
on Risk Management 
By:  CHEN, Cathy W.S.; WENG, Monica M.C.; WATANABE, Toshiaki 
Abstract:  To allow for a higher degree of flexibility in model parameters, we propose a general and timevarying nonlinear smooth transition (ST) heteroskedastic model with a secondorder logistic function of varying speed in the mean and variance. This paper evaluates the performance of ValueatRisk (VaR) measures in a class of risk models, specially focusing on three distinct ST functions with GARCH structures: first and secondorder logistic functions, and the exponential function. The likelihood function is nondifferentiable in terms of the threshold values and delay parameter. We employ Bayesian Markov chain Monte Carlo sampling methods to update the estimates and quantile forecasts. The proposed methods are illustrated using simulated data and an empirical study. We estimate VaR forecasts for the proposed models alongside some competing asymmetric models with skew and fattailed error probability distributions, including realized volatility models. To evaluate the accuracy of VaR estimates, we implement two loss functions and three backtests. The results show that the ST model with a secondorder logistic function and skew Student’s t error is a worthy choice at the 1% level, when compared to a range of existing alternatives. 
Keywords:  Secondorder logistic transition function, Backtesting, Markov chain Monte Carlo methods, ValueatRisk, Volatility forecasting, Realized volatility models 
Date:  2015–12–08 
URL:  http://d.repec.org/n?u=RePEc:hit:hiasdp:hiase16&r=rmg 
By:  Allen, D.E.; McAleer, M.J.; Powell, R.J.; Singh, A.K. 
Abstract:  This paper features an analysis of the effectiveness of a range of portfolio diversification strategies, with a focus on downside risk metrics, as a portfolio diversification strategy in a European market context. We apply these measures to a set of daily arithmetically compounded returns on a set of ten market indices representing the major European markets for a nine year period from the beginning of 2005 to the end of 2013. The sample period, which incorporates the periods of both the Global Financial Crisis (GFC) and subsequent European Debt Crisis (EDC), is challenging one for the application of portfolio investment strategies. The analysis is undertaken via the examination of multiple investment strategies and a variety of holdout periods and backtests. We commence by using four two year estimation periods and subsequent one year investment hold out period, to analyse a naive 1/N diversification strategy, and to contrast its effectiveness with Markowitz mean variance analysis with positive weights. Markowitz optimisation is then compared with various down side investment opimisation strategies. We begin by comparing Markowitz with CVaR, and then proceed to evaluate the relative e effctiveness of Markowitz with various drawdown strategies, utilising a series of backtests. Our results suggest that none of the more sophisticated optimisation strategies appear to dominate naive diversification. 
Keywords:  portfolio diversification, Markowitz analysis, downside risk, CVaR, drawdown 
JEL:  G11 C61 
Date:  2015–11–01 
URL:  http://d.repec.org/n?u=RePEc:ems:eureir:79216&r=rmg 
By:  Marco Bardoscia; Fabio Caccioli; Juan Ignacio Perotti; Gianna Vivaldo; Guido Caldarelli 
Abstract:  We consider a dynamical model of distress propagation on complex networks, which we apply to the study of financial contagion in networks of banks connected to each other by direct exposures. The model that we consider is an extension of the DebtRank algorithm, recently introduced in the literature. The mechanics of distress propagation is very simple: When a bank suffers a loss, distress propagates to its creditors, who in turn suffer losses, and so on. The original DebtRank assumes that losses are propagated linearly between connected banks. Here we relax this assumption and introduce a oneparameter family of nonlinear propagation functions. As a case study, we apply this algorithm to a dataset of 183 European banks, and we study how the stability of the system depends on the nonlinearity parameter under different stresstest scenarios. We find that the system is characterized by a transition between a regime where small shocks can be amplified and a regime where shocks do not propagate, and that the overall the stability of the system increases between 2008 and 2013. 
Date:  2015–12 
URL:  http://d.repec.org/n?u=RePEc:arx:papers:1512.04460&r=rmg 
By:  Frank Gehmlich; Thorsten Schmidt 
Abstract:  The intensity of a default time is obtained by assuming that the default indicator process has an absolutely continuous compensator. Here we drop the assumption of absolute continuity with respect to the Lebesgue measure and only assume that the compensator is absolutely continuous with respect to a general $\sigma$finite measure. This allows for example to incorporate the Mertonmodel in the generalized intensity based framework. An extension of the BlackCox model is also considered. We propose a class of generalized Merton models and study absence of arbitrage by a suitable modification of the forward rate approach of HeathJarrowMorton (1992). Finally, we study affine term structure models which fit in this class. They exhibit stochastic discontinuities in contrast to the affine models previously studied in the literature. 
Date:  2015–12 
URL:  http://d.repec.org/n?u=RePEc:arx:papers:1512.03896&r=rmg 
By:  Dionne, Georges (HEC Montreal, Canada Research Chair in Risk Management); Malekan, Sara (HEC Montreal, Canada Research Chair in Risk Management) 
Abstract:  We address the moral hazard problem of securitization using a principalagent model where the investor is the principal and the lender is the agent. Our model considers structured assetbacked securitization with a credit enhancement procedure. We assume that the originator can affect the default probability and the conditional loss distribution. We show that the optimal form of retention must be proportional to the pool default loss even in the absence of systemic risk when the originator can affect the conditional distribution of portfolio losses, yet the current regulations propose a constant retention rate. 
Keywords:  Securitization; optimal retention; moral hazard; principalagent model; tranching; credit enhancement; conditional loss distribution. 
JEL:  D80 D82 D86 G18 G21 G23 
Date:  2015–11–27 
URL:  http://d.repec.org/n?u=RePEc:ris:crcrmw:2015_004&r=rmg 
By:  Michael Wosser (Department of Economics, Finance and Accounting, Maynooth University.) 
Abstract:  Using a sample of 75 developed and emerging economies covering the period 19982011 we show that the enhanced Basel III Accord variables Tier1 capital and the new liquidity measure known as the Net Stable Funding Ratio (NSFR), when measured in levels, do not feature as systemic banking crisis determinants. Neither does distance from the minimum standard, in either direction, matter. However the compound annual growth rate of Tier1 capital is shown to be significantly associated with overall financialservices stability. Certain aspects of the regulatory environment are shown to contribute positively towards systemic risk mitigation whereas others do not. For example by restricting the breadth of trading activities permitted to banks, banking sectors are made stable. However regimes where capital adequacy standards are rigorously enforced are no more robust than their less strictlyenforced counterparts. 
Keywords:  Systemic Banking Crises; Determinants; Basel III Accord; Regulations; Regulatory Framework; Stability; Early Warning System 
JEL:  G21 G28 
Date:  2015 
URL:  http://d.repec.org/n?u=RePEc:may:mayecw:n26515.pdf&r=rmg 
By:  Christopher W. Miller; Insoon Yang 
Abstract:  We consider continuoustime stochastic optimal control problems featuring Conditional ValueatRisk (CVaR) in the objective. The major difficulty in these problems arises from timeinconsistency, which prevents us from directly using dynamic programming. To resolve this challenge, we convert to an equivalent bilevel optimization problem in which the inner optimization problem is standard stochastic control. Furthermore, we provide conditions under which the outer objective function is convex and differentiable. We compute the outer objective's value via a HamiltonJacobiBellman equation and its gradient via the viscosity solution of a linear parabolic equation, which allows us to perform gradient descent. The significance of this result is that we provide an efficient dynamic programmingbased algorithm for optimal control of CVaR without lifting the statespace. To broaden the applicability of the proposed algorithm, we provide convergent approximation schemes in cases where our key assumptions do not hold and characterize relevant suboptimality bounds. In addition, we extend our method to a more general class of risk metrics, which includes meanvariance and mediandeviation. We also demonstrate a concrete application to portfolio optimization under CVaR constraints. Our results contribute an efficient framework for solving timeinconsistent CVaRbased dynamic optimization. 
Date:  2015–12 
URL:  http://d.repec.org/n?u=RePEc:arx:papers:1512.05015&r=rmg 
By:  Libin Yang; William Rea; Alethea Rea 
Abstract:  We show that the last few components in principal component analysis of the correlation matrix of a group of stocks may contain useful financial information by identifying highly correlated pairs or larger groups of stocks. The results of this type of analysis can easily be included in the information an investor uses to manage their portfolio. 
Date:  2015–12 
URL:  http://d.repec.org/n?u=RePEc:arx:papers:1512.03537&r=rmg 