nep-rmg New Economics Papers
on Risk Management
Issue of 2007‒06‒30
nine papers chosen by
Stan Miles
Thompson Rivers University

  1. Sophistication in Risk Management, Bank Equity, and Stability By Gersbach, Hans; Wenzelburger, Jan
  2. Asset liquidity, debt valuation and credit risk By Ethan Cohen-Cole
  3. Robust Bayesian Analysis of Loss Reserves Data Using the Generalized-t Distribution By Jennifer Chan; Boris Choy; Udi Makov
  4. Volatility forecasting for crude oil futures By Marzo, Massimiliano; Zagaglia, Paolo
  5. How useful are historical data for forecasting the long-run equity return distribution? By John M Maheu; Thomas H McCurdy
  6. Stock-bond correlation and the bond quality ratio: Removing the discount factor to generate a “deflated” stock index By Andrea Terzi; Giovanni Verga
  7. Conditional Leptokurtosis in Energy Prices: Multivariate Evidence from Futures Markets By Marzo, Massimiliano; Zagaglia, Paolo
  8. Market Impact of International Sporting and Cultural Events By António Miguel Martins; Ana Paula Serra
  9. Fiscal Policy and Default Risk in Emerging Markets. By Gabriel Cuadra; Horacio Sapriza

  1. By: Gersbach, Hans; Wenzelburger, Jan
    Abstract: We investigate the question of whether sophistication in risk management fosters banking stability. We compare a simple banking system in which an average rating is used with a sophisticated banking system in which banks are able to assess the default risk of entrepreneurs individually. Both banking systems compete for deposits, loans, and bank equity. While a sophisticated system rewards entrepreneurs with low default risks by low loan interest rates, a simple system acquires more bank equity and finances more entrepreneurs. Expected repayments in a simple system are always higher and its default risk is lower if productivity is sufficiently high. Expected aggregate consumption of entrepreneurs, however, is higher in a sophisticated banking system.
    Keywords: banking regulation; Financial intermediation; macroeconomic risks; rating; risk management; risk premia
    JEL: D40 E44 G21
    Date: 2007–06
  2. By: Ethan Cohen-Cole
    Abstract: This paper presents a structural debt valuation model that links default probabilities and recovery rates of corporate securities to asset market liquidity. This linking is advantageous for risk management and regulation of financial institutions in that it provides a method of calibrating the relationship between probability of default (PD) and loss given default (LGD). Two innovations in the paper are the placing of the default point in a model of debt valuation into general equilibrium and conditioning this point on market factors such as asset liquidity. These allow one to derive implications on the correlation between various components of the model. Specifically, it finds two relationships between the probability of default (PD) and loss given default (LGD) of a debt instrument; temporal correlations are positive and cross-sectional ones negative. Such findings confirm the intuition of existing reduced form approaches and provide the ability to inspect other properties of the relationship that derive from theory. For example, one can use the model to forecast LGD. Some empirical validation of the theoretical results is provided.
    Keywords: Securities ; Default (Finance)
    Date: 2007
  3. By: Jennifer Chan (University of Sydney); Boris Choy (Department of Mathematical Sciences, University of Technology, Sydney); Udi Makov (University of Haifa)
    Abstract: This paper presents a Bayesian approach using Markov chain Monte Carlo methods and the generalized-t (GT) distribution to predict loss reserves for the insurance companies. Existing models and methods cannot cope with irregular and extreme claims and hence do not offer an accurate prediction of loss reserves. To develop a more robust model for irregular claims, this paper extends the conventional normal error distribution to the GT distribution which nests several heavytailed distributions including the Student-t and exponential power distributions. It is shown that the GT distribution can be expressed as a scale mixture of uniforms (SMU) distribution which facilitates model implementation and detection of outliers by using mixing parameters. Different models for the mean function, including the log-ANOVA, log-ANCOVA, state space and threshold models, are adopted to analyze real loss reserves data. Finally, the best model is selected according to the deviance information criterion (DIC).
    Keywords: Bayesian approach; state space model; threshold model; scale mixtures of uniform distribution; device information criterion
    Date: 2007–05–01
  4. By: Marzo, Massimiliano (Department of Economics, Universit`a di Bologna); Zagaglia, Paolo (Dept. of Economics, Stockholm University)
    Abstract: This paper studies the forecasting properties of linear GARCH models for closing-day futures prices on crude oil, first position, traded in the New York Mercantile Exchange from January 1995 to November 2005. In order to account for fat tails in the empirical distribution of the series, we compare models based on the normal, Student’s t and Generalized Exponential distribution. We focus on out-of-sample predictability by ranking the models according to a large array of statistical loss functions. The results from the tests for predictive ability show that the GARCH-G model fares best for short horizons from one to three days ahead. For horizons from one week ahead, no superior model can be identified. We also consider out-of-sample loss functions based on Value-at-Risk that mimic portfolio managers and regulators’ preferences. EGARCH models display the best performance in this case.
    Keywords: GARCH models; kurtosis; oil prices; forecasting
    JEL: C22 G19
    Date: 2007–06–21
  5. By: John M Maheu; Thomas H McCurdy
    Abstract: We provide an approach to forecasting the long-run (unconditional) distribution of equity returns making optimal use of historical data in the presence of structural breaks. Our focus is on learning about breaks in real time and assessing their impact on out-of-sample density forecasts. Forecasts use a probability-weighted average of submodels, each of which is estimated over a different history of data. The paper illustrates the importance of uncertainty about structural breaks and the value of modeling higher-order moments of excess returns when forecasting the return distribution and its moments. The shape of the long-run distribution and the dynamics of the higher-order moments are quite different from those generated by forecasts which cannot capture structural breaks. The empirical results strongly reject ignoring structural change in favor of our forecasts which weight historical data to accommodate uncertainty about structural breaks. We also strongly reject the common practice of using a fixed-length moving window. These differences in long-run forecasts have implications for many financial decisions, particularly for risk management and long-run investment decisions.
    Keywords: density forecasts, structural change, model risk, parameter uncertainty, Bayesian learning, market returns
    JEL: C51 C53 C11
    Date: 2007–06–28
  6. By: Andrea Terzi (DISCE, Università Cattolica); Giovanni Verga (Università di Parma)
    Abstract: This paper investigates the cyclical co-movements between US stocks and interest rates by testing a simple model where divergence between stock and bond price behavior is explained by “stock market strength,” where the latter depends on the market climate about future corporate profits—as captured by the corporate bond quality ratio—and an unexplained stock market sentiment. Using two different regression techniques to check for robustness, we find evidence of a statistically significant cyclical correlation between stocks and bonds. On the basis of this finding, we then present a methodology to “deflate” a stock price index such that we can compare stock market strength over time. This is obtained by removing the effect of a changing discount rate—as measured by our regressions—on stock prices. For example, viewed in this light, the past five years in the US stock market reveal a wider fluctuation in stock market strength than we can observe on the basis of stock price indices alone.
    Keywords: Stock-bond correlation, Market sentiment, Stock price.
    JEL: D84 G12 G14
    Date: 2006–09
  7. By: Marzo, Massimiliano (Department of Economics, Universit`a di Bologna); Zagaglia, Paolo (Dept. of Economics, Stockholm University)
    Abstract: We study the joint movements of the returns on futures for crude oil, heating oil and natural gas at a daily frequency. We model the leptokurtic behavior through the multivariate GARCH with dynamic conditional correlations and elliptical distributions introduced by Pelagatti and Rondena (2004). Futures prices of crude and heating oil co-vary strongly. The correlation between the futures prices of natural gas and crude oil has been rising over the last 5 years. However, this correlation has been low on average over two thirds of the sample, indicating that futures markets have no established tradition of pricing natural gas as a function of developments on oil markets.
    Keywords: Multivariate GARCH; Kurtosis; Energy Prices; Futures Markets
    JEL: C22 G19
    Date: 2007–06–27
  8. By: António Miguel Martins (Faculdade de Economia da Universidade do Porto); Ana Paula Serra (Faculdade de Economia da Universidade do Porto)
    Abstract: This paper investigates the impact of international sporting and cultural events on national stock markets. We study market reaction to the announcements of the selected country hosting the Summer and Winter Olympic Games, the World Football Cup, the European Football Cup and World and Specialized Exhibitions. We also measure the market effects of the announcement of the nomination of the European Cultural City. First, we evaluate the abnormal returns of winning bidders at (and around) the announcement date using an event study methodology. We study the impact at market and industry-levels. Second, we analyze the determinants of the variation in abnormal returns across events and industries on the basis of a set of variables found important by previous studies and control for the prior probability of observing the event. Third, on the basis of a simple model of partial anticipation, we reexamine the abnormal returns observed for the winning and losing countries and perform a series of tests to disentangle the different theoretical arguments that could account for the observed stock market behavior. Our initial results suggest that the abnormal returns measured at the announcement date and around the event are not consistently different from zero. Further, when we look at particular industries, we find no evidence supporting that industries, that a priori were more likely to extract direct benefits from the event, observe positive significant effects. Yet when we control for the prior expectations, the announcement of these mega-events is associated with a positive market reaction in the nominated country and a negative reaction in the losing country. Overall we interpret our findings as supportive of rational asset pricing and partial anticipation.
    Keywords: Market efficiency; Event studies; Mega-events
    JEL: G31 G14 L83
    Date: 2007–06
  9. By: Gabriel Cuadra; Horacio Sapriza
    Abstract: Emerging economies usually experience procyclical public expenditures, tax rates and private consumption, countercyclical default risk, interest rate spreads and current account and higher volatility in consumption than in output. In this article we develop a dynamic stochastic equilibrium model of a small open economy with endogenous fiscal policy, endogenous default risk and country interest rate spreads in an incomplete credit markets framework that rationalizes these empirical findings.
    Keywords: Procyclical fiscal policy, Sovereign default
    JEL: F34 F41
    Date: 2007–03

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