nep-rmg New Economics Papers
on Risk Management
Issue of 2017‒08‒27
fourteen papers chosen by
Stan Miles
Thompson Rivers University

  1. Portfolio Optimization with Entropic Value-at-Risk By Amir Ahmadi-Javid; Malihe Fallah-Tafti
  2. Models with Short-Term Variations and Long-Term Dynamics in Risk Management of Commodity Derivatives By Guo, Zi-Yi
  3. VIX-linked fees for GMWBs via Explicit Solution Simulation Methods By Michael A. Kouritzin; Anne MacKay
  4. The impact of sectoral macroprudential capital requirements on mortgage lending: evidence from the Belgian risk weight add-on By Ferrari, Stijn; Pirovano, Mara; Rovira Kaltwasser, Pablo
  5. Managing Counterparty Risk in OTC Markets By Christoph Frei; Agostino Capponi; Celso Brunetti
  6. Capturing the Black Swan: Scenario-Based Asset Allocation with Fat Tails and Non-Linear Correlations By Vsevolod I Gorlach
  7. Does Extreme Rainfall Lead to Heavy Economic Losses in the Food Industry? By Edimilson Costa Lucas; Wesley Mendes Da Silva; Gustavo Silva Araujo
  8. Variance stochastic orders By Gollier, Christian
  9. Risk Spillover between the US and the Remaining G7 Stock Markets Using Time-Varying Copulas with Markov Switching: Evidence from Over a Century of Data By Qiang Ji; Bing-Yue Liu; Juncal Cunado; Rangan Gupta
  10. Empirical Performance of GARCH Models with Heavy-tailed Innovations By Guo, Zi-Yi
  11. Bank capital and risk-taking: evidence from misconduct provisions By Tracey, Belinda; Schnittker, Christian; Sowerbutts, Rhiannon
  12. The impact of Basel III on money creation: A synthetic analysis By Xiong, Wanting; Wang, Yougui
  13. BSDEs with weak reflections and partial hedging of American options By Roxana Dumitrescu; Romuald Elie; Wissal Sabbagh; Chao Zhou
  14. Competitiveness and Economic Integration in IDB Member Countries By Mohammed Ali, Khalifa

  1. By: Amir Ahmadi-Javid; Malihe Fallah-Tafti
    Abstract: The entropic value-at-risk (EVaR) is a new coherent risk measure, which is an upper bound for both the value-at-risk (VaR) and conditional value-at-risk (CVaR). As important properties, the EVaR is strongly monotone over its domain and strictly monotone over a broad sub-domain including all continuous distributions, while well-known monotone risk measures, such as VaR and CVaR lack these properties. A key feature for a risk measure, besides its financial properties, is its applicability in large-scale sample-based portfolio optimization. If the negative return of an investment portfolio is a differentiable convex function, the portfolio optimization with the EVaR results in a differentiable convex program whose number of variables and constraints is independent of the sample size, which is not the case for the VaR and CVaR. This enables us to design an efficient algorithm using differentiable convex optimization. Our extensive numerical study shows the high efficiency of the algorithm in large scales, compared to the existing convex optimization software packages. The computational efficiency of the EVaR portfolio optimization approach is also compared with that of CVaR-based portfolio optimization. This comparison shows that the EVaR approach generally performs similarly, and it outperforms as the sample size increases. Moreover, the comparison of the portfolios obtained for a real case by the EVaR and CVaR approaches shows that the EVaR approach can find portfolios with better expectations and VaR values at high confidence levels.
    Date: 2017–08
  2. By: Guo, Zi-Yi
    Abstract: We adopt Schwartz and Smith’s model (2000) to calculate risk measures of Brent oil futures contracts and light sweet crude oil (WTI) futures contracts and Mirantes, Poblacion and Serna’s model (2012) to calculate risk measures of natural gas futures contracts, gasoil futures contracts, heating oil futures contracts, RBOB gasoline futures contracts, PJM western hub peak and off-peak electricity futures contracts. We show that the models present well goodness of fit and explain two stylized facts of the data: the Samuelson effect and the seasonality effect. Our backtesting results demonstrate that the models provide satisfactory risk measures for listed energy commodity futures contracts. A simple estimation method possessing quick convergence is developed.
    Keywords: Samuelson effect,seasonal effect,value-at-risk,least-square-estimation
    Date: 2017
  3. By: Michael A. Kouritzin; Anne MacKay
    Abstract: In a market with stochastic volatility and jumps, we consider a VIX-linked fee structure for variable annuity contracts with guaranteed minimum withdrawal benefits (GMWB). Our goal is to assess the effectiveness of the VIX-linked fee structure in decreasing the sensitivity of the insurer's liability to volatility risk. Since the GMWB payoff is highly path-dependent, it is particularly sensitive to volatility risk, and can also be challenging to price, especially in the presence of the VIX-linked fee. In this paper, we present an explicit weak solution for the value of the VA account and use it in Monte Carlo simulations to value the GMWB guarantee. Numerical examples are provided to analyze the impact of the VIX-linked fee on the sensitivity of the liability to changes in market volatility.
    Date: 2017–08
  4. By: Ferrari, Stijn; Pirovano, Mara; Rovira Kaltwasser, Pablo
    Abstract: In December 2013 the National Bank of Belgium introduced a sectoral capital requirement aimed at strengthening the resilience of Belgian banks against adverse developments in the real estate market. This paper assesses the impact of this macroprudential measure on mortgage lending. Our results indicate that the sectoral capital requirement on average did not affect IRB banks’ mortgage rates and mortgage loan growth. However, the findings do indicate that IRB banks may have reacted heterogeneously to the introduction of the measure: capital-constrained banks with more exposures to the segment targeted by the additional requirement tended to respond stronger in terms of mortgage lending.
    Keywords: Systemic risk, macroprudential policy, bank capital requirements, real estate.
    JEL: E44 E58 G21 G28
    Date: 2017–08
  5. By: Christoph Frei; Agostino Capponi; Celso Brunetti
    Abstract: We study how banks manage their default risk before bilaterally negotiating the quantities and prices of over-the-counter (OTC) contracts resembling credit default swaps (CDSs). We show that the costly actions exerted by banks to reduce their default probabilities are not socially optimal. Depending on the imposed trade size limits, risk-management costs and sellers' bargaining power, banks may switch from choosing default risk levels above the social optimum to reducing them even below the social optimum. We use a unique and comprehensive data set of bilateral exposures from the CDS market to test the main model implications on the OTC market structure: (i) intermediation is done by low-risk banks with medium credit exposure; (ii) all banks with high credit exposures are net buyers of CDSs, and low-risk banks with low credit exposures are the main net sellers; and (iii) heterogeneity in post-trade credit exposures is higher for riskier banks and smaller for safer banks.
    Keywords: Over-the-counter markets ; Counterparty risk ; Credit default swaps ; Search
    JEL: G11 G12 G21
    Date: 2017–08–15
  6. By: Vsevolod I Gorlach
    Abstract: This paper highlights the shortfalls of Modern Portfolio Theory (MPT). Amongst other flaws, MPT assumes that returns are normally distributed; that correlations are linear; and that risks are symmetrical. We propose a dynamic and flexible scenario-based approach to portfolio selection that incorporates an investor’s economic forecast. Extreme Value Theory (EVT) is used to capture the skewness and kurtosis inherent in asset-class returns; and it also accounts for the volatility clustering and the extreme co-movements across asset classes. The estimation consists of using an asymmetric GJR-GARCH model to extract the filtered residuals for each asset-class return. Subsequently, a marginal cumulative distribution function (CDF) of each asset class is constructed by using a Gaussian-kernel estimation for the interior, together with a generalised Pareto distribution (GPD) for the upper and lower tails. The distribution of exceedance method is applied to find residuals in the tails. A Student’s t copula is then fitted to the data; and then used to induce correlation between the simulated residuals of each asset class. A Monte Carlo technique is applied to simulate standardised residuals, which represent a univariate stochastic process when viewed in isolation; but it maintains the correlation induced by the copula. The results are mean-CVaR optimised portfolios, which are derived based on an investor’s forward-looking expectation.
    Keywords: Portfolio optimisation, Scenario-based, Non-normal distribution, Fat-tails, Non-linear correlation, Extreme Value Theory, Marginal Distribution Modelling, Copula, simulation, Conditional Value-at-Risk
    JEL: C14 C58 C61 G11 G17
    Date: 2017–08
  7. By: Edimilson Costa Lucas; Wesley Mendes Da Silva; Gustavo Silva Araujo
    Abstract: Natural extreme events have been occurring more frequently with growing impacts in well-being, mainly in emerging economies. Therefore, the need for more accurate information for managing such impacts has grown. In response to this issue, financial literature has been focusing on the assessment of economic impacts that arise from extreme weather changes. However, these efforts have imparted little attention to the economic impact analysis at the corporate level. To reduce this gap, this article analyzes the impact of extreme rainfall events on the food industry in an emerging economy that is a prominent player in this sector, Brazil. For this purpose, we use the ARGARCH-GPD hybrid methodology to identify whether extreme rainfalls affect stock prices of food companies. The results indicate that these events have a strong impact on the stock returns: In more than half of the days immediately after extreme rain events that occurred between 2.28.2005 and 12.30.2014, returns were significantly low, causing average daily losses of 1.97%. These results point to the need for more accurate financial management to hedge against weather risk
    Date: 2017–08
  8. By: Gollier, Christian
    Abstract: Suppose that the decision-maker is uncertain about the variance of the payoff of a gamble, and that this uncertainty comes from not knowing the number of zero-mean i.i.d. risks attached to the gamble. In this context, we show that any n-th degree increase in this variance risk reduces expected utility if and only if the sign of the 2n-th derivative of the utility function u is (-1)n+1. Moreover, increasing the statistical concordance between the mean payoff of the gamble and the n-th degree riskiness of its variance reduces expected utility if and only if the sign of the 2n + 1 derivative of u is (-1)n+1. These results generalize the theory of risk apportionment developed by Eeckhoudt and Schlesinger (2006), and is useful to better understand the impact of stochastic volatility on welfare and asset prices.
    Keywords: Long-run risk; stochastic dominance; prudence; temperance; stochastic volatility; risk apportionment.
    JEL: D81
    Date: 2017–07
  9. By: Qiang Ji (Center for Energy and Environmental Policy research, Institutes of Science and Development, Chinese Academy of Sciences and School of Public Policy and Management, University of Chinese Academy of Sciences, Beijing, China); Bing-Yue Liu (Center for Energy and Environmental Policy research, Institutes of Science and Development, Chinese Academy of Sciences and Department of Statistics and Finance, University of Science and Technology of China, Hefei, China); Juncal Cunado (University of Navarra, School of Economics, Edificio Amigos, E-31080 Pamplona, Spain); Rangan Gupta (Department of Economics, University of Pretoria, Pretoria, South Africa)
    Abstract: This paper analyses the risk spillover effect between the US stock market and the remaining G7 stock markets by measuring the conditional Value-at-Risk (CoVaR) using time-varying copula models with Markov switching and data that covers more than 100 years. The main results suggest that the dependence structure varies with time and has distinct high and low dependence regimes. Our findings verify the existence of risk spillover between the US stock market and the remaining G7 stock markets. Furthermore, the results imply the following: 1) abnormal spikes of dynamic CoVaR were induced by well-known historical economic shocks; 2) The value of upside risk spillover is significantly larger than the downside risk spillover and 3) The magnitudes of risk spillover from the remaining G7 countries to the US are significantly larger than that from the US to these countries.
    Keywords: Time-varying copula, Markov switching, CoVaR, risk spillover, G7 stock markets
    JEL: C21 G32 G38
    Date: 2017–08
  10. By: Guo, Zi-Yi
    Abstract: We introduce a new type of heavy-tailed distribution, the normal reciprocal inverse Gaussian distribution (NRIG), to the GARCH and Glosten-Jagannathan-Runkle (1993) GARCH models, and compare its empirical performance with two other popular types of heavy-tailed distribution, the Student’s t distribution and the normal inverse Gaussian distribution (NIG), using a variety of asset return series. Our results illustrate that there is no overwhelmingly dominant distribution in fitting the data under the GARCH framework, although the NRIG distribution performs slightly better than the other two types of distribution. For market indexes series, it is important to introduce both GJR-terms and the NRIG distribution to improve the models’ performance, but it is ambiguous for individual stock prices series. Our results also show the GJR-GARCH NRIG model has practical advantages in quantitative risk management. Finally, the convergence of numerical solutions in maximum-likelihood estimation of GARCH and GJR-GARCH models with the three types of heavy-tailed distribution is investigated.
    Keywords: Heavy-tailed distribution,GARCH model,Model comparison,Numerical solution
    Date: 2017
  11. By: Tracey, Belinda (Bank of England); Schnittker, Christian (Bank of England); Sowerbutts, Rhiannon (Bank of England)
    Abstract: We use provisions for misconduct issues as an instrumental variable to identify the causal effect of bank capital on risk-taking. Misconduct provisions can adversely affect bank capital via their negative impact on retained earnings, and we find evidence of this for UK banks. We also find strong support for our assumption that misconduct provisions are otherwise unrelated to risk-taking. We facilitate our analysis with a new UK panel dataset of bank-level information including misconduct provisions, merged with loan-level data on all regulated UK mortgages. Our main finding is that a negative bank capital shock leads to an increase in risk-taking.
    Keywords: Banking; risk-taking; capital shocks; 2SLS
    JEL: G21 G28
    Date: 2017–08–18
  12. By: Xiong, Wanting; Wang, Yougui
    Abstract: Recent evidences provoke broad rethinking of the role of banks in money creation. The authors argue that apart from the reserve requirement, prudential regulations also play important roles in constraining the money supply. Specifically, they study three Basel III regulations and theoretically analyze their standalone and collective impacts. The authors find that 1) the money multiplier under Basel III is not constant but a decreasing function of the monetary base; 2) the determinants of the bank's money creation capacity are regulation-specific; 3) the effective binding regulation and the corresponding money multiplier vary across different economic states and bank balance sheet conditions.
    Keywords: money creation,Basel III,liquidity coverage ratio,capital adequacy ratio,leverage ratio,money multiplier
    JEL: E51 G28 G18 E60
    Date: 2017
  13. By: Roxana Dumitrescu; Romuald Elie; Wissal Sabbagh; Chao Zhou
    Abstract: We introduce a new class of \textit{Backward Stochastic Differential Equations with weak reflections} whose solution $(Y,Z)$ satisfies the weak constraint $\textbf{E}[\Psi(\theta,Y_\theta)] \geq m,$ for all stopping time $\theta$ taking values between $0$ and a terminal time $T$, where $\Psi$ is a random non-decreasing map and $m$ a given threshold. We study the wellposedness of such equations and show that the family of minimal time $t$-values $Y_t$ can be aggregated by a right-continuous process. We give a nonlinear Mertens type decomposition for lower reflected $g$-submartingales, which to the best of our knowledge, represents a new result in the literature. Using this decomposition, we obtain a representation of the minimal time $t$-values process. We also show that the minimal supersolution of a such equation can be written as a \textit{stochastic control/optimal stopping game}, which is shown to admit, under appropriate assumptions, a value and saddle points. From a financial point of view, this problem is related to the approximative hedging for American options.
    Date: 2017–08
  14. By: Mohammed Ali, Khalifa (The Islamic Research and Teaching Institute (IRTI))
    Abstract: Recently the issue of the real exchange rate management has received renewed attention from prominent development economist in leading universities and development intuitions. Example of some of the recent work include Gala (2007), Eichengreen (2007), Prasad et al. (2006) and Rodrik (2009). The main theme of this recent research is the importance of managing the real exchange rate as growth facilitating factor. Research on this area has shown that both the level and the volatility of the real exchange rate have important impact on exports, investment and growth in developing countries. This study uses a new large data set for the real effective exchange rate for estimating real exchange rate over/under valuation for member countries. The study also discusses the implication of the results on member countries of the Islamic Development Bank Group
    Keywords: Risk Management Practices; Islamic banking; Nigeria; Malaysia
    JEL: G20 G21 G28
    Date: 2017–02–20

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