywords:  Agribusiness, Agricultural Finance, Financial Economics, Research Methods/ Statistical Methods, Risk and Uncertainty, 
Date:  2014 
URL:  http://d.repec.org/n?u=RePEc:ags:aaea14:170579&r=rmg 
By:  Erika GomesGoncalves (UC3M); Henryk Gzyl (IESA); Silvia Mayoral (UC3M) 
Abstract:  Here we present an application of two maxentropic procedures to determine the probability density distribution of compound sums of random variables, using only a finite number of empirically determined fractional moments. The two methods are the Standard method of Maximum Entropy (SME), and the method of Maximum Entropy in the Mean (MEM). We shall verify that the reconstructions obtained satisfy a variety of statistical quality criteria, and provide good estimations of VaR and TVaR, which are important measures for risk management purposes. We analyze the performance and robustness of these two procedures in several numerical examples, in which the frequency of losses is Poisson and the individual losses are lognormal random variables. As side product of the work, we obtain a rather accurate description of the density of the compound random variable. This is an extension of a previous application based on the Standard Maximum Entropy approach (SME) where the analytic form of the Laplace transform was available to a case in which only observed or simulated data is used. These approaches are also used to develop a procedure to determine the distribution of the individual losses through the knowledge of the total loss. Then, in the case of having only historical total losses, it is possible to decompound or disaggregate the random sums in its frequency/severity distributions, through a probabilistic inverse problem. 
Date:  2014–11 
URL:  http://d.repec.org/n?u=RePEc:arx:papers:1411.5625&r=rmg 
By:  Stijn Claessens; Swati R. Ghosh; Roxana Mihet 
Abstract:  Macroprudential policies aimed at mitigating systemic financial risks have become part of the policy toolkit in many emerging markets and some advanced countries. Their effectiveness and efficacy are not wellknown, however. Using panel data regressions, we analyze how changes in balance sheets of some 2,800 banks in 48 countries over 2000–2010 respond to specific macroprudential policies. Controlling for endogeneity, we find that measures aimed at borrowers––caps on debttoincome and loantovalue ratios––and at financial institutions––limits on credit growth and foreign currency lending––are effective in reducing asset growth. Countercyclical buffers are little effective through the cycle, and some measures are even counterproductive during downswings, serving to aggravate declines, consistent with the exante nature of macroprudential tools. 
Keywords:  Macroprudential policies and financial stability;Banking systems;Systemic risk;Risk management;Econometric models;Systemic risk, Macropudential policies, Effectiveness, Banking vulnerabilities 
Date:  2014–08–19 
URL:  http://d.repec.org/n?u=RePEc:imf:imfwpa:14/155&r=rmg 
By:  Wu, Feng; Guan, Zhengfei 
Abstract:  Recent development in production risk analyses has raised questions on the conventional approaches to estimating risk preferences. This study proposes to identify the risk separately from input equations with a seminonparametric estimator. The approach circumvents the issue of arbitrary risk specifications. Meanwhile, it facilitates analytical derivation of input equations. The GMM estimation method is then applied to input equations to estimate risk preferences. The procedure is validated by a Monte Carlo experiment. Simulation results show that the proposed method provides a consistent estimator and significantly improves estimation efficiency. 
Keywords:  Risk Preferences, GMM, Simulations, Seminonparametric Estimator, Estimation Efficiency, Production Economics, Risk and Uncertainty, C14, Q12, 
Date:  2014 
URL:  http://d.repec.org/n?u=RePEc:ags:aaea14:170625&r=rmg 
By:  Guan, Zhengfei; Wu, Feng 
Abstract:  Nonoptimal behavior due to budget constraint or credit availability is commonly observed in agricultural production. Not accounting for nonoptimal behavior would result in biased estimates of risk preferences. A generalized model is developed in this article for estimating agents’ risk attitude accommodating both optimal and nonoptimal behaviors. Results from Monte Carlo simulations suggest that estimation based on the proposed model yields consistent and unbiased risk preference estimates, whereas estimation based on the conventional modeling procedure produces biased results. 
Keywords:  Corner Solution, Nonoptimal Behavior, Risk Preferences, Budget Constraint, Monte Carlo Simulation, GMM Estimation., Agricultural Finance, Production Economics, Risk and Uncertainty, C13, C51, Q12, Q14, 
Date:  2014–05 
URL:  http://d.repec.org/n?u=RePEc:ags:aaea14:170636&r=rmg 
By:  Bekaert, Geert; Hoerova, Marie 
Abstract:  We decompose the squared VIX index, derived from US S&P500; options prices, into the conditional variance of stock returns and the equity variance premium. We evaluate a plethora of stateoftheart volatility forecasting models to produce an accurate measure of the conditional variance. We then examine the predictive power of the VIX and its two components for stock market returns, economic activity and financial instability. The variance premium predicts stock returns while the conditional stock market variance predicts economic activity and has a relatively higher predictive power for financial instability than does the variance premium. JEL Classification: C22, C52, G12, E32 
Keywords:  economic uncertainty, financial instability, option implied volatility, realized volatility, risk aversion, riskreturn tradeoff, stock return predictability, variance risk premium, VIX 
Date:  2014–05 
URL:  http://d.repec.org/n?u=RePEc:ecb:ecbwps:20141675&r=rmg 
By:  Jihun Han; Hyungbin Park 
Abstract:  Risk premium is one of main concepts in mathematical finance. It is a measure of the tradeoffs investors make between return and risk and is defined by the excess return over the riskfree interest rate earned per one unit of risk of an asset. The purpose of this article is to find the upper and lower bounds of the risk premium of an asset based on the prices of options in the market. One of key assumptions to achieve this is that the market is Markovian. Under this assumption, we can transform the problem into a problem of a secondorder differential equation and then obtain the upper and lower bounds by analyzing the differential equation. 
Date:  2014–11 
URL:  http://d.repec.org/n?u=RePEc:arx:papers:1411.4606&r=rmg 
By:  Tröger, Tobias H. 
Abstract:  This essay argues that at least some of the financial stability concerns associated with shadow banking can be addressed by an approach to financial regulation that imports its functional foundations more vigorously into the interpretation and implementation of existing rules. It shows that the general policy goals of prudential banking regulation remain constant over time despite dramatic transformations in the financial and technological landscape. Moreover, these overarching policy goals also legitimize intervention in the shadow banking sector. On these grounds, this essay encourages a more normative construction of available rules that potentially limits both the scope for regulatory arbitrage and the need for ever more rapid updates and a constant increase in the complexity of the regulatory framework. By tying the regulatory treatment of financial innovation closely to existing prudential rules and their underlying policy rationales, the proposed approach potentially ends the socially wasteful race between hare and tortoise that signifies the relation between regulators and a highly dynamic industry. In doing so it does not generally hamper market participants' efficient discoveries where disintermediation proves socially beneficial. Instead, it only weedsout rentseeking circumventions of existing rules and standards. 
Keywords:  shadow banking,regulatory arbitrage,prudential supervision 
JEL:  G21 G28 H77 K22 K23 L22 
Date:  2014 
URL:  http://d.repec.org/n?u=RePEc:zbw:imfswp:83&r=rmg 
By:  Busby, Gwen; Geiger, Richelle; Mercer, Evan 
Keywords:  Resource /Energy Economics and Policy, 
Date:  2014 
URL:  http://d.repec.org/n?u=RePEc:ags:aaea14:170714&r=rmg 
By:  Eirini Konstantinidi (University of Manchester); George Skiadopoulos (Queen Mary University of London University of Piraeus) 
Abstract:  We explore whether the market variance risk premium (VRP) can be predicted. First, we propose a novel approach to measure VRP which distinguishes the investment horizon from the variance swap's maturity. We extract VRP from actual rather than synthetic S&P 500 variance swap quotes, thus avoiding biases in VRP measurement. Next, we find that a deterioration of the economy and of the trading activity, increases VRP. These relations hold both in and outofsample for various maturities and investment horizons and they are economically significant. Volatility trading strategies which condition on the detected relations outperform popular buyandhold strategies even after transaction costs are considered. 
Keywords:  Economic conditions, Predictability, Trading activity, Variance swaps, Variance risk premium, Volatility trading 
JEL:  G13 G17 
Date:  2014–10 
URL:  http://d.repec.org/n?u=RePEc:qmw:qmwecw:wp732&r=rmg 
By:  Hac\`ene Djellout; Arnaud Guillin; Yacouba Samoura 
Abstract:  Realized statistics based on high frequency returns have become very popular in financial economics. In recent years, different nonparametric estimators of the variation of a logprice 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 logprice, we are concerned with the large deviation estimation of the vector $V\_t^n(X)=(Q\_{1,t}^n(X), Q\_{2,t}^n(X), C\_{t}^n(X))$ 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 highfrequency financial data analysis. 
Date:  2014–11 
URL:  http://d.repec.org/n?u=RePEc:arx:papers:1411.5159&r=rmg 
By:  Xiaolin Luo; Pavel V. Shevchenko 
Abstract:  In this paper we present a numerical valuation of variable annuities with combined Guaranteed Minimum Withdrawal Benefit (GMWB) and Guaranteed Minimum Death Benefit (GMDB) under optimal policyholder behaviour solved as an optimal stochastic control problem. This product simultaneously deals with financial risk, mortality risk and human behaviour. We assume that market is complete in financial risk and mortality risk is completely diversified by selling enough policies and thus the annuity price can be expressed as appropriate expectation. The computing engine employed to solve the optimal stochastic control problem is based on a robust and efficient GaussHermite quadrature method with cubic spline. We present results for three different types of death benefit and show that, under the optimal policyholder behaviour, adding the premium for the death benefit on top of the GMWB can be problematic for contracts with long maturities if the continuous fee structure is kept, which is ordinarily assumed for a GMWB contract. In fact for some long maturities it can be shown that the fee cannot be charged as any proportion of the account value  there is no solution to match the initial premium with the fair annuity price. On the other hand, the extra fee due to adding the death benefit can be charged upfront or in periodic instalment of fixed amount, and it is cheaper than buying a separate life insurance. 
Date:  2014–11 
URL:  http://d.repec.org/n?u=RePEc:arx:papers:1411.5453&r=rmg 
By:  Zhen, Miao; Qiu, Feng; Rude, James; Unterschultz, James 
Keywords:  Agribusiness, Risk and Uncertainty, 
Date:  2014 
URL:  http://d.repec.org/n?u=RePEc:ags:aaea14:170151&r=rmg 
By:  Tsunehiro Ishihara (Department of Economics, Hitotsubashi University); Yasuhiro Omori (Faculty of Economics, The University of Tokyo); Manabu Asai (Faculty of Economics, Soka University) 
Abstract:  A multivariate stochastic volatility model with the dynamic correlation and the cross leverage effect is described and its efficient estimation method using Markov chain Monte Carlo is proposed. The timevarying covariance matrices are guaranteed to be positive definite by using a matrix exponential transformation. Of particular interest is our approach for sampling a set of latent matrix logarithm variables from their conditional posterior distribution, where we construct the proposal density based on an approximating linear Gaussian state space model. The proposed model and its extended models with fattailed error distribution are applied to trivariate returns data (daily stocks, bonds, and exchange rates) of Japan. Further, a model comparison is conducted including constant correlation multivariate stochastic volatility models with leverage and diagonal multivariate GARCH models. 
Date:  2014–08 
URL:  http://d.repec.org/n?u=RePEc:tky:fseres:2014cf938&r=rmg 