nep-rmg New Economics Papers
on Risk Management
Issue of 2017‒02‒12
fifteen papers chosen by

  1. Tail event driven networks of SIFIs By Cathy Yi-Hsuan Chen; Wolfgang Karl Härdle; Yarema Okhrin;
  2. Computing the aggregate loss distribution based on numerical inversion of the compound empirical characteristic function of frequency and severity By Viktor Witkovsky; Gejza Wimmer; Tomas Duby
  3. Investment Fund Risk: The Tale in the Tails By Shaw, Frances; Dunne, Peter G.
  4. S&P 500 Index, an Option Implied Risk Analysis By Giovanni Barone-Adesi; Chiara Legnazzi; Carlo Sala
  5. Market liquidity, closeout procedures and initial margin for CCPs By Cerezetti, Fernando; Sumawong, Anannit; Karimalis, Emmanouil; Shreyas, Ujwal
  6. Higher and More Stable Returns From Cottonseed By Regmund, Wes; Robinson, John; Anderson, David
  7. Existence, uniqueness, and stability of optimal portfolios of eligible assets By Michel Baes; Pablo Koch-Medina; Cosimo Munari
  8. A novel multivariate risk measure: the Kendall VaR By Matthieu Garcin; Dominique Guegan; Bertrand Hassani
  9. Systemic Risk in Europe By Robert F. Engle; Eric Jondeau; Michael Rockinger
  10. WTI Crude Oil Option-Implied VaR and CVaR: An Empirical Application By Giovanni Barone-Adesi; Chiara Legnazzi; Carlo Sala
  11. Dependent Defaults and Losses with Factor Copula Models By Damien Ackerer; Thibault Vatter
  12. Firm-Related Risk and Precautionary Saving Response By Fagereng, Andreas; Guiso, Luigi; Pistaferri, Luigi
  13. Ways to improve risk management at the enterprises of the energy sector By Elena Tkach; Grigoriy Khavanskiy
  14. Bank Ratings: What Determines Their Quality? By Harald Hau; Sam Langfield; David Marques-Ibanez
  15. “Resolution of optimization problems and construction of efficient portfolios: An application to the Euro Stoxx 50 index" By Víctor Adame-García; Fernando Fernández-Rodríguez; Simón Sosvilla-Rivero

  1. By: Cathy Yi-Hsuan Chen; Wolfgang Karl Härdle; Yarema Okhrin;
    Abstract: The interdependence, dynamics and riskiness of financial institutions are the key features frequently tackled in financial econometrics. We propose a Tail Event driven Network Quantile Regression (TENQR) model which addresses these three aspects. More precisely, our framework captures the risk propagation and dynamics in terms of a quantile (or expectile) autoregression involving network effects quantified through an adjacency matrix. To reflect the nature and risk content of systemic risk, the construction of the adjacency matrix is suggested to include tail event covariates. The model is evaluated using the SIFIs (systemically important financial institutions) identified by the Financial Stability Board (FSB) as main players in the global financial system. The risk decomposition analysis of it identifies the systemic importance of SIFIs and thus provides measures for the required level of additional loss absorbency. It is discovered that the network effect, as a function of the tail probability, becomes more profound in stress situations and brings the various impacts to the SIFIs located in different geographic regions.
    Keywords: systemic risk; network analysis; network autoregression
    JEL: C01 C14 C58 C45 G01 G15 G31
    Date: 2017–01
  2. By: Viktor Witkovsky; Gejza Wimmer; Tomas Duby
    Abstract: A non-parametric method for evaluation of the aggregate loss distribution (ALD) by combining and numerically inverting the empirical characteristic functions (CFs) is presented and illustrated. This approach to evaluate ALD is based on purely non-parametric considerations, i.e., based on the empirical CFs of frequency and severity of the claims in the actuarial risk applications. This approach can be, however, naturally generalized to a more complex semi-parametric modeling approach, e.g., by incorporating the generalized Pareto distribution fit of the severity distribution heavy tails, and/or by considering the weighted mixture of the parametric CFs (used to model the expert knowledge) and the empirical CFs (used to incorporate the knowledge based on the historical data - internal and/or external). Here we present a simple and yet efficient method and algorithms for numerical inversion of the CF, suitable for evaluation of the ALDs and the associated measures of interest important for applications, as, e.g., the value at risk (VaR). The presented approach is based on combination of the Gil-Pelaez inversion formulae for deriving the probability distribution (PDF and CDF) from the compound (empirical) CF and the trapezoidal rule used for numerical integration. The applicability of the suggested approach is illustrated by analysis of a well know insurance dataset, the Danish fire loss data.
    Date: 2017–01
  3. By: Shaw, Frances (Central Bank of Ireland); Dunne, Peter G. (Central Bank of Ireland)
    Abstract: Efforts to develop risk assessment metrics for the non-bank financial sector have been given impetus following the post-crisis broadening of the IMF's Financial Stability Assessments and recent efforts by the Financial Stability Board to address structural vulnerabilities from asset management activities. Using a novel database of investment funds reporting in Ireland, we employ Marginal Expected Shortfall metrics to capture investment fund exposures to pervasive industry-wide tail events. We reveal the primary fund sectors most responsible for widespread extreme return shortfalls. Fund attributes are then used to explain (mostly) the cross-sectional variation in marginal expected shortfall using panel regression techniques. We find that leverage, derivative usage, redemption rates, cash holdings, openness and retail investor focus are important factors that consistently explain the variation in fund-specific sensitivity to pervasive tail risk. Finally, we provide new evidence that ex ante exposure to pervasive extreme negative returns explains significantly more of the risk premium implicit in ex post returns than traditional beta.
    Keywords: Investment Funds, systemic risk, marginal expected shortfall.
    JEL: G15 G23 G28
    Date: 2017–01
  4. By: Giovanni Barone-Adesi (Swiss Finance Institute); Chiara Legnazzi (Swiss Finance Institute); Carlo Sala (ESADE Business School)
    Abstract: The forward looking nature of option prices provides a natural model-free way to extract different risk measures. Not relying on any distributional assumptions, the option implied VaR and CVaR are naturally back testable risk measures where the elicitability requirement is no longer an issue. Tested on the 2005-2015 S&P 500 Index and options data and placing a focus on the financial crisis, the obtained results appear to be superior with respect to the classical risk measures. This is especially true in periods of high volatility, where a proper risk estimation is needed the most.
    Keywords: Option Prices, Risk Measures, VaR and CvaR, Elicitability, S&P 500 Index
    JEL: G13 G17
  5. By: Cerezetti, Fernando (Bank of England); Sumawong, Anannit (University of Sussex); Karimalis, Emmanouil (Bank of England); Shreyas, Ujwal (Bank of England)
    Abstract: Closeout procedures enable central counterparties (CCPs) to respond to events that challenge the continuity of their normal operations, most frequently triggered by the default of one or more clearing members. The procedures ensure the regularity of the settlement process through the prudent and orderly closeout of the defaulter’s portfolio. Traditional approaches to CCPs’ margin requirements typically assume a simple closeout profile, and do not account for the ‘real-life’ constraints embedded on the management of a default. The paper proposes an approach of evaluating how distinct closeout strategies may expose a CCP to different sets of risk and costs, and consequently could impact the sufficiency of financial resources to cover its risk exposure to a default. The approach is based on a counterfactual simulation, and evaluates a full spectrum of hedging strategies in an exploratory and model-free manner, deriving endogenous and market-dependent risk metrics. Using the trade repository data available to the Bank (as a result of EMIR reporting) on over-the-counter (OTC) interest rate swaps (IRS) and ten years (ie 2005 to 2015) of information on related market risk factors, the paper derives empirically an efficient hedging strategy that minimizes the CCP’s risk exposure to a defaulting clearing member. Endogenous trade-off structures between total risk (market risk plus funding needs) and transaction costs are also established, with marginal sensitivities to individual components of the hedging strategy determined.
    Keywords: CCPs; market liquidity; closeout procedures; initial margin
    JEL: C61 G20 G28 G32
    Date: 2017–02–06
  6. By: Regmund, Wes; Robinson, John; Anderson, David
    Abstract: Price variability is a significant source of risk in the market for whole cottonseed. Conventional risk management practices for similar commodities consist of longer term storage, forward contracting, and hedging using futures markets as a means to combat unfavorable price movements. However, no futures market currently exists for cottonseed, limiting users and growers in their marketing planning and approaches for risk reduction. The purpose of this study is examine cottonseed supply and usage patterns within Texas and to analyze the feasibility of price risk management strategies by cross hedging cash cottonseed with soybean and soybean meal futures. Results from a survey disseminated to Texas gins gave credibility to the idea that finding an alternative method to managing price risk would be economically beneficial. The relationship between cash and futures prices are deemed to be significant enough to warrant further investigation and hedge ratios allowing for the proper risk coverage for a seller of seed are estimated. Additionally, a measurement of hedge effectiveness is considered and results in cross hedges using either soybean or soybean meal contracts reasonably reducing risk when compared to an unhedged position. Practical testing from a seller’s perspective using historical data produced outcomes that showed that net effective prices from cross hedging are typically higher than unhedged cash prices over the considered time period. This presents an additional potential outlet for cotton gins to market cottonseed aside from the traditional methods, and possibly improve their financial position and profitability. The strategies analyzed will conceivably allow growers, gins, oil mills, and livestock feeders to reduce price risk and uncertainty and aid in financial decisions.
    Keywords: cottonseed, hedging, Crop Production/Industries, Marketing,
  7. By: Michel Baes; Pablo Koch-Medina; Cosimo Munari
    Abstract: We study the existence of portfolios of traded assets making a given financial institution pass some pre-specified (internal or external) regulatory test. In particular, we are interested in the existence of optimal portfolios, i.e. portfolios that allow to pass the test at the lowest cost, and in their sensitivity to changes in the underlying capital position. This naturally leads to investigate the continuity properties of the set-valued map associating to each capital position the corresponding set of optimal portfolios. We pay special attention to inner semicontinuity, which is the key continuity property from a financial perspective. This property is always satisfied if the test is based on a polyhedral risk measure such as Expected Shortfall, but it generally fails, even in a convex world, if we depart from polyhedrality. In this case, the optimal portfolio map may even fail to admit a continuous selection. Our results have applications to capital adequacy, pricing and hedging, and capital allocation. In particular, we allow for regulatory tests designed to capture systemic risk.
    Date: 2017–02
  8. By: Matthieu Garcin (Natixis Asset Management and LabEx ReFi); Dominique Guegan (Centre d'Economie de la Sorbonne and LabEx ReFi); Bertrand Hassani (Grupo Santander and Centre d'Economie de la Sorbonne and LabEx ReFi)
    Abstract: The definition of multivariate Value at Risk is a challenging problem, whose most common solutions are given by the lower- and upper-orthant VaRs, which are based on copulas: the lower-orthant VaR is indeed the quantile of the multivariate distribution function, whereas the upper-orthant VaR is the quantile of the multivariate survival function. In this paper we introduce a new approach introducing a total-order multivariate Value at Risk, referred to as the Kendall Value at Risk, which links the copula approach to an alternative definition of multivariate quantiles, known as the quantile surface, which is not used in finance, to our knowledge. We more precisely transform the notion of orthant VaR thanks to the Kendall function so as to get a multivariate VaR with some advantageous properties compared to the standard orthant VaR: it is based on a total order and, for a non-atomic and Rd-supported density function, there is no distinction anymore between the d-dimensional VaRs based on the distribution function or on the survival function. We quantify the differences between this new kendall VaR and orthant VaRs. In particular, we show that the Kendall VaR is less (respectively more) conservative than the lower-orthant (resp. upper-orthant) VaR. The definition and the properties of the Kendall VaR are illustrated using Gumbel and Clayton copulas with lognormal marginal distributions and several levels of risk
    Keywords: Value at Risk; multivariate quantile; risk measure; Kendall function; copula; total order
    JEL: C1 C6
    Date: 2017–01
  9. By: Robert F. Engle (New York University, New York University (NYU), and National Bureau of Economic Research (NBER)); Eric Jondeau (University of Lausanne and Swiss Finance Institute); Michael Rockinger (University of Lausanne, Centre for Economic Policy Research (CEPR), and Swiss Finance Institute)
    Abstract: Systemic risk may be defined as the propensity of a financial institution to be undercapitalized when the financial system as a whole is undercapitalized. In this paper, we investigate the case of non-U.S. institutions, with several factors explaining the dynamics of financial firms returns and with asynchronicity of time zones. We apply this methodology to the 196 largest European financial firms and estimate their systemic risk over the 2000-2012 period. We find that, for certain countries, the cost for the taxpayer to rescue the riskiest domestic banks is so high that some banks might be considered too big to be saved.
    Keywords: Systemic Risk, Marginal Expected Shortfall, Multi-factor Model
    JEL: C32 G01 G20 G28 G32
  10. By: Giovanni Barone-Adesi (Swiss Finance Institute); Chiara Legnazzi (Swiss Finance Institute); Carlo Sala (ESADE Business School)
    Abstract: The forward-looking structure of option market prices provides a natural model-free way to extract different risk measures. We extract the 2014-2015 daily option implied VaR and CVaR from the WTI crude oil future prices and the options written on it. Without relying neither on numerical simulations nor on distributional assumptions, we propose a forward-looking risk measure that is both coherent and backtestable. Working naturally at longer-than-usual time horizons, the risk that the risk could change is no longer an issue. From a forecasting viewpoint, the ratio of the two risk measures allows to predict the probability density of jumps in the underlying price, which would have been otherwise unpredictable a priori with standard inference models.
    Keywords: Option Prices, Risk Measures, VaR and CVaR, Elicitability
    JEL: G13 G17
  11. By: Damien Ackerer (Ecole Polytechnique Fédérale de Lausanne and Swiss Finance Institute); Thibault Vatter (Ecole Polytechnique Fédérale de Lausanne and University of Lausanne)
    Abstract: We introduce a class of flexible and tractable static factor models for the joint term structure of default probabilities, the factor copula models. These high dimensional models remain parsimonious with pair copula constructions, and nest numerous standard models as special cases. With finitely supported random losses, the loss distributions of credit portfolios and derivatives can be exactly and efficiently computed. Numerical examples on collateral debt obligation (CDO), CDO squared, and credit index swaption illustrate the versatility of our framework. An empirical exercise shows that a simple model specification can fit credit index tranche prices.
    Keywords: credit portfolio, credit derivatives, discrete Fourier transform, factor copula, random loss, survival models
    JEL: C10 G12 G13
  12. By: Fagereng, Andreas; Guiso, Luigi; Pistaferri, Luigi
    Abstract: We propose a new approach to identify the strength of the precautionary motive and the extent of self-insurance in response to earnings risk based on Euler equation estimates. To address endogeneity problems, we use Norwegian administrative data and instrument consumption and earnings volatility with the variance of firm-specific shocks. The instrument is valid because firms pass some of their productivity shocks onto wages; moreover, for most workers firm shocks are hard to avoid. Our estimates suggest a coefficient of relative prudence of 2, in a very plausible range.
    Keywords: firm shocks; precautionary savings; self-insurance
    Date: 2017–01
  13. By: Elena Tkach (Russian Presidential Academy of National Economy and Public Administration, Chelyabinsk branch); Grigoriy Khavanskiy (Chelyabinsk State University)
    Abstract: The article highlights the main problems of managing risks in native energetics, considers possible ways of solving diagnosed problems, studies causes making modern enterprises of the energy sector search the most appropriate ways to minimize and even risks. In conclusion the authors suggest a number of measures aimed at improving risk management in the context of higher volatility of world energetic markets
    Keywords: risk management, energetic company, analysis of risks, risk-management
    JEL: L0
    Date: 2015–11
  14. By: Harald Hau (University of Geneva, Swiss Finance Institute, Centre for Economic Policy Research (CEPR), and CESifo (Center for Economic Studies and Ifo Institute)); Sam Langfield (European Central Bank - European Systemic Risk Board Secretariat); David Marques-Ibanez (European Central Bank (ECB))
    Abstract: This paper examines the quality of credit ratings assigned to banks in Europe and the United States by the three largest rating agencies over the past two decades. We interpret credit ratings as relative assessments of creditworthiness, and define a new ordinal metric of rating error based on banks’ expected default frequencies. Our results suggest that rating agencies assign more positive ratings to large banks and to those institutions more likely to provide the rating agency with additional securities rating business (as indicated by private structured credit origination activity). These competitive distortions are economically significant and help perpetuate the existence of ‘too-big-to-fail’ banks. We also show that, overall, differential risk weights recommended by the Basel accords for investment grade banks bear no significant relationship to empirical default probabilities.
    Keywords: Rating Agencies, Credit Ratings, Conflicts of Interest, Prudential Regulation
    JEL: G21 G23 G28
  15. By: Víctor Adame-García (Universidad Complutense de Madrid, Campus de Somosaguas, 28223 Madrid, Spain.); Fernando Fernández-Rodríguez (Universidad de Las Palmas de Gran Canaria, Campus de Tafira, 35017 Las Palmas de Gran Canaria, Spain.); Simón Sosvilla-Rivero (Complutense Institute for International Studies, Universidad Complutense de Madrid, Campus de Somosaguas, 28223 Madrid, Spain.)
    Abstract: We assess the effectiveness of various portfolio optimization strategies (only long allocations) applied to the components of the Euro Stoxx 50 index during the period 2002-2015. The sample under study contemplates episodes of high volatility and instability in financial markets, such as the Global Financial Crisis and the European Debt Crisis. This implies a real challenge in portfolio optimization strategies, since all the methodologies used are restricted to the assignment of positive weights. We use the daily returns for the asset allocation with a three year estimation window, keeping the assets in portfolio for one year.In the context of strategies with short-selling constraints, we contribute to the debate on whether naive diversification proves to be an effective alternative for the construction of the portfolio, as opposed to the portfolio optimization models. To that end, we analyse the out-of-sample performance of 16 strategies for the selection of assets and weights in the main stock index of the euro area. Our results suggest that a large number of strategies outperform both the naive strategy and the Euro Stoxx 50 index in terms of the profitability and Sharpe's ratio. Furthermore, the portfolio strategy based on the maximization of the diversification ratio provides the highest return and the classical strategy of mean-variance renders the highest Sharpe ratio, which is statistically different from the Euro Stoxx 50 index in the period under study.
    Keywords: Optimization problems; portfolio choice; investment decisions; asset allocation;econometrics; minimum-variance portfolios; robust statistics; out-of-sample performance. JEL classification:C14, C61, G11.
    Date: 2017–02

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