New Economics Papers
on Risk Management
Issue of 2012‒05‒02
nine papers chosen by

  1. Risk Management and Financial Derivatives: An Overview By Shawkat Hammoudeh; Michael McAleer
  2. Alternative Modeling for Long Term Risk. By Dominique Guegan; Xin Zhao
  3. Risk spillovers in international equity portfolios By Matteo Bonato; Massimiliano Caporin; Angelo Ranaldo
  4. Modelling macroeconomic effects and expert judgements in operational risk : a Bayesian approach By Holger Capa Santos; Marie Kratz; Franklin Mosquera Munoz
  5. Support Vector Machines with Evolutionary Feature Selection for Default Prediction By Wolfgang Karl Härdle; Dedy Dwi Prastyo; Christian Hafner
  6. Securitization and the dark side of diversification By Maarten van Oordt
  7. Transmission of distress in a bank credit network By Yoshiharu Maeno; Satoshi Morinaga; Hirokazu Matsushima; Kenichi Amagai
  8. Estimating financial institutions’ intraday liquidity risk: a Monte Carlo simulation approach By Carlos Léon
  9. Using Merton model: an empirical assessment of alternatives By Zvika Afik; Ohad Arad; Koresh Galil

  1. By: Shawkat Hammoudeh (Department of Economics Drexel University); Michael McAleer (Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam and Tinbergen Institute, The Netherlands, Department of Quantitative Economics, Complutense University of Madrid, and Institute of Economic Research, Kyoto University)
    Abstract: Risk management is crucial for optimal portfolio management. One of the fastest growing areas in empirical finance is the expansion of financial derivatives. The purpose of this special issue on “Risk Management and Financial Derivatives” is to highlight some areas in which novel econometric, financial econometric and empirical finance methods have contributed significantly to the analysis of risk management, with an emphasis on financial derivatives, specifically conditional correlations and volatility spillovers between crude oil and stock index returns, pricing exotic options using the Wang transform, the rise and fall of S&P500 variance futures, predicting volatility using Markov switching multifractal model: evidence from S&P100 index and equity options, the performance of commodity trading advisors: a mean-variance-ratio test approach, forecasting volatility via stock return, range, trading volume and spillover effects: the case of Brazil, estimating and simulating Weibull models of risk or price durations: an application to ACD models, valuation of double trigger catastrophe options with counterparty risk, day of the week effect on the VIX - a parsimonious representation, equity and CDS sector indices: dynamic models and risk hedging, the probability of default in collateralized credit operations, risk premia in multi-national enterprises, solving replication problems in a complete market by orthogonal series expansion, downside risk management and VaR-based optimal portfolios for precious metals, oil and stocks, and implied Sharpe ratios of portfolios with options: application to Nikkei futures and listed options.
    Keywords: Risk management, Optimal portfolios, Financial derivatives, Financial econometrics, Options, Futures, Volatility, Spillovers, Hedging, Default, Risk premia, Complete markets.
    Date: 2012–04
  2. By: Dominique Guegan (Centre d'Economie de la Sorbonne - Paris School of Economics); Xin Zhao (Centre d'Economie de la Sorbonne)
    Abstract: In this paper, we propose an alternative approach to estimate long-term risk. Instead of using the static square root method, we use a dynamic approach based on volatility forecasting by non-linear models. We explore the possibility of improving the estimations by different models and distributions. By comparing the estimations of two risk measures, value at risk and expected shortfall, with different models and innovations at short, median and long-term horizon, we find out that the best model varies with the forecasting horizon and the generalized Pareto distribution gives the most conservative estimations with all the models at all the horizons. The empirical results show that the square root method underestimates risk at long horizon and our approach is more competitive for risk estimation at long term.
    Keywords: Long memory, Value at Risk, expect shortfall, extreme value distribution.
    JEL: G32 G17 C58
    Date: 2012–03
  3. By: Matteo Bonato; Massimiliano Caporin; Angelo Ranaldo
    Abstract: We define risk spillover as the dependence of a given asset variance on the past covariances and variances of other assets. Building on this idea, we propose the use of a highly flexible and tractable model to forecast the volatility of an international equity portfolio. According to the risk management strategy proposed, portfolio risk is seen as a specific combination of daily realized variances and covariances extracted froma high frequency dataset, which includes equities and currencies. In this framework, we focus on the risk spillovers across equities within the same sector (sector spillover), and fromcurrencies to international equities (currency spillover). We compare these specific risk spillovers to a more general framework (full spillover) whereby we allow for lagged dependence across all variances and covariances. The forecasting analysis shows that considering only sector- and currency-risk spillovers, rather than full spillovers, improves performance, both in economic and statistical terms.
    Keywords: Risk spillover, portfolio risk, currency risk, variance forecasting, international portfolio, Wishart distribution
    JEL: C13 C16 C22 C51 C53 G17
    Date: 2012
  4. By: Holger Capa Santos (Escuela Politecnica Nacional - Facultad de Geologia); Marie Kratz (MAP5 - Mathématiques appliquées Paris 5 - CNRS : UMR8145 - Université Paris V - Paris Descartes, SID - Information Systems / Decision Sciences Department - ESSEC Business School); Franklin Mosquera Munoz (Escuela Politecnica Nacional - Facultad de Geologia)
    Abstract: This work presents a contribution on operational risk under a general Bayesian context incorporating information on market risk pro le, experts and operational losses, taking into account the general macroeconomic environment as well. It aims at estimating a characteristic parameter of the distributions of the sources, market risk pro le, experts and operational losses, chosen here at a location parameter. It generalizes under more realistic conditions a study realized by Lambrigger, Shevchenko and Wuthrich, and analyses macroeconomic e ects on operational risk. It appears that severities of operational losses are more related to the macroeconomics environment than usually assumed.
    Keywords: Basel II ; Bayesian inference ; Loss distribution approach ; Macroeconomics dependence ; Operational Risk ; Quantitative Risk Management ; Solvency 2
    Date: 2012–01–01
  5. By: Wolfgang Karl Härdle; Dedy Dwi Prastyo; Christian Hafner
    Abstract: Predicting default probabilities is at the core of credit risk management and is becoming more and more important for banks in order to measure their client's degree of risk, and for rms to operate successfully. The SVM with evolutionary feature selection is applied to the CreditReform database. We use classical methods such as discriminan analysis (DA), logit and probit models as benchmark On overall, GA-SVM is outperforms compared to the benchmark models in both training and testing dataset.
    Keywords: SVM, Genetic algorithm, global optmimum, default prediction
    JEL: C14 C45 C61 C63 G33
    Date: 2012–04
  6. By: Maarten van Oordt
    Abstract: Diversification by banks affects the systemic risk of the sector. Importantly, Wagner (2010) shows that linear diversification increases systemic risk. We consider the case of securitization, whereby loan portfolios are sliced into tranches with different seniority levels. We show that tranching offers nonlinear diversification strategies, which can reduce the failure risk of individual institutions beyond the minimum level attainable by linear diversification, without increasing systemic risk.
    Keywords: Securitization; Diversification; Systemic risk; Risk management; Tranching
    JEL: G11 G21
    Date: 2012–03
  7. By: Yoshiharu Maeno; Satoshi Morinaga; Hirokazu Matsushima; Kenichi Amagai
    Abstract: The European sovereign debt crisis has impaired many European banks. The distress on the European banks may transmit worldwide, and result in a large-scale knock-on default of financial institutions. This study presents a computer simulation model to analyze the risk of insolvency of banks and defaults in a bank credit network. Simulation experiments reproduce the knock-on default, and quantify the impact which is imposed on the number of bank defaults by heterogeneity of the bank credit network, the equity capital ratio of banks, and the capital surcharge on big banks.
    Date: 2012–04
  8. By: Carlos Léon
    Abstract: The most recent financial crisis unveiled that liquidity risk is far more important and intricate than regulation have conceived. The shift from bank-based to market-based financial systems and from Deferred Net Systems to liquidity-demanding Real-Time Gross Settlement of payments explains some of the shortcomings of traditional liquidity risk management. Although liquidity regulations do exist, they still are in an early stage of development and discussion. Moreover, no all connotations of liquidity are equally addressed. Unlike market and funding liquidity, intraday liquidity has been absent from financial regulation, and has appeared only recently, after the crisis. This paper addresses the measurement of Large-Value Payment System’s intraday liquidity risk. Based on the generation of bivariate Poisson random numbers for simulating the minute-by-minute arrival of received and executed payments, each financial institution’s intraday payments time-varying volume and degree of synchrony (i.e. timing) is modeled. To model intraday payments’ uncertainty allows for (i) overseeing participants’ intraday behavior; (ii) assessing their ability to fulfill intraday payments at a certain confidence level; (iii) identifying participants non-resilient to changes in payments’ timing mismatches; (iv) estimating intraday liquidity buffers. Vis-à-vis the increasing importance of liquidity risk as a source of systemic risk, and the recent regulatory amendments, results are useful for financial authorities and institutions.
    Date: 2012–04–11
  9. By: Zvika Afik (Guilford Glazer faculty of Business and Management, Ben- Gurion University of the Negev, Israel); Ohad Arad (Ben Gurion University of the Negev, Beer-Sheva, Israel); Koresh Galil (Ben Gurion University of the Negev, Beer-Sheva, Israel)
    Abstract: Merton (1974) suggested a structural model for default prediction which allows using timely information from the equity market. The literature describes several specifications to the application of the model, including methods presumably used by practitioners. However, recent studies demonstrate that these methods result in inferior estimates compared to simpler substitutes. We empirically examine various specification alternatives and find that the prediction goodness is only slightly sensitive to different choices of default barrier, whereas the choice of assets expected return and assets volatility is significant. Equity historical return and historical volatility produce underbiased estimates for assets expected return and assets volatility, especially for defaulting firms. Acknowledging these characteristics we suggest specifications that improve the model accuracy.
    Keywords: Credit risk; Default prediction; Merton model; Bankruptcy prediction, Default barrier; Assets volatility
    Date: 2012

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