nep-rmg New Economics Papers
on Risk Management
Issue of 2013‒06‒16
eighteen papers chosen by
Stan Miles
Thompson Rivers University

  1. Bayesian inference for CoVar By Mauro Bernardi; Ghislaine Gayraud; Lea Petrella
  2. Loss Distribution Approach for Operational Risk Capital Modelling under Basel II: Combining Different Data Sources for Risk Estimation By Pavel V. Shevchenko; Gareth W. Peters
  3. Estimating Default and Recovery Rate Correlations By Jiri Witzany
  4. A Note on the Vasicek’s Model with the Logistic Distribution By Jiri Witzany
  5. GFC-Robust Risk Management under the Basel Accord using Extreme Value Methodologies By Juan-Angel Jimenez-Martin; Michael McAleer; Teodosio Perez Amaral; Paulo Araujo Santos
  6. Forecasting Value-at-Risk using Block Structure Multivariate Stochastic Volatility Models By Manabu Asai; Massimiliano Caporin; Michael McAleer
  7. A Viable Alternative to Basel III Prudential Capital Rules By Micossi,Stefano
  8. Impact of Macroeconomic and Endogenous Factors on Non-Performing Bank Assets By Swamy, Vighneswara
  9. Modeling and Forecasting the Volatility of Energy Forward Returns - Evidence from the Nordic Power Exchange By Asger Lunde; Kasper V. Olesen
  10. Ship incident risk in the areas of Tubbataha and Banc d’Arguin: A case for designation as Particular Sensitive Sea Area? By Knapp, S.; Heij, C.; Henderson, R.; Kleverlaan, E.
  11. Rules of Thumb for Banking Crises in Emerging Markets By Paolo Manasse; Roberto Savona; Marika Vezzoli
  12. On the Risk Return Relationship. By Jianxin Wang; Minxian Yang
  13. Disentangling Continuous Volatility from Jumps in Long-Run Risk-Return Relationships By Éric Jacquier; Cédric Okou
  14. Ensuring robust flood risk management in Ho Chi Minh city By Lempert, Robert; Kalra, Nidhi; Peyraud, Suzanne; Mao, Zhimin; Tan, Sinh Bach; Cira, Dean; Lotsch, Alexander
  15. Systemic risk and spatiotemporal dynamics of the US housing market By Hao Meng; Wen-Jie Xie; Zhi-Qiang Jiang; Boris Podobnik; Wei-Xing Zhou; H. Eugene Stanley
  16. Portfolio selection models based on characteristics of return distributions By Paweł Wnuk Lipinski
  17. Commodity futures markets: are they an effective price risk management tool for the European wheat supply chain ? By Revoredo-Giha, C.; Zuppiroli, M.
  18. Social Crisis Prevention: A Political Alert Index for the Israel-Palestine Conflict By André De Palma,; Federico Perali; Nathalie Picard; Roberto Ricciuti; Alexandrina Scorbureanu

  1. By: Mauro Bernardi; Ghislaine Gayraud; Lea Petrella
    Abstract: Recent financial disasters emphasised the need to investigate the consequence associated with the tail co-movements among institutions; episodes of contagion are frequently observed and increase the probability of large losses affecting market participants' risk capital. Commonly used risk management tools fail to account for potential spillover effects among institutions because they provide individual risk assessment. We contribute to analyse the interdependence effects of extreme events providing an estimation tool for evaluating the Conditional Value-at-Risk (CoVaR) defined as the Value-at-Risk of an institution conditioned on another institution being under distress. In particular, our approach relies on Bayesian quantile regression framework. We propose a Markov chain Monte Carlo algorithm exploiting the Asymmetric Laplace distribution and its representation as a location-scale mixture of Normals. Moreover, since risk measures are usually evaluated on time series data and returns typically change over time, we extend the CoVaR model to account for the dynamics of the tail behaviour. Application on U.S. companies belonging to different sectors of the Standard and Poor's Composite Index (S&P500) is considered to evaluate the marginal contribution to the overall systemic risk of each individual institution
    Date: 2013–06
  2. By: Pavel V. Shevchenko; Gareth W. Peters
    Abstract: The management of operational risk in the banking industry has undergone significant changes over the last decade due to substantial changes in operational risk environment. Globalization, deregulation, the use of complex financial products and changes in information technology have resulted in exposure to new risks very different from market and credit risks. In response, Basel Committee for banking Supervision has developed a regulatory framework, referred to as Basel II, that introduced operational risk category and corresponding capital requirements. Over the past five years, major banks in most parts of the world have received accreditation under the Basel II Advanced Measurement Approach (AMA) by adopting the loss distribution approach (LDA) despite there being a number of unresolved methodological challenges in its implementation. Different approaches and methods are still under hot debate. In this paper, we review methods proposed in the literature for combining different data sources (internal data, external data and scenario analysis) which is one of the regulatory requirement for AMA.
    Date: 2013–06
  3. By: Jiri Witzany (University of Economics in Prague)
    Abstract: The paper analyzes a two-factor credit risk model allowing to capture default and recovery rate variation, their mutual correlation, and dependence on various explanatory variables. At the same time, it allows computing analytically the unexpected credit loss. We propose and empirically implement estimation of the model based on aggregate and exposure level Moody’s default and recovery data. The results confirm existence of significantly positive default and recovery rate correlation. We empirically compare the unexpected loss estimates based on the reduced two-factor model with Monte Carlo simulation results, and with the current regulatory formula outputs. The results show a very good performance of the proposed analytical formula which could feasibly replace the current regulatory formula.
    Keywords: credit risk, Basel II regulation, default rates, recovery rates, correlation
    JEL: G20 G28 C51
    Date: 2013–04
  4. By: Jiri Witzany (University of Economics in Prague)
    Abstract: The paper argues that it would be natural to replace the standard normal distribution function by the logistic function in the regulatory Basel II (Vasicek’s) formula. Such a model would be in fact consistent with the standard logistic regression PD modeling approach. An empirical study based on US commercial bank’s loan historical delinquency rates re-estimates the default correlations and unexpected losses for the normal and logistic distribution models. The results indicate that the capital requirements could be up to 100% higher if the normal Vasicek’s model was replaced by the logistic one.
    Keywords: credit risk, Basel II regulation, default rates
    JEL: G20 G28 C51
    Date: 2013–01
  5. By: Juan-Angel Jimenez-Martin (Complutense University of Madrid, Spain); Michael McAleer (Complutense University of Madrid, Spain, Erasmus School of Economics, Erasmus University Rotterdam, The Netherlands, and Kyoto University, Japan); Teodosio Perez Amaral (Complutense University of Madrid, Spain); Paulo Araujo Santos (University of Lisbon, Portugal)
    Abstract: In this paper we provide further evidence on the suitability of the median of the point VaR forecasts of a set of models as a GFC-robust strategy by using an additional set of new extreme value forecasting models and by extending the sample period for comparison. These extreme value models include DPOT and Conditional EVT. Such models might be expected to be useful in explaining financial data, especially in the presence of extreme shocks that arise during a GFC. Our empirical results confirm that the median remains GFC-robust even in the presence of these new extreme value models. This is illustrated by using the S&P500 index before, during and after the 2008-09 GFC. We investigate the performance of a variety of single and combined VaR forecasts in terms of daily capital requirements and violation penalties under the Basel II Accord, as well as other criteria, including several tests for independence of the violations. The strategy based on the median, or more generally, on combined forecasts of single models, is straightforward to incorporate into existing computer software packages that are used by banks and other financial institutions.
    Keywords: Value-at-Risk (VaR), DPOT, daily capital charges, robust forecasts, violation penalties, optimizing strategy, aggressive risk management, conservative risk management, Basel, global financial crisis
    JEL: G32 G11 G17 C53 C22
    Date: 2013–05–21
  6. By: Manabu Asai (Soka University, Japan); Massimiliano Caporin (University of Padova, Italy); Michael McAleer (Erasmus University Rotterdam, The Netherlands, Complutense University of Madrid, Spain, and Kyoto University, Japan)
    Abstract: Most multivariate variance or volatility models suffer from a common problem, the “curse of dimensionality”. For this reason, most are fitted under strong parametric restrictions that reduce the interpretation and flexibility of the models. Recently, the literature has focused on multivariate models with milder restrictions, whose purpose is to combine the need for interpretability and efficiency faced by model users with the computational problems that may emerge when the number of assets can be very large. We contribute to this strand of the literature by proposing a block-type parameterization for multivariate stochastic volatility models. The empirical analysis on stock returns on the US market shows that 1% and 5 % Value-at-Risk thresholds based on one-step-ahead forecasts of covariances by the new specification are satisfactory for the period including the Global Financial Crisis.
    Keywords: block structures; multivariate stochastic volatility; curse of dimensionality; leverage effects; multi-factors; heavy-tailed distribution
    JEL: C32 C51 C10
    Date: 2013–05–27
  7. By: Micossi,Stefano
    Abstract: Stefano Micossi argues in this paper that the Basel framework for bank prudential requirements is deeply flawed and that the Basel III revision has failed to correct these flaws, making the system even more complicated, opaque and open to manipulation. In practice, he finds that the present system does not offer regulators and financial markets a reliable capital standard for banks and its divergent implementation in the main jurisdictions of the European Union and the United States has broken the market into special fiefdoms governed by national regulators in response to untoward special interests. The time is ripe to stop tinkering with minor adjustment and revisions in order to rescue the system, because the system cannot be rescued. In response to the current situation, Micossi calls for abandoning reference to risk-weighted assets calculated by banks with their internal risk management models for the determination of banks’ prudential capital, together with the preoccupation with the asset side of banks in correcting for risk exposure. He suggests that the alternative may be provided by a combination of a straight capital ratio and a properly designed deposit insurance system. It is a logical, complete and much less distortive alternative; it would serve better the cause of financial stability as well as the interest of the banks in clear, transparent and level playing field.
    Date: 2013–05
  8. By: Swamy, Vighneswara
    Abstract: Determinants of default risk of banks in emerging economies have so far received inadequate attention in the literature. Using panel data techniques, this paper seeks to examine the impact of macroeconomic and endogenous factors on non-performing assets for the period from 1997-2009. The findings of the study reveal some interesting inferences contrary to the perception of few opinion makers. Lending Rates have been found to be not so significant in affecting the NPAs contrary to the general perception Bank Assets has turned out to be negatively significant indicating that large banks may have better risk management procedures and technology which definitely allows them to finish up with lower levels of NPAs. Further, this study has established that private banks and foreign banks have advantages in terms of their efficiencies in better credit management in containing the NPAs that indicates that bank privatization can lead to better management of default risk.
    Keywords: Banks, Risk Management, Ownership Structure, Financial Markets, Non-Performing Assets, Lending Policy, Macro-economy, Central Banks
    JEL: E44 E51 G21 G32
    Date: 2012
  9. By: Asger Lunde (Aarhus University and CREATES); Kasper V. Olesen (Aarhus University and CREATES)
    Abstract: We explore the structure of transaction records from NASDAQ OMX Commodities Europe back to 2006 and analyze base load forwards with the Nordic system price on electric power as reference. Following a discussion of the appropriate rollover scheme we incorporate selected realizedmeasures of volatility in a Realized EGARCH framework for the joint modeling of returns and realized measures of volatility. Conditional variances are shown to vary over time, which stresses the importance of portfolio reallocation for risk management and other purposes. We document gains from utilizing data at higher frequencies by comparing to ordinary EGARCH models that are nested in the Realized EGARCH. We obtain improved fit, in-sample as well as out-of-sample. In-sample in terms of improved loglikelihood and out-of-sample in terms of 1-, 5-, and 20-step-ahead regular and bootstrapped rolling-window forecasts. The Realized EGARCH forecasts are statistically superior to ordinary EGARCH forecasts.
    Keywords: Financial Volatility, Realized GARCH, High Frequency Data, Electricity, Power, Forecasting, Realized Variance, Realized Kernel, Model Confidence Set
    JEL: C10 C22 C53 C58 C80
    Date: 2013–05–24
  10. By: Knapp, S.; Heij, C.; Henderson, R.; Kleverlaan, E.
    Abstract: Since the early 1990's, the International Maritime Organization (IMO) has designated fourteen sea areas as Particular Sensitive Sea Areas (PSSA) that enjoy special protection because of their various important attributes and vulnerability to potential harm by increasing shipping activities. The United Nations Educational, Scientific and Cultural Organization (UNESCO) has identified two possible sites for possible designation as PSSA under IMO: the Banc d'Arguin National Park (Mauritania) and the Tubbataha Reef National Park (Philippines). This article presents an integrated framework for the estimation of total risk exposure due to shipping activities and various risk measures for ships trading in the areas of interest. Using a unique and comprehensive combination of data, we test whether ship specific risk increased over time. The results confirm an increase in the considered risk measures of ships trading through or nearby West Africa (Banc d’Arguin) and South-East Asia (Tubbataha) in general and also close to both regions and therefore support the recommendation for an increased level of protection.
    Keywords: binary logistic regression;total risk exposure;observation frequency;change of risk over time;incident probabili
    Date: 2013–06–01
  11. By: Paolo Manasse; Roberto Savona; Marika Vezzoli
    Abstract: This paper employs a recent statistical algorithm (CRAGGING) in order to build an early warning model for banking crises in emerging markets. We perturb our data set many times and create “artificial” samples from which we estimated our model, so that, by construction, it is flexible enough to be applied to new data for out-of-sample prediction. We find that, out of a large number (540) of candidate explanatory variables, from macroeconomic to balance sheet indicators of the countries’ financial sector, we can accurately predict banking crises by just a handful of variables. Using data over the period from 1980 to 2010, the model identifies two basic types of banking crises in emerging markets: a “Latin American type”, resulting from the combination of a (past) credit boom, a flight from domestic assets, and high levels of interest rates on deposits; and an “Asian type”, which is characterized by an investment boom financed by banks’ foreign debt. We compare our model to other models obtained using more traditional techniques, a Stepwise Logit, a Classification Tree, and an “Average” model, and we find that our model strongly dominates the others in terms of out-of-sample predictive power. JEL: E44, G01, G21 Keywords: Banking Crises, Early Warnings, Regression and Classification Trees, Stepwise Logit
    Date: 2013
  12. By: Jianxin Wang (UTS Business School, the University of Technology Sydney); Minxian Yang (School of Economics, the University of New South Wales)
    Abstract: While the risk return trade-off theory suggests a positive relationship between the expected return and the conditional volatility, the volatility feedback theory implies a channel that allows the conditional volatility to negatively affect the expected return. We examine the effects of the risk return trade-off and the volatility feedback in a model where both the return and its volatility are influenced by news arrivals. Our empirical analysis shows that the two effects have approximately the same size with opposite signs for the daily excess returns of seven major developed markets. For the same data set, we also find that a linear relationship between the expected return and the conditional standard deviation is preferable to polynomial-type nonlinear specifications.
    Keywords: Risk premium, volatility feedback, GARCH-in-mean, Maximum likelihood, Mixture distributions, Time series.
    Date: 2012–05
  13. By: Éric Jacquier; Cédric Okou
    Abstract: Realized variance can be broken down into continuous volatility and jumps. We show that these two components have very different predictive powers on future long-term excess stock market returns. While continuous volatility is a key driver of medium to long-term risk-return relationships, jumps do not predict future medium- to long-term excess returns. We use inference methods robust to persistent predictors in a multi-horizon setup. That is, we use a rescaled Student-t to test for significant risk-return links, give asymptotic arguments and simulate its exact behavior under the null in the case of multiple regressors with different degrees of persistence. Then, with Wald tests of equality of the risk-return relationship at multiple horizons, we find no evidence against a proportional relationship, constant across horizons, between long-term continuous volatility and future returns. Two by-products of our analysis are that imposing model-based constraints on long term regressions can improve their efficiency, and short-run estimates are sensitive to short-term variability of the predictors. <P>
    Keywords: predictability, realized variance, continuous volatility, jumps, long-run returns, persistent regressor,
    Date: 2013–06–01
  14. By: Lempert, Robert; Kalra, Nidhi; Peyraud, Suzanne; Mao, Zhimin; Tan, Sinh Bach; Cira, Dean; Lotsch, Alexander
    Abstract: Ho Chi Minh City faces significant and growing flood risk. Recent risk reduction efforts may be insufficient as climate and socio-economic conditions diverge from projections made when those efforts were initially planned. This study demonstrates how robust decision making can help Ho Chi Minh City develop integrated flood risk management strategies in the face of such deep uncertainty. Robust decision making is an iterative, quantitative, decision support methodology designed to help policy makers identify strategies that are robust, that is, satisfying decision makers'objectives in many plausible futures, rather than being optimal in any single estimate of the future. This project used robust decision making to analyze flood risk management in Ho Chi Minh City's Nhieu Loc-Thi Nghe canal catchment area. It found that the soon-to-be-completed infrastructure may reduce risk in best estimates of future conditions, but it may not keep risk low in many other plausible futures. Thus, the infrastructure may not be sufficiently robust. The analysis further suggests that adaptation and retreat measures, particularly when used adaptively, can play an important role in reducing this risk. The study examines the conditions under which robust decision making concepts and full robust decision making analyses may prove useful in developing countries. It finds that planning efforts in developing countries should at minimum use models and data to evaluate their decisions under a wide range of conditions. Full robust decision making analyses can also augment existing planning efforts in numerous ways.
    Keywords: Hazard Risk Management,Non Bank Financial Institutions,Labor Policies,Water Supply and Sanitation Governance and Institutions,Debt Markets
    Date: 2013–05–01
  15. By: Hao Meng (ECUST); Wen-Jie Xie (ECUST); Zhi-Qiang Jiang (ECUST); Boris Podobnik (BU and ZSEM); Wei-Xing Zhou (ECUST); H. Eugene Stanley (BU)
    Abstract: Housing markets play a crucial role in economies and the collapse of a real-estate bubble usually destabilizes the financial system and causes economic recessions. We investigate the systemic risk and spatiotemporal dynamics of the US housing market (1975-2011) at the state level based on the Random Matrix Theory (RMT). We identify rich economic information in the largest eigenvalues deviating from RMT predictions and unveil that the component signs of the eigenvectors contain either geographical information or the extent of differences in house price growth rates or both. Our results show that the US housing market experienced six different regimes, which is consistent with the evolution of state clusters identified by the box clustering algorithm and the consensus clustering algorithm on the partial correlation matrices. Our analysis uncovers that dramatic increases in the systemic risk are usually accompanied with regime shifts, which provides a means of early detection of housing bubbles.
    Date: 2013–06
  16. By: Paweł Wnuk Lipinski (Faculty of Economic Sciences)
    Abstract: This article concerns the problem of optimal portfolio selection. The objective of this paper is to indicate the best method and criteria for optimal portfolio selection. In order to achieve the objective six models including such optimization criteria as mean, variance, skewness, kurtosis and transaction costs are analyzed. The method of fuzzy multi-objective programming is used to transform multiple conflicting criteria into a single objective problem and to find optimal portfolios. In order to indicate the best portfolio selection model a simulation based on five years data from January 1, 2007 to December 31, 2011 was conducted. The portfolios were constructed from WIG20 stocks and WIBID 3M as risk-free asset.
    Keywords: optimal portfolio, portfolio selection, fuzzy multi-objective programming, skewness, kurtosis
    JEL: G11 C61
    Date: 2013
  17. By: Revoredo-Giha, C.; Zuppiroli, M.
    Abstract: The instability of commodity prices and the hypothesis that speculative behaviour was one of its causes has brought renewed interest in futures markets. In this paper, we analyse the European wheat futures markets (feed and milling) and the CBOT’s wheat contract as a comparison, to study their efficiency, hedging effectiveness and whether they were affected during the period of high instability after 2007. Implicitly this is a test of whether the increasing presence of speculation in futures markets have made them divorced from the physical markets, and therefore, not useful for commercial entities aiming to exchange price risk for basis risk.
    Keywords: Futures prices, commodity prices, volatility, wheat, Demand and Price Analysis, Farm Management, International Relations/Trade, G1, G130,
    Date: 2013–06
  18. By: André De Palma,; Federico Perali; Nathalie Picard; Roberto Ricciuti; Alexandrina Scorbureanu (Ecole Normale Supérieure de Cachan; University of Verona and CHILD; Universite de Cergy-Pontoise; University of Verona and CESifo; University of Verona)
    Abstract: This study presents a novel approach to crisis prevention based on data on premonitory political and religious events and the international media coverage of publicly sensitive circumstances. We implement our method to the Israel-Palestine conflict. First we identify two main political scenarios associated with "good" and "bad" political times of low or high levels of political unrest using a hierarchical clustering technique. Then we construct a political alert index to predict the probability of occurrence of good and bad times. Bad times are positively and significantly associated with the number of Israeli victims at the checkpoints, the number of homeless or injured Palestinians and with the number of demolitions. The number of Palestinian prisoners and injured Israelis negatively affect the probability of occurrence of a bad time. Media coverage is positively and significantly associated with the transition to bad times. Our results show that our statistical tool can be a reliable method for early warning of social crisis and can be effectively replicated to other social crisis situations.
    Keywords: crisis prevention, alert index, news, Israel, Palestine
    JEL: D74 F51 P48
    Date: 2013

This nep-rmg issue is ©2013 by Stan Miles. It is provided as is without any express or implied warranty. It may be freely redistributed in whole or in part for any purpose. If distributed in part, please include this notice.
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