nep-rmg New Economics Papers
on Risk Management
Issue of 2017‒04‒16
eighteen papers chosen by
Stan Miles
Thompson Rivers University

  1. SRISK: a conditional capital shortfall measure of systemic risk By Christian Brownlees; Robert Engle
  2. On Path–dependency of Constant Proportion Portfolio Insurance strategies By Raquel M. Gaspar
  3. Rating Trajectories and Credit Risk Migration: Evidence for SMEs By Camilla Ferretti; Giampaolo Gabbi; Piero Ganugi; Pietro Vozzella
  4. Naive Risk Parity Portfolio with Fractal Estimation of Volatility By Sergey Kamenshchikov; Ilia Drozdov
  5. Invariance properties in the dynamic gaussian copula model * By Stéphane Crépey; Shiqi Song
  6. Illiquidity Component of Credit Risk By Stephen Morris; Hyun Song Shin
  7. Realized Matrix-Exponential Stochastic Volatility with Asymmetry, Long Memory and Spillovers By Asai, M.; Chang, C-L.; McAleer, M.J.
  8. Reinterpreting the mutual fund theorem: the risk portfolio as a tactical overlay By Tenani, Paulo Sérgio
  9. Sharp Target Range Strategies with Application to Dynamic Portfolio Selection By Rongju Zhang; Nicolas Langren\'e; Yu Tian; Zili Zhu; Fima Klebaner; Kais Hamza
  10. Parameter uncertainty for integrated risk capital calculations based on normally distributed subrisks By Andreas Fr\"ohlich; Annegret Weng
  11. Rare Events and Risk Perception: Evidence from Fukushima Accident "Abstract: We study changes in nuclear-risk perception following the Fukushima nuclear accident of March 2011. Using an exhaustive registry of individual housing transactions in England and Wales between 2007 and 2014, we implement a difference-in-difference strategy and compare housing prices in at-risk areas to areas further away from nuclear sites before and after Fukushima incident. We find a persistent price malus of about 3.5% in response to the Fukushima accident for properties close to nuclear plants. We show evidence that this price malus can be interpreted as a change in nuclear-risk perception. In addition, the price decrease is much larger for high-value properties within neighborhoods, and deprived zones in at-risk areas are more responsive to the accident. We discuss various theoretical channels that could explain these results. " By Renaud Coulomb; Yanos Zylberberg
  12. Splitting Risks in Insurance Markets In Adverse Selection By Pierre Picard
  13. The Role of Economic and Financial Uncertainties in Predicting Commodity Futures Returns and Volatility: Evidence from a Nonparametric Causality-in-Quantiles Test By Mehmet Balcilar; Walid Bahloul; Juncal Cunado; Rangan Gupta
  14. Volatility risk premia and future commodities returns By José Renato Haas Ornelas; Roberto Baltieri Mauad
  15. Mostly Prior-Free Asset Allocation By Sylvain Chassang
  16. Impacts of OPEC's political risk on the international crude oil prices: An empirical analysis based on the SVAR models By Hao Chen; Hua Liao; Bao-Jun Tang; Yi-Ming Wei
  17. On coherency and other properties of MAXVAR By Jie Sun; Qiang Yao
  18. Modelling Volatility Spillovers for Bio-ethanol, Sugarcane and Corn Spot and Futures Prices By Chang, C-L.; McAleer, M.J.; Wang, Y-A.

  1. By: Christian Brownlees; Robert Engle
    Abstract: We introduce SRISK to measure the systemic risk contribution of a financial firm. SRISK measures the capital shortfall of a firm conditional on a severe market decline, and is a function of its size, leverage and risk. We use the measure to study top US financial institutions in the recent financial crisis. SRISK delivers useful rankings of systemic institutions at various stages of the crisis and identifies Fannie Mae, Freddie Mac, Morgan Stanley, Bear Stearns and Lehman Brothers as top contributors as early as 2005-Q1. Moreover, aggregate SRISK provides early warning signals of distress in indicators of real activity. JEL Classification: C22, C23, C53, G01, G20Keywords: Systemic Risk Measurement, Great Financial Crisis, GARCH, DCC
    Date: 2017–03
  2. By: Raquel M. Gaspar
    Abstract: This paper evaluates the path-dependency/independency of the most widespread Portfolio Insurance strategies. In particular, we look into various Constant Proportion Portfolio Insurance (CPPI) structures and compare them to the classical Option Based Portfolio Insurance (OBPI) and with naive strategies such as Stop-loss Portfolio Insurance (SLPI).The paper is based upon conditional Monte Carlo simulations and we show that CPPI strategies with a multiplier higher than 1 are extremely path-dependent and that they can easily get cash-locked, even in scenarios when the underlying at maturity can be worth much more than initially. This likelihood of being cash-locked increases with maturity of the CPPI as well as with properties of the underlying's dynamics and is a major drawback to investors.To emphasise path dependency of CPPIs, we show that even in scenarios where the investor correctly "guesses" a higher future value for the underlying, CPPIs can get cash-locked and lead to losses. This path-dependency problem is specific of CPPIs, it goes against theEuropean-style nature of most traded CPPIs, and it does not occur in the classical case of OBPI strategies.We expect that this study will contribute to reinforce the idea that CPPI strategies suffer from a serious design problem. To clearly show the path dependency and the problems of CPPI strategies, the simulation exercise preformed in this paper takes a point of view that is not the one of the previous literature. Although we use a standard geometric Brownian motion to model the underlying, our Monte Carlo simulated paths are all conditioned to fixed final value, using the methodology proposed by Sousa, Esquível and Gaspar (2015). The financial intuition is to consider the point of view of an investor who has some expectation about the future value of an underlying asset at maturity, but uses portfolio insurance hedge against the possibility of being wrong. In our simulations we consider the investor is right, and show that, despite this, CPPI strategies with multipliers higher than one, can still lead to losses. This occurs due to the ``cash-lock'' property of CPPI strategies, which makes the risk of the strategy to become unrelated to the evolution of the underlying. Term sheets of most real life CPPIs simply ignore this important path-dependency risk. The existence of this path dependency make it hard to understand which investor risk profile is this product meant to satisfy. In fact, the traditional alternatives always stochastically dominate CPPIs with multipliers higher than 1 are. We expect this study contributes to the debate on design risk of structured products and reinforce the idea that CPPI products are ill conceived.
    Keywords: n.a., Finance, Finance
    Date: 2016–07–04
  3. By: Camilla Ferretti (DISCE, Università Cattolica); Giampaolo Gabbi (DISAG, Università di Siena); Piero Ganugi (DIA, Università di Parma); Pietro Vozzella (DISAG, Università di Siena)
    Abstract: The misestimation of rating transition probabilities may lead banks to lend money incoherently with borrowers’ default trajectory, causing both a deterioration in asset quality and higher system distress. Applying a Mover-Stayer model to determine the migration risk of small and medium enterprises, we find that banks are overestimating their credit risk resulting in excessive regulatory capital. This has important macroeconomic implications due to the fact that holding a large capital buffer is costly for banks and this in turn influences their ability to lend in the wider economy. This conclusion is particularly true during economic downturns with the consequence of exacerbating the cyclicality in risk capital that therefore acts to aggravate economic conditions further. We also explain part of the misevaluation of borrowers and the actual relevant weight of nonperforming loans within banking portfolios: prudential prescriptions cannot be considered as effective as expected by regulators who have designed the “new” regulation in response to the most recent crisis.The Mover-Stayers approach helps to reduce calculation inaccuracy when analyzing the historical movements of borrowers’ ratings and, consequently improves the efficacy of the resource allocation process and banking industry stability.
    Keywords: credit risk; Markov chains; absorbing state; rating migration
    Date: 2016–07
  4. By: Sergey Kamenshchikov; Ilia Drozdov
    Abstract: A fractal approach to long-only portfolio optimization is proposed. The quantitative system is based on naive risk parity approach. The core of the optimization scheme is a fractal distribution of returns, applied to estimation of the volatility law. Out-of-sample performance data has been represented in ten period of observation with half year and one year horizons. Implementation of fractal estimator of volatility improves all performance metrics of portfolio in comparison to the standard estimator of volatility. The efficiency of fractal estimator plays a significant protective role for the periods of market abnormal volatility and drawdowns, which allows beating the market in the long term perspective. The provided results may be useful for a wide range of quantitative investors, including hedge funds, robo-advisors and retail investors.
    Date: 2017–03
  5. By: Stéphane Crépey (LaMME - Laboratoire de Mathématiques et Modélisation d'Evry - INRA - Institut National de la Recherche Agronomique - UEVE - Université d'Évry-Val-d'Essonne - ENSIIE - CNRS - Centre National de la Recherche Scientifique); Shiqi Song (LaMME - Laboratoire de Mathématiques et Modélisation d'Evry - INRA - Institut National de la Recherche Agronomique - UEVE - Université d'Évry-Val-d'Essonne - ENSIIE - CNRS - Centre National de la Recherche Scientifique)
    Abstract: We prove that the default times (or any of their minima) in the dynamic Gaussian copula model of Crépey, Jeanblanc, and Wu (2013) are invariance times in the sense of Crépey and Song (2017), with related invariance probability measures different from the pricing measure. This reflects a departure from the immersion property, whereby the default intensities of the surviving names and therefore the value of credit protection spike at default times. These properties are in line with the wrong-way risk feature of counterparty risk embedded in credit derivatives, i.e. the adverse dependence between the default risk of a counterparty and an underlying credit derivative exposure.
    Keywords: time, CDS, immersion property, dynamic copula,counterparty credit risk, wrong-way risk, Gaussian copula, invariance
    Date: 2017–02–03
  6. By: Stephen Morris (Princeton University); Hyun Song Shin (Bank for International Settlements; Princeton University)
    Abstract: We provide a theoretical decomposition of bank credit risk into insolvency risk and illiquidity risk, defining illiquidity risk to be the counterfactual probability of failure due to a run when the bank would have survived in the absence of a run. We show that illiquidity risk is (i) decreasing in the "liquidity ratio"--the ratio of realizable cash on the balance sheet to short-term liabilities; (ii) decreasing in the excess return of debt; and (iii) increasing in the solvency uncertainty--a measure of the variance of the asset portfolio.
    JEL: G21 G32 G33
    Date: 2016–05
  7. By: Asai, M.; Chang, C-L.; McAleer, M.J.
    Abstract: The paper develops a novel realized matrix-exponential stochastic volatility model of multivariate returns and realized covariances that incorporates asymmetry and long memory (hereafter the RMESV-ALM model). The matrix exponential transformation guarantees the positivedefiniteness of the dynamic covariance matrix. The contribution of the paper ties in with Robert Basmann’s seminal work in terms of the estimation of highly non-linear model specifications (“Causality tests and observationally equivalent representations of econometric models”, Journal of Econometrics, 1988, 39(1-2), 69–104), especially for developing tests for leverage and spillover effects in the covariance dynamics. Efficient importance sampling is used to maximize the likelihood function of RMESV-ALM, and the finite sample properties of the quasi-maximum likelihood estimator of the parameters are analysed. Using high frequency data for three US financial assets, the new model is estimated and evaluated. The forecasting performance of the new model is compared with a novel dynamic realized matrix-exponential conditional covariance model. The volatility and co-volatility spillovers are examined via the news impact curves and the impulse response functions from returns to volatility and co-volatility.
    Keywords: Matrix-exponential transformation, Realized stochastic covariances, Realized conditional, covariances, Asymmetry, Long memory, Spillovers, Dynamic covariance matrix, Finite, sample properties, Forecasting performance.
    JEL: C22 C32 C58 G32
    Date: 2016–09–01
  8. By: Tenani, Paulo Sérgio
    Abstract: The Mutual Fund Theorem is an elegant way of describing how investors with different attitudes towards risk should construct their portfolios. It is, however, often misinterpreted. This paper revisits the topic by defining the Risk Portfolio as a self-financed tactical overlay portfolio in which all the overweight and underweight positions cancel each other out. In this sense no net resources are ever allocated to the Risk Portfolio and all the investment is allocated to the Minimum Variance Portfolio. Under these circumstances the Mutual Fund Theorem implies that the ratio of Bonds to Stocks in the Total Portfolio would depend on investor´s risk aversion; as it is actually observed in practice. The paper also argues that the Asset Allocation puzzle, as traditionally stated in the literature, only arises because of a misconception about the “the facto” definition of the Risk Portfolio.
    Date: 2017–01–24
  9. By: Rongju Zhang; Nicolas Langren\'e; Yu Tian; Zili Zhu; Fima Klebaner; Kais Hamza
    Abstract: A family of sharp target range strategies is presented for portfolio selection problems. Our proposed strategy maximizes the expected portfolio value within a target range, composed of a conservative lower target representing capital guarantee and a desired upper target representing investment goal. This strategy favorably shapes the entire probability distribution of return, as it simultaneously seeks a high expected return, cuts off downside risk, and implicitly caps volatility, skewness and other higher moments of the return distribution. To illustrate the effectiveness of our new investment strategies, we study a multi-period portfolio selection problem with transaction cost, where the results are generated by the Least-Squares Monte-Carlo algorithm. Our numerical tests show that the presented strategy produces a better efficient frontier, a better trade-off between return and downside risk, and a wider range of possible risk profiles than classical constant relative risk aversion utility. Finally, straightforward extensions of the sharp target range are presented, such as purely maximizing the probability of achieving the target range, adding an explicit target range for realized volatility, and defining the range bounds as excess return over a stochastic benchmark, for example, stock index or inflation rate. These practical extensions make the approach applicable to a wide array of investment funds, including pension funds, controlled-volatility funds, and index-tracking funds.
    Date: 2017–04
  10. By: Andreas Fr\"ohlich; Annegret Weng
    Abstract: In this contribution we consider the overall risk given as the sum of random subrisks $\mathbf{X}_j$ in the context of value-at-risk (VaR) based risk calculations. If we assume that the undertaking knows the parametric distribution family subrisk $\mathbf{X}_j=\mathbf{X}_j(\theta_j)$, but does not know the true parameter vectors $\theta_j$, the undertaking faces parameter uncertainty. To assess the appropriateness of methods to model parameter uncertainty for risk capital calculation we consider a criterion introduced in the recent literature. According to this criterion, we demonstrate that, in general, appropriateness of a risk capital model for each subrisk does not imply appropriateness of the model on the aggregate level of the overall risk.\\ For the case where the overall risk is given by the sum of normally distributed subrisks we prove a theoretical result leading to an appropriate integrated risk capital model taking parameter uncertainty into account. Based on the theorem we develop a method improving the approximation of the required confidence level simultaneously for both - on the level of each subrisk as well as for the overall risk.
    Date: 2017–04
  11. By: Renaud Coulomb (University of Melbourne); Yanos Zylberberg (Bristol University)
    Keywords: Hedonic prices, housing markets, risk perception, nuclear power.
    JEL: D80 Q51 Q53 R21 R23 R31
    Date: 2016–03
  12. By: Pierre Picard (Ecole Polytechnique [Palaiseau])
    Abstract: We characterize the design of insurance schemes when policyhold- ers face several insurable risks in a context of adverse selection. Split- ting risks emerges as a feature of second-best Pareto-optimal alloca- tions. This may take the form of risk-speci c contracts, or of con- tracts where risks are bundled, but subject to di⁄erential coverage rules such as risk speci c copayments, combined with a deductible, an out-of-pocket maximum or a cap on coverage.
    Keywords: Insurance, adverse selection, contract, health insurance, copayment, deductible
    Date: 2017–01–22
  13. By: Mehmet Balcilar (Department of Economics, Eastern Mediterranean University, Famagusta, Northern Cyprus, Turkey and Department of Economics, University of Pretoria, Pretoria, South Africa); Walid Bahloul (Governance, Finance and Accounting Laboratory, Faculty of Business and Economics, University of Sfax, Sfax, Tunisia); Juncal Cunado (University of Navarra, School of Economics, Edificio Amigos, Pamplona, Spain.); Rangan Gupta (Department of Economics, University of Pretoria, Pretoria, South Africa)
    Abstract: We analyze the ability of economic and financial uncertainties in predicting movements in commodity futures markets. Using daily data over the period of 8th May, 1992 to 31st August, 2016 on 21 commodity futures covering agriculture, energy, metals and livestock, we find that: (a) Linear predictive tests provide virtually no evidence of predictability; (b) Linear models are misspecified due to nonlinearity and hence, results from the framework cannot be relied upon, and; (c) Using a k-th order nonparametric causality-in-quantiles test, which is robust to misspecification in the presence of nonlinearities, we find evidence that measures of uncertainty can predict returns and/or volatility of as many as 20 of the commodities considered at least at one point of their respective conditional distributions for returns and variance. In general, we highlight the importance of modeling nonlinearity, higher order moments, and quantiles of returns and volatility when carrying out predictability analysis involving commodity futures and uncertainty.
    Keywords: Economic and Financial Uncertainty, Commodity Futures Markets, Returns, Volatility, Nonparametric Causality-in-Quantiles Test.
    JEL: C22 G13 Q02
    Date: 2017–04
  14. By: José Renato Haas Ornelas; Roberto Baltieri Mauad
    Abstract: This paper extends the empirical literature on Volatility Risk Premium (VRP) and future returns by analyzing the predictive ability of Commodities Currencies VRP and commodities VRP. The empirical evidence throughout this paper provides support for a positive relationship of Commodities Currencies VRP and future commodities returns, but only for the period after the 2008 Global Financial Crisis. This predictability survives to the inclusion of control variables like the Equity VRP and past currency returns. Furthermore, we find a negative relationship between Gold VRP and future commodities and currency returns. This result corroborates the view of Gold as a safe haven asset.
    Keywords: commodities predictability, volatility risk premium, safe haven
    Date: 2017–03
  15. By: Sylvain Chassang (Princeton University)
    Abstract: This paper develops a prior-free version of Markowitz (1952)’s efficient portfolio theory that allows the decision maker to express preferences over risk and reward, even though she is unable to express a prior over potentially non-stationary returns. The corresponding optimal allocation strategies are admissible, interior, and exhibit a form of momentum. Empirically, prior-free efficient allocation strategies successfully exploit time-varying risk premium present in historical returns.
    Keywords: prior-free portfolios, non-stationary returns, time-varying risk premium, fear-of-missing out, fear-of-loss, regret aversion, drawdown frontier
    JEL: G11
    Date: 2016–01
  16. By: Hao Chen; Hua Liao; Bao-Jun Tang; Yi-Ming Wei (Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology)
    Abstract: The impacts of OPEC's political risk on the fluctuations of international crude oil prices have caused widespread concern and analyzing the impacts is of great significance to the investment decisions and risk aversion strategies in the crude oil markets. Therefore, using the International Country Risk Guide (ICRG) index as a proxy for the countries' political risk situation, we empirically investigate the impacts of OPEC's political risk on the Brent crude oil prices, based on several Structural Vector Autoregression (SVAR) models. The main empirical results indicate that: (1) The political risk of OPEC countries does have a significant and positive influence on Brent crude oil prices in the sample period from January 1998 to September 2014, and the most significant positive influences appear in about one and a half year and last about a year. (2) The OPEC's integrated political risk contribute to 17.58% of the oil price fluctuations in the sample period, which is only lesser than that of the oil demand shocks (34.64%). (3) Compared with the political risk of OPEC countries in North Africa and South America, the political risk of OPEC countries in Middle East contribute most to the oil price fluctuations. (4) Among the eight components of the political risk in OPEC, the internal conflicts contribute most to the oil price fluctuations in the sample period.
    Keywords: OPEC; Political risk; Oil price; SVAR
    JEL: Q54 Q40
    Date: 2016–10–01
  17. By: Jie Sun; Qiang Yao
    Abstract: Consider the MAXVAR risk measure on L^2 space. We present a simple and direct proof of its coherency and aversity. Based on the observation that the MAXVAR measure is a continuous convex combination of the CVAR measure, we provide an explicit formula for the risk envelope of MAXVAR.
    Date: 2017–03
  18. By: Chang, C-L.; McAleer, M.J.; Wang, Y-A.
    Abstract: The recent and rapidly growing interest in biofuel as a green energy source has raised concerns about its impact on the prices, returns and volatility of related agricultural commodities. Analyzing the spillover effects on agricultural commodities and biofuel helps commodity suppliers hedge their portfolios, and manage the risk and co-risk of their biofuel and agricultural commodities. There have been many papers concerned with analyzing crude oil and agricultural commodities separately. The purpose of this paper is to examine the volatility spillovers for spot and futures returns on bio-ethanol and related agricultural commodities, specifically corn and sugarcane. The diagonal BEKK model is used as it is the only multivariate conditional volatility model with well-established regularity conditions and known asymptotic properties. The daily data used are from 31 October 2005 to 14 January 2015. The empirical results show that, in 2 of 6 cases for the spot market, there were significant negative co-volatility spillover effects: specifically, corn on subsequent sugarcane co-volatility with corn, and sugarcane on subsequent corn co-volatility with sugarcane. In the other 4 cases, there are no significant co-volatility spillover effects. There are significant positive co-volatility spillover effects in all 6 cases, namely between corn and sugarcane, corn and ethanol, and sugarcane and ethanol, and vice-versa, for each of the three pairs of commodities. It is clear that the futures prices of bio-ethanol and the two agricultural commodities, corn and sugarcane, have stronger co-volatility spillovers than their spot price counterparts. These empirical results suggest that the bio-ethanol and agricultural commodities should be considered as viable futures products in financial portfolios for risk management
    Keywords: Biofuel, spot prices, futures prices, returns, volatility, risk, co-risk, bio-ethanol, corn, sugarcane, diagonal BEKK model, co-volatility spillover effects, hedging, risk management.
    JEL: C32 C58 G13 G15 Q14 Q42
    Date: 2016–12–01

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