nep-rmg New Economics Papers
on Risk Management
Issue of 2014‒03‒08
twelve papers chosen by
Stan Miles
Thompson Rivers University

  1. Stress Testing Engineering: the real risk measurement? By Dominique Guegan; Bertrand Hassani
  2. On bank credit risk: systemic or bank-specific? Evidence from the US and UK By Junye Li; Gabriele Zinna
  3. Banks’ Loan Screening Incentives with Credit Risk Transfer: An Alternative to Risk Retention By Arnold, Marc
  4. Ailing Mothers, Healthy Daughters? Contagion in the Central European Banking Sector By Tomas Fiala; Tomas Havranek
  5. Disentangling Systematic and Idiosyncratic Dynamics in Panels of Volatility Measures By Matteo Barigozzi; Christian T. Brownlees; Giampiero M. Gallo; David Veredas
  6. Performance of Utility Based Hedges By John Cotter; Jim Hanly
  7. Positive Semidefinite Integrated Covariance Estimation, Factorizations and Asynchronicity By Kris Boudt; Sébastien Laurent; Asger Lunde; Rogier Quaedvlieg
  8. "Volatility and Quantile Forecasts by Realized Stochastic Volatility Models with Generalized Hyperbolic Distribution" By Makoto Takahashi; Toshiaki Watanabe; Yasuhiro Omori
  9. The Benefits of Intrastate and Interstate Geographic Diversification in Banking By Céline Meslier; Donald P. Morgan; Katherine Somolyk; Amine Tarazi
  10. Are hedge funds uncorrelated with financial markets? An empirical assessment By Khaled Guesmi; Saoussen Jebri; Abdelkarim Jabri; Frédéric Teulon
  11. Statistics of Heteroscedastic Extremes By Einmahl, J.H.J.; Haan, L.F.M. de; Zhou, C.
  12. Forecasting Realized Volatility with Changes of Regimes By Giampiero M. Gallo; Edoardo Otranto

  1. By: Dominique Guegan (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Paris 1 - Panthéon-Sorbonne); Bertrand Hassani (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Paris 1 - Panthéon-Sorbonne)
    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
  2. By: Junye Li (ESSEC Business School); Gabriele Zinna (Bank of Italy)
    Abstract: We develop a multivariate credit risk model that accounts for joint defaults of banks and al-lows us to disentangle how much of banks' credit risk is systemic. We find that the US and UK dif-fer not only in the evolution of systemic risk, but in particular in their banks' systemic exposures. In both countries, however, systemic credit risk varies substantially, represents about half of total bank credit risk on average, and induces high risk premia. Further, the results suggest that sovereign and bank systemic risk are particularly interlinked in the UK.
    Keywords: systemic bank credit Risk, credit default swaps, distress risk premia, Bayesian estimation
    JEL: F34 G12 G15
    Date: 2014–02
  3. By: Arnold, Marc
    Abstract: This article analyzes the impact of credit risk transfer on banks' screening incentives on the primary loan market. While credit derivatives allow banks to transfer risk to investors, they negatively affect the incentive to screen due to the asymmetry of information between banks and investors. I show that screening incentives can be reestablished with standardized credit derivatives that fully transfer the underlying loan default risk. In particular, a callable credit default swap reveals a loan's quality to the investor by letting him observe the bank's readiness to pay for the implicit call feature. The ability to signal loan quality induces screening incentives. The paper also examines the impact of current developments such as higher regulatory capital standards, stricter margin requirements, and central clearing on the design of the optimal credit risk transfer contract.
    Keywords: Credit Risk Transfer, Callable Credit Default Swaps, Screening Incentives
    JEL: G18 G28
  4. By: Tomas Fiala; Tomas Havranek
    Abstract: Foreign-dominated banking sectors, such as those prevalent in Central and Eastern Europe, are susceptible to two major sources of systemic risk: (i) linkages between local banks and (ii) linkages between a foreign mother bank and its local subsidiary. Using a nonparametric method based on extreme value theory, which accounts for fat-tail shocks, we analyze inter- dependencies in downward risk in the banking sector of the Czech Republic, Hungary, Poland, and Slovakia during 1994-2013. In contrast to the pre- sumptions of the current regulatory policy of these countries, we find that the risk of contagion from a foreign mother bank to its local subsidiary is substantially smaller than the risk between two local banks.
    Keywords: systemic risk, extreme value theory, financial stability, Central Eastern Europe, banking, parent-subsidiary relationship
    JEL: F23 F36 G01 G21
    Date: 2014–01–01
  5. By: Matteo Barigozzi (London School of Economics and Political Science – Department of Statistics); Christian T. Brownlees (Universitat Pompeu Fabra – Department of Economics and Business & Barcelona GSE); Giampiero M. Gallo (Dipartimento di Statistica, Informatica, Applicazioni "G.Parenti", Università di Firenze); David Veredas (ECARES – Solvay Brussels School of Economics and Management – Université libre de Bruxelles)
    Abstract: Realized volatilities measured on several assets exhibit a common secular trend and some idiosyncratic pattern. We accommodate such an empirical regularity extending the class of Multiplicative Error Models (MEMs) to a model where the common trend is estimated nonparametrically while the idiosyncratic dynamics are assumed to follow univariate MEMs. Estimation theory based on seminonparametric methods is developed for this class of models for large cross-sections and large time dimensions. The methodology is illustrated using two panels of realized volatility measures between 2001 and 2008: the SPDR Sectoral Indices of the S&P500 and the constituents of the S&P100. Results show that the shape of the common volatility trend captures the overall level of risk in the market and that the idiosyncratic dynamics have an heterogeneous degree of persistence around the trend. An out–of–sample forecasting exercise shows that the proposed methodology improves volatility prediction over a number of benchmark specifications.
    Keywords: Vector Multiplicative Error Model, Seminonparametric Estimation, Volatility.
    JEL: C32 C51 G01
    Date: 2014–02
  6. By: John Cotter (UCD School of Business, University College Dublin); Jim Hanly (UCD School of Business, University College Dublin)
    Abstract: Hedgers as investors are concerned with both risk and return; however the literature has generally neglected the role of both returns and investor risk aversion by its focus on minimum variance hedging. In this paper we address this by using utility based performance metrics to evaluate the hedging effectiveness of utility based hedges for hedgers with both moderate and high risk aversion together with the more traditional minimum variance approach. We apply our approach to two asset classes, equity and energy, for three different hedging horizons, daily,weekly and monthly. We find significant differences between the minimum variance and utility based hedges and their attendant performance in-sample for all frequencies. However out of sample performance differences persist for the monthly frequency only.
    Keywords: Energy, Hedging Performance; Utility, Risk Aversion
    JEL: G10 G12 G15
    Date: 2014–02–19
  7. By: Kris Boudt (Department of Business, Vrije Universiteit Brussel, Belgium and VU University Amsterdam, Netherlands); Sébastien Laurent (Aix-Marseille University, Aix-Marseille School of Economics, CNRS & EHESS, France); Asger Lunde (Aarhus University and CREATES); Rogier Quaedvlieg (Department of Finance, Maastricht University, Netherlands)
    Abstract: An estimator of the ex-post covariation of log-prices under asynchronicity and microstructure noise is proposed. It uses the Cholesky factorization on the correlation matrix in order to exploit the heterogeneity in trading intensity to estimate the different parameters sequentially with as many observations as possible. The estimator is guaranteed positive semidefinite. Monte Carlo simulations confirm good finite sample properties. In the application we forecast portfolio Value-at-Risk and sector risk exposures for a portfolio of 52 stocks. We find that forecasts obtained from dynamic models utilizing the proposed high-frequency estimator provide statistically and economically superior forecasts to models using daily returns.
    Keywords: Cholesky decomposition, Integrated covariance, Non-synchronous trading, Positive semidefinite, Realized covariance
    JEL: C10 C58
    Date: 2014–02–24
  8. By: Makoto Takahashi (Center for the Study of Finance and Insurance, Osaka University and Department of Finance, Kellogg School of Management, Northwestern University); Toshiaki Watanabe (Institute of Economic Research, Hitotsubashi University); Yasuhiro Omori (Faculty of Economics, The University of Tokyo)
    Abstract:    The realized stochastic volatility model of Takahashi, Omori, and Watanabe (2009), which incorporates the asymmetric stochastic volatility model with the realized volatility, is extended with more general form of bias correction in realized volatility and wider class distribution, the generalized hyperbolic skew Student's t -distribution, fornancial returns. The extensions make it possible to adjust the bias due to the market microstructure noise and non-trading hours, which possibly depends on the level of the volatility, and to consider the heavy tail and skewness in nancial returns. With the Bayesian estimation scheme via Markov chain Monte Carlo method, the model enables us to estimate the parameters in the return distribution and in the model jointly. It also makes it possible to forecast volatility and return quantiles by sampling from their posterior distributions jointly. The model is applied to quantile forecasts of nancial returns such as value-at-risk and expected shortfall as well as volatility forecasts and those forecasts are evaluated by several backtesting procedures. Empirical results with SPDR, the S&P 500 exchange-traded fund, show that the heavy tail and skewness of daily returns are important for the model fit and the quantile forecasts but not for the volatility forecasts, and that the additional bias correction improves the quantile forecasts but does not substantially improve the model fit nor the volatility forecasts.
    Date: 2014–02
  9. By: Céline Meslier (LAPE - Laboratoire d'Analyse et de Prospective Economique - Université de Limoges : EA1088 - Institut Sciences de l'Homme et de la Société); Donald P. Morgan (Federal Reserve Bank of New-York - Federal Reserve Bank of New-York); Katherine Somolyk (Consumer Financial Protection Bureau - Consumer Financial Protection Bureau); Amine Tarazi (LAPE - Laboratoire d'Analyse et de Prospective Economique - Université de Limoges : EA1088 - Institut Sciences de l'Homme et de la Société)
    Abstract: We estimate the benefits of intrastate and interstate geographic diversification for bank risk and return, and assess whether such benefits could be shaped by differences in bank size and disparities in economic conditions within states or across U.S. states. For small banks, only intrastate diversification is beneficial in terms of risk-adjusted returns but for very large institutions both intrastate and intrastate expansions are rewarding. However, in all cases the relationship is hump-shaped for both intrastate and interstate diversification indicating limits for banks of all size. Moreover, while our results indicate that the average 'very large' bank has already reached its optimal diversification level, the average 'small bank' could still benefit in terms of risk-adjusted returns from further geographic diversification. Higher economic disparity as measured by the dispersion in unemployment rates either across counties or states impacts the benefits of diversification. At initially low levels of diversification, moving to other markets with dissimilar economic conditions lowers the added value of diversification but it becomes more beneficial at higher diversification levels.
    Keywords: Bank Holding Company; Geographic Diversification; Intrastate and interstate disparities in economic activity; Bank risk and return
    Date: 2014–02–21
  10. By: Khaled Guesmi; Saoussen Jebri; Abdelkarim Jabri; Frédéric Teulon
    Abstract: In this paper, we examine the correlations between hedge fund strategy indices and asset classes. Based on the Dynamic Conditional Correlation (DCC) GARCH Model, we estimate the correlations between hedge fund, stock, and bond indices during bull and bear markets. The results reveal that there are significant correlations between hedge funds and the stock market, especially during the recent financial crisis that took place from 2007 to 2009.
    Keywords: Hedge funds, Stock market.
    Date: 2014–02–25
  11. By: Einmahl, J.H.J.; Haan, L.F.M. de; Zhou, C. (Tilburg University, Center for Economic Research)
    Abstract: Abstract: We extend classical extreme value theory to non-identically distributed observations. When the distribution tails are proportional much of extreme value statistics remains valid. The proportionality function for the tails can be estimated nonparametrically along with the (common) extreme value index. Joint asymptotic normality of both estimators is shown; they are asymptotically independent. We develop tests for the proportionality function and for the validity of the model. We show through simulations the good performance of tests for tail homoscedasticity. The results are applied to stock market returns. A main tool is the weak convergence of a weighted sequential tail empirical process.
    Date: 2014
  12. By: Giampiero M. Gallo (Dipartimento di Statistica, Informatica, Applicazioni "G.Parenti", Università di Firenze); Edoardo Otranto (Dipartimento di Scienze Cognitive e della Formazione, Università degli Studi di Messina)
    Abstract: Realized volatility of financial time series generally shows a slow–moving average level from the early 2000s to recent times, with alternating periods of turmoil and quiet. Modeling such a pattern has been variously tackled in the literature with solutions spanning from long–memory, Markov switching and spline interpolation. In this paper, we explore the extension of Multiplicative Error Models to include a Markovian dynamics (MS-MEM). Such a model is able to capture some sudden changes in volatility following an abrupt crisis and to accommodate different dynamic responses within each regime. The model is applied to the realized volatility of the S&P500 index: next to an interesting interpretation of the regimes in terms of market events, the MS-MEM has better in–sample fitting capability and achieves good out–of–sample forecasting performances relative to alternative specifications.
    Keywords: MEM, regime switching, realized volatility, volatility persistence, volatility forecasting
    JEL: C22 C24 C58
    Date: 2014–02

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