New Economics Papers
on Risk Management
Issue of 2007‒04‒09
twelve papers chosen by

  1. Integrating credit and interest rate risk: A theoretical framework and an application to banks' balance sheets By Mathias Drehmann; Steffen Sorensen; Marco Stringa
  2. International Portfolio Diversification and Market Linkages in the presence of regime-switching volatility By Thomas Flavin; Ekaterini Panopoulou
  3. Nonlinear Combination of Financial Forecast with Genetic Algorithm By Ozun, Alper; Cifter, Atilla
  4. Scaling Models for the Severity and Frequency of External Operational Loss Data By Hela Dahen; Georges Dionne
  5. The Predictive Performance of Asymmetric Normal Mixture GARCH in Risk Management: Evidence from Turkey By Cifter, Atilla; Ozun, Alper
  6. Single and joint default in a structural model with purely discontinuous assets By Filippo Fiorani; Elisa Luciano; Patrizia Semeraro
  7. Multiscale Systematic Risk: An Application on ISE-30 By Cifter, Atilla; Ozun, Alper
  8. Assessing the Relation between Equity Risk Premia and Macroeconomic Volatilities By Renatas Kizys; Peter Spencer
  9. Managing Adverse Dependence for Portfolios of Collateral in Financial Infrastructures By Alejandro García; Ramazan Gençay
  10. Does Risk Aversion Drive Financial Crises? Testing the Predictive Power of Empirical Indicators By Virginie Coudert; Mathieu Gex
  11. Emerging Stock Market Returns: The CAPM Challenge. By Laurent Gheeraert
  12. Sentiment in foreign exchange markets: Hidden fundamentals by the back door or just noise? By Rafael R. Rebitzky

  1. By: Mathias Drehmann (Systemic Risk Assessment Division, Bank of England); Steffen Sorensen (Systemic Risk Assessment Division, Bank of England); Marco Stringa (Systemic Risk Assessment Division, Bank of England)
    Abstract: Credit and interest rate risk in the banking book are the two most important risks faced by commercial banks. In this paper we derive a consistent and general framework to measure the riskiness of a bank which is subject to correlated interest rate and credit risk. The framework accounts for all sources of credit risk, interest rate risk and their combined impact As we model the whole balance sheet of a bank the framework not only enables us to assess the impact of credit and interest rate risk on the bank's economic value but also on its future earnings and capital adequacy. We apply our framework to a hypothetical bank in normal and stressed conditions. The simulation highlights that it is fundamental to measure the impact of correlated interest rate and credit risk jointly on the whole portfolio of banks, including assets, liabilities and off-balance sheet items
    Keywords: Integration of credit risk & interest rate risk, asset & liability management of banks, economic value, stress testing
    JEL: G21 E47 C13
    Date: 2007–02–02
  2. By: Thomas Flavin (NUI, Maynooth); Ekaterini Panopoulou (NUI, Maynooth)
    Abstract: We examine if the benefits of international portfolio diversification are robust to time-varying asset return volatility. Since diversified portfolios are subject to common cross-country shocks, we focus on the transmission mechanism of such shocks in the presence of regime-switching volatility. We find little evidence of incresaed market interdependence in turbulent periods. Furthermore, for the vast majority of time, we show that risk reduction is delivered for the US investor who holds foreign equit
    Keywords: Market comovement, International portfolio diversification, Financial market crises, Regime switching
    JEL: F42
    Date: 2007–02–02
  3. By: Ozun, Alper; Cifter, Atilla
    Abstract: Complexity in the financial markets requires intelligent forecasting models for return volatility. In this paper, historical simulation, GARCH, GARCH with skewed student-t distribution and asymmetric normal mixture GRJ-GARCH models are combined with Extreme Value Theory Hill by using artificial neural networks with genetic algorithm as the combination platform. By employing daily closing values of the Istanbul Stock Exchange from 01/10/1996 to 11/07/2006, Kupiec and Christoffersen tests as the back-testing mechanisms are performed for forecast comparison of the models. Empirical findings show that the fat-tails are more properly captured by the combination of GARCH with skewed student-t distribution and Extreme Value Theory Hill. Modeling return volatility in the emerging markets needs “intelligent” combinations of Value-at-Risk models to capture the extreme movements in the markets rather than individual model forecast.
    Keywords: Forecast combination; Artificial neural networks; GARCH models; Extreme value theory; Christoffersen test
    JEL: G0 C52 C32
    Date: 2007–02–01
  4. By: Hela Dahen; Georges Dionne
    Abstract: According to Basel II criteria, the use of external data is absolutely indispensable to the implementation of an advanced method for calculating operational capital. This article investigates how the severity and frequencies of external losses are scaled for integration with internal data. We set up an initial model designed to explain the loss severity. This model takes into account firm size, location, and business lines as well as risk types. It also shows how to calculate the internal loss equivalent to an external loss, which might occur in a given bank. OLS estimation results show that the above variables have significant power in explaining the loss amount. They are used to develop a normalization formula. A second model based on external data is developed to scale the frequency of losses over a given period. Two regression models are analyzed: the truncated Poisson model and the truncated negative binomial model. Variables estimating the size and geographical distribution of the banks' activities have been introduced as explanatory variables. The results show that the negative binomial distribution outperforms the Poisson distribution. The scaling is done by calculating the parameters of the selected distribution based on the estimated coefficients and the variables related to a given bank. Frequency of losses of more than $1 million are generated on a specific horizon.
    Keywords: Operational risk in banks, scaling, severity distribution, frequency distribution, truncated count data regression models
    JEL: G21 G28 C30 C35
    Date: 2007
  5. By: Cifter, Atilla; Ozun, Alper
    Abstract: The purpose of this study is to test predictive performance of Asymmetric Normal Mixture Garch (NMAGARCH) and other Garch models based on Kupiec and Christoffersen tests for Turkish equity market. The empirical results show that the NMAGARCH perform better based on %99 CI out-of-sample forecasting Christoffersen test where Garch with normal and student-t distribution perform better based on %95 Cl out-of-sample forecasting Christoffersen test and Kupiec test. These results show that none of the model including NMAGARCH outperforms other models in all cases as trading position or confidence intervals and these results shows that volatility model should be chosen according to confidence interval and trading positions. Besides, NMAGARCH increases predictive performance for higher confidence internal as Basel requires.
    Keywords: Garch; Asymmetric Normal Mixture Garch; Kupiec Test; Christoffersen Test; Emerging markets
    JEL: G00 C52 C32
    Date: 2007–01–01
  6. By: Filippo Fiorani; Elisa Luciano; Patrizia Semeraro
    Abstract: Structural models of credit risk are known to present both vanishing spreads at very short maturities and a poor spread fit over longer maturities. The former shortcoming, which is due to the diffusive behavior assumed for asset values, can be circumvented by considering discontinuous assets. In this paper we resort to a pure jump process of the Variance-Gamma type. First we calibrate the corresponding Merton type structural model to single-name data for the DJ CDX NA IG and CDX NA HY components. By so doing, we show that it circumvents also the diffusive structural models difficulties over longer horizons. In particular, it corrects for underprediction of low risk spreads and overprediction of high risk ones. Then we extend the model to joint default, resorting to a recent formulation of the VG multivariate model and without superimposing a copula choice. We fit default correlation for a sample of CDX NA names, using equity correlation. The main advantage of our joint model with respect to the existing non diffusive ones is that it allows calibration without the equicorrelation assumption, but still in a parsimonious way. As an example of the default assessments which the calibrated model can provide, we price a FtD swap.
    Keywords: credit risk, structural models, Lévy asset prices, default probability, joint default.
    JEL: G32 G12
    Date: 2007
  7. By: Cifter, Atilla; Ozun, Alper
    Abstract: In this study, variance changing to the scale and multi-scale Capital Asset Pricing Model (CAPM) is tested by Wavelets as a new analysis method in finance and economics. It introduces a new approach to the variance changing to the scale as a general risk indicator, and to multi-scale CAPM portfolio theory as a systematic risk indicator. In the study, variance changes to scale and systematic risk changes to scale of 10 stocks in ISE-30 have been determined. The ability of the investors to conduct risk based analysis up to 128 days allows them to determine the risk level to the scale (stock holding period). According to the study results; it is determined that the variances of 10 stocks from ISE 30 change according to the scale and variance differentiation as an expression of general risk level increase starting from the 1st scale (1 to 4 days). In multi-scale CAPM, it is determined that systematic risk of all stocks is changed to frequency (scale) and increased at higher scales. The finding as to beta and return at the high levels shall be in stronger form evidenced by Gencay et al (2005) is determined as not applicable to ISE 30. The risk and return for ISE 30 are close to the positive in the 3rd scale (32 days), but they are in the same direction for the other scales. This finding shows that the risk-return maximization of a portfolio of 10 stocks from ISE may be achieved at a level of 32 days and the risk will be higher than the return in the portfolios established at those levels different than 32 days.
    Keywords: Multiscale systematic risk; CAPM; wavelets; multiscale variance
    JEL: G0 G1
    Date: 2007–03–01
  8. By: Renatas Kizys (Department of Economics and Related Studies, University of York); Peter Spencer (Department of Economics and Related Studies, University of York)
    Abstract: In this paper, we used modified multivariate EGARCH-M models to assess the relation between the equity risk premium, macroeconomic risk, and inflationary expectations. To rationalise this link between equity risk premia and macroeconomic volatilities, we built our empirical study on the stochastic discount factor (SDF) model. As an innovative feature of our empirical model, we used long-term government bond yields in order to explain this risk-return relation. Our research suggests that stock market investors should use long-term government bond yield for the UK and term spread for the US in order to instrument their assessment of stock market investment opportunities and riskiness. We also document that the relevance of the short-term interest rates has decreased over the last decade, whereas the relevance of the long-term government bond yields, by contrast, has increased. With regard to the risk-return relation, we found the UK investors tend to significantly price in inflation risk premia. Estimation results strongly suggest that the decline in macroeconomic volatilities might have played an increasingly important role in reducing risk premia in the US and, to some extent, in the UK
    Keywords: Asset pricing, Risk premium, Macroeconomic volatility, Stochastic discount factor model, Multivariate EGARCH-M model
    JEL: E32 E44 G12
    Date: 2007–02–02
  9. By: Alejandro García; Ramazan Gençay
    Abstract: We propose a framework that allows a portfolio manager to quantify the probability of simultaneous losses in multiple assets of a collateral portfolio. Using this framework, we propose a methodology to conduct stress tests on the market value of the portfolio of collateral when undesirable extreme dependence occurs. This framework permits us to quantify the potential impact on the portfolio returns of systemic events that change, or 'break down', the historical comovement structure, imposing an adverse extreme dependence.We illustrate our framework using securities pledged as collateral in the Canadian securities clearing and settlement system.
    Keywords: Econometric and statistical methods; Financial markets; Financial stability
    JEL: G00 G10 C10
    Date: 2007
  10. By: Virginie Coudert; Mathieu Gex
    Abstract: Financial institutions often refer to empirical risk aversion indicators to gauge investors’ market sentiment. Fluctuations in risk aversion are generally considered as a factor explaining crises. Periods of strong risk appetite can create speculative bubbles on financial prices, building up vulnerabilities. Then a sudden reversal in risk aversion may trigger sharp falls in asset prices and prompt a financial crisis. A crucial point is to clearly define the concept of risk aversion. In the framework of asset pricing models, more precisely the Consumption CAPM (CCAPM), a risk premium can be decomposed into a “price of risk”, which is common to all assets, and a “quantity of risk”, which is specific to each asset. The empirical indicators of risk aversion used by financial institutions aim at assessing this “price of risk”. Those empirical indicators can be put together in four main groups. 1) The indicators of the GRAI (Global Risk Aversion Index) type are based on the idea that an increase in risk aversion should lead to a rise in risk premia across all markets, but the rise should be greater on the riskiest markets (Persaud, 1996, Kumar and Persaud, 2002). By using the CAPM, regarded as a special case of the CCAPM, this idea amounts to assessing changes in risk aversion as the correlation between price changes and their volatility. 2) Risk aversion can also be estimated as the common factor driving risk premia. This common factor can be evaluated through a factor analysis such as the Principal Component Analysis (PCA). 3) Some financial institutions also use raw series, as the VIX which is the implied volatility on the S&P 500, or combinations of raw series. 4) There are also other indicators, such as the State Street’s one which does not fall into the previous categories.
    Keywords: Risk aversion; leading indicators of crises; currency crises; stock market crises; crises prediction; models; financial markets; crisis
    JEL: C33 E44 F37 G12
    Date: 2007–01
  11. By: Laurent Gheeraert (Centre Emile Bernheim, Solvay Business School, Université Libre de Bruxelles, Brussels.)
    Abstract: With a double-digit growth rate in total market capitalization over the last decade, emerging stocks are becoming an increasingly important investment category. Emerging market equities behave in a different way from equities traded on developed capital markets. In the literature, there is usually a consensus on at least four distinguishing features of emerging market stock returns: (1) volatility is high, (2) correlations with developed market returns are low, (3) returns are predictable to a certain extent, (4) third and fourth moments matter. However, opinions differ about average attractiveness of realized returns in emerging markets, depending on the period studied, the region, and the methodologies. This paper surveys the wide literature around marginal and expected moments of the distribution of emerging stock returns. It reviews literature findings in a structure per statistical moment. Then, it examines the potential consequences on the applicability of the CAPM in emerging markets. Finally,it exposes avenues for further research identified from the survey.
    Keywords: emerging stock markets, equity returns, investment, moments.
    JEL: G15 G11 F30
    Date: 2006–09
  12. By: Rafael R. Rebitzky (University of Hannover)
    Abstract: Foreign exchange markets have to deal next to hard facts with lots of expectations and emo-tions. One of the major puzzles in international finance remains the “exchange rate discon-nect puzzleâ€. Analyzing sentiment in foreign exchange markets, it appears in fact that senti-ment contains some forward looking information. Particularly due to the unknown economic relevance of sentiment in foreign exchange markets so far, we first analyze the relationship between fundamentals and sentiment in order to reveal underlying forces of the latter; sec-ond we accomplish our analysis by concentrating on popular expectation concepts and con-sidering threshold effects. Third, we evaluate sentiment by testing on accuracy and on for-ward looking elements of subsequent exchange rate returns
    Keywords: Foreign exchange market, sentiment, bootstrap, threshold
    JEL: G14 F31
    Date: 2007–02–02

General information on the NEP project can be found at For comments please write to the director of NEP, Marco Novarese at <>. Put “NEP” in the subject, otherwise your mail may be rejected.
NEP’s infrastructure is sponsored by the School of Economics and Finance of Massey University in New Zealand.