nep-rmg New Economics Papers
on Risk Management
Issue of 2014‒05‒17
ten papers chosen by
Stan Miles
Thompson Rivers University

  1. Systemic Risk of Commercial Banks: A Markov-Switching Quantile Autoregression Approach By Liu, Xiaochun
  2. Distortion Risk Measures and Elicitability By Ruodu Wang; Johanna F. Ziegel
  3. Ailing Mothers, Healthy Daughters? Contagion in the Central European Banking Sector By Tomas Fiala; Tomas Havranek
  4. Risk management of savings accounts By Hana Dzmuranova; Petr Teply
  5. Systemic Event Prediction by Early Warning System By Diana Zigraiova; Petr Jakubik
  6. Risk Measurement and Risk Modelling Using Applications of Vine Copulas By David E. Allen; Michael McAleer; Abhay K. Singh
  7. Systemic Risk and Heterogeneous Leverage in Banking Network: Implications for Banking Regulation By Tolga Umut Kuzubas; Burak Saltoglu; Can Sever
  8. An Application of Correlation Clustering to Portfolio Diversification By Hannah Cheng Juan Zhan; William Rea; Alethea Rea
  9. Optimal stopping under model uncertainty: randomized stopping times approach By Denis Belomestny; Volker Kraetschmer
  10. The goodness-of-fit of the fuel-switching price using the mean-reverting Lévy jump process By Julien Chevallier; Stéphane Goutte

  1. By: Liu, Xiaochun
    Abstract: This paper extends the Conditional Value-at-Risk approach of Adrian and Brunnermeier (2011) by allowing systemic risk structures subject to economic regime shifts, which are governed by a discrete, latent Markov process. This proposed Markov-Switching Conditional Value-at-Risk is more suitable to Supervisory Stress Scenario required by FederalReserve Bank in conducting Comprehensive Capital Analysis and Review, since it is ca-pable of identifying the risk states in which the estimated risk levels are characterized. Applying MSCoVaR to stress-testing the U.S. largest commercial banks, this paper finds that the CoVaR approach underestimates systemic risk contributions of individual banks by around 131 basis points of asset loss on average. In addition, this paper constructs Banking Systemic Risk Index by value-weighted individual risk contributions for specifically monitoring the systemic risk of the banking system as a whole.
    Keywords: Markov-Switching Conditional Value-at-Risk, Conditional Expected Shortfall, Bayesian Quantile Inference, Stress-testing, Value-at-Risk, Commercial Banks, Banking Systemic Risk Index
    JEL: G1 G12 G17 G21
    Date: 2013–12–03
  2. By: Ruodu Wang; Johanna F. Ziegel
    Abstract: We discuss equivalent axiomatic characterizations of distortion risk measures, and give a novel and concise proof of the characterization of elicitable distortion risk measures. Elicitability has recently been discussed as a desirable criterion for risk measures, motivated by statistical considerations of forecasting. We reveal the mathematical conflict between the requirements of elicitability and comonotonic additivity which intuitively explains why only Value-at-Risk and the mean are elicitable distortion risk measures in a general sense.
    Date: 2014–05
  3. By: Tomas Fiala (Tilburg University and Institute of Economic Studies, Faculty of Social Sciences, Charles University, Prague, Czech Republic); Tomas Havranek (Institute of Economic Studies, Faculty of Social Sciences, Charles University, Prague, Czech Republic and Czech National Bank)
    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 par- ent bank and its local subsidiary. Using a nonparametric method based on extreme value theory, which accounts for fat-tail shocks, we analyze interde- pendencies in downward risk in the banking sectors 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 parent 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: 2014–04
  4. By: Hana Dzmuranova (Institute of Economic Studies, Faculty of Social Sciences, Charles University, Prague, Czech Republic); Petr Teply (Institute of Economic Studies, Faculty of Social Sciences, Charles University, Prague, Czech Republic and Department of Banking and Insurance Faculty of Finance and Accounting, University of Economics University of Economics, Prague)
    Abstract: This paper deals with the risk management of savings accounts. Savings accounts are non-maturing accounts bearing a relatively attractive rate of return and two embedded options: a customer’s option to withdraw money at any time and a bank’s option to set the deposit as it wishes. The risk management of saving accounts remains a big challenge for banks and simultaneously raises serious concerns by some regulators. In this paper, we focus on the interest rate risk management of savings accounts. By constructing the replicating portfolio and simulating six scenarios for the market rate and client rates, we show that under the severest scenario, some banks in the Czech Republic might face a capital shortage up to 22% in next two years if market rates start to increase dramatically. We conclude that savings accounts are risky instruments that cannot be hedged by standard risk mitigation techniques. Since savings accounts in the Czech Republic are not subject to any special regulation yet, we propose imposing stricter regulation and supervision (the Belgium framework might be an inspiring model to consider).
    Keywords: demand deposits, interest rate risk, replicating portfolio, risk management, savings accounts, simulations
    JEL: C15 G21 G11
    Date: 2014–04
  5. By: Diana Zigraiova (Czech National Bank and Institute of Economic Studies, Faculty of Social Sciences, Charles University, Prague, Czech Republic); Petr Jakubik (European Insurance and Occupational Pensions Authority (EIOPA) and Institute of Economic Studies, Faculty of Social Sciences, Charles University, Prague, Czech Republic)
    Abstract: This work develops an early warning system framework for assessing systemic risks and for predicting systemic events, i.e. periods of extreme financial instability with potential real costs, over the short horizon of six quarters and the long horizon of twelve quarters on the panel of 14 countries, both advanced and developing. First, we build Financial Stress Index to identify starting dates of systemic financial crises for each country in the panel. Second, early warning indicators for assessment and prediction of systemic risks are selected in a two-step approach; relevant prediction horizons for each indicator are found by the univariate logit model followed by the application of Bayesian model averaging method to identify the most useful indicators. Next, we validate early warning model, containing only useful indicators, for both horizons on the panel. Finally, the in-sample performance of the constructed EWS over both horizons is assessed for the Czech Republic. We find that the model over the 3 years’ horizon slightly outperforms the EWS with the horizon of 1.5 years on the Czech data. The long model attains the maximum utility in crises detection as well as it maximizes area under Receiver Operating Characteristics curve which measures the quality of the forecast.
    Keywords: Systemic risk, Financial stress, Financial crisis, Early warning indicators, Bayesian model averaging, Early warning system
    JEL: C33 E44 F47 G01
    Date: 2014–01
  6. By: David E. Allen; Michael McAleer (University of Canterbury); Abhay K. Singh
    Abstract: This paper features an application of Regular Vine copulas which are a novel and recently developed statistical and mathematical tool which can be applied in the assessment of composite financial risk. Copula-based dependence modelling is a popular tool in financial applications, but is usually applied to pairs of securities. By contrast, Vine copulas provide greater flexibility and permit the modelling of complex dependency patterns using the rich variety of bivariate copulas which may be arranged and analysed in a tree structure to explore multiple dependencies. The paper features the use of Regular Vine copulas in an analysis of the co-dependencies of 10 major European Stock Markets, as represented by individual market indices and the composite STOXX 50 index. The sample runs from 2005 to the end of 2011 to permit an exploration of how correlations change in different economic circumstances using three different sample periods: pre-GFC (Jan 2005- July 2007), GFC (July 2007-Sep 2009), and post-GFC periods (Sep 2009 - Dec 2011). The empirical results suggest that the dependencies change in a complex manner, and are subject to change in different economic circumstances. One of the attractions of this approach to risk modelling is the flexibility in the choice of distributions used to model co-dependencies. The practical application of Regular Vine metrics is demonstrated via an example of the calculation of the VaR of a portfolio made up of the indices.
    Keywords: Regular Vine Copulas, Tree structures, Co-dependence modelling, European stock markets
    JEL: G11 C02
    Date: 2014–05–08
  7. By: Tolga Umut Kuzubas; Burak Saltoglu; Can Sever
    Date: 2014–01
  8. By: Hannah Cheng Juan Zhan; William Rea (University of Canterbury); Alethea Rea
    Abstract: This paper presents a novel application of software developed for constructing a phylogenetic network to the correlation matrix for 126 stocks listed on the Shanghai A Stock Market. We show that by visualizing the correlation matrix using a Neighbor-Net network and using the circular ordering produced during the construction of the network we can reduce the risk of a diversified portfolio compared with random or industry group based selection methods in times of market increase.
    Keywords: Visualization, Neighbour-Nets, Correlation Matrix, Diversification
    JEL: G11
    Date: 2014–05–05
  9. By: Denis Belomestny; Volker Kraetschmer
    Abstract: In this work we consider optimal stopping problems with conditional convex risk measures called optimised certainty equivalents. Without assuming any kind of time-consistency for the underlying family of risk measures, we derive a novel representation for the solution of the optimal stopping problem. In particular, we generalise the additive dual representation of Rogers (2002) to the case of optimal stopping under uncertainty. Finally, we develop several Monte Carlo algorithms and illustrate their power for optimal stopping under Average Value at Risk.
    Date: 2014–05
  10. By: Julien Chevallier; Stéphane Goutte
    Abstract: This article analyzes the interactions between the electricity and CO2 (carbon) markets. In particular, we describe the dynamics of the fuel-switching price (from coal to gas) when taking into account carbon costs. Several stochastic processes are considered to model the fuel-switching price: (i) the Brownian motion, and (ii) the Lévy jump process. Besides, the probability density function is evaluated by considering the Gaussian case versus the Normal Inverse Gaussian and the Variance Gamma distributions. The results unambigu- ously point out the need to resort to jump modeling techniques to model satisfactorily the fuel-switching price with evidence of heavy tails. The Gaussianity assumption is also clearly rejected in favor of its main competitors, whereas it is found that the NIG beats the Variance Gamma distribution. Taken together, these empirical results convey implications for risk managers looking to forecast and hedge their utilities’ production.
    Keywords: CO2; Fuel-Switching; Lévy Jump process; Mean-reversion; Normal Inverse Gaussian; Variance Gamma; Model fit; Heavy tails; Goodness-of-fit testing.
    JEL: C15 C53 Q40
    Date: 2014–05–12

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