nep-rmg New Economics Papers
on Risk Management
Issue of 2006‒12‒01
nine papers chosen by
Stan Miles
Thompson Rivers University

  1. Comparing Value-at-Risk Methodologies By Luiz Renato Regis de Oliveira Lima; Breno de Andrade Pinheiro Neri
  2. Recovery Rates, Default Probabilities and the Credit Cycle By Carlos González-Aguado; Max Bruche
  3. On Estimating an Assett's Implicit Beta By Sven Husmann; Andreas Stephan
  4. Does Credit Risk Vary with Economic Cycles? The Case of Finland By Petr Jakubík
  5. Modeling and forecasting the volatility of Brazilian asset returns By MArcelo Carvalho; MArco Aurelio Freire; Marcelo Cunha Medeiros; Leonardo Souza
  6. On a relationship between distorted and spectral risk measures By Henryk, Gzyl; Silvia, Mayoral
  7. What drives the market value of firms in the Defense industry ? By Gunther Capelle-Blancard; Nicolas Couderc
  8. Using Option Theory to Estimate Default Probabilities of Brazilian Companies By Minardi, Andrea Maria Accioly Fonseca
  9. Value at Risk yang memperhatikan sifat statistika distribusi return By Situngkir, Hokky

  1. By: Luiz Renato Regis de Oliveira Lima (EPGE/FGV); Breno de Andrade Pinheiro Neri
    Date: 2006–11
  2. By: Carlos González-Aguado; Max Bruche
    Abstract: Recovery rates are negatively related to default probabilities (Altman et al.,2005). This paper proposes and estimates a model in which this dependence is the result of an unobserved credit cycle: When times are bad, the default probability is high and recovery rates are low; when times are good, the default probability is low and recovery rates are high. The proposed dynamic model is shown to produce a better fit to the data than a standard static approach. It indicates that ignoring the dynamic nature of credit risk could lead to a severe underestimation of credit risk (e.g. by a factor of up to 1.7 in terms of the 95% VaR). Also, the model indicates that the credit cycle is related to but distinct from the business cycle as e.g. determined by the NBER, which might explain why previous studies have found the power of macroeconomic variables in explaining default probabilities and recoveries to be low.
    Date: 2006–11
  3. By: Sven Husmann; Andreas Stephan
    Abstract: Siegel (1995) has developed a technique with which the systematic risk of a security (beta) can be estimated without recourse to historical capital market data. Instead, beta is estimated implicitly from the current market prices of exchange options that enable the exchange of a security against shares on the market index. Because this type of exchange options is not currently traded on the capital markets, Siegel's technique cannot yet be used in practice. This article will show that beta can also be estimated implicitly from the current market prices of plain vanilla options, based on the Capital Asset Pricing Model. We provide empirical evidence on implicit betas using prices of exchange options from the EUREX over years 2000 to 2004.
    Keywords: Capital Asset Pricing Model; Beta; Option Pricing.
    JEL: G12
    Date: 2006
  4. By: Petr Jakubík (Institute of Economic Studies, Faculty of Social Sciences, Charles University, Prague, Czech Republic; Czech National Bank, Prague, Czech Republic)
    Abstract: The significance of credit risk models has increased with the introduction of new Basel accord known as Basel II. The aim of this study is default rate modeling. This paper follows the two possible approaches of a macro credit risk modeling. First, empirical models are investigated. Second, a latent factor model based on Merton's idea is introduced. Both of these models are derived from individual default probability models. We employed data over the time period from 1988 to 2003 of the Finnish economy. First, linear vector autoregressive models were used in the case of dynamic empirical model. We examined how significant macroeconomic indicators determined the default rate in the economy. However these models cannot provide microeconomic foundation as latent factor models. A one-factor model was estimated using disaggregated industrial data. This estimation can help understand relation between credit risk and macroeconomic indicators. Models can be used for default rate prediction or stress testing by central authorities.
    Keywords: banking; credit risk; latent factor model; default rate
    JEL: G21 G28 G33
    Date: 2006–04
    Abstract: The goal of this paper is twofold. First, using five of the most actively traded stocks in the Brazilian financial market, this paper shows that the normality assumption commonly used in the risk management area to describe the distributions of returns standardized by volatilities is not compatible with volatilities estimated by EWMA or GARCH models. In sharp contrast, when the information contained in high frequency data is used to construct the realized volatility measures, we attain the normality of the standardized returns, giving promise of improvements in Value-at-Risk statistics. We also describe the distributions of volatilities of the Brazilian stocks, showing that they are nearly lognormal. Second, we estimate a simple model to the log of realized volatilities that differs from the ones in other studies. The main difference is that we do not find evidence of long memory. The estimated model is compared with commonly used alternatives in an out-of-sample forecasting experiment.
    Date: 2006–11
  6. By: Henryk, Gzyl; Silvia, Mayoral
    Abstract: We study the relationship between two widely used risk measures, the spectral measures and the distortion risk measures. In both cases, the risk measure can be thought of as a re-weighting of some initial distribution. We prove that spectral risk measures are equivalent to distorted risk pricing measures, or equivalently, spectral risk functions are related to distortion functions. Besides that we prove that distorted measures are absolutely continuous with respect to the original measure.
    Keywords: Coherent risk measure; distortion function; Spectral measures; Risk Aversion Function.
    JEL: G11
    Date: 2006–11
  7. By: Gunther Capelle-Blancard (EconomiX - [CNRS : UMR7166] - [Université de Paris X - Nanterre], CES - Centre d'économie de la Sorbonne - [CNRS : UMR8174] - [Université Panthéon-Sorbonne - Paris I]); Nicolas Couderc (CES - Centre d'économie de la Sorbonne - [CNRS : UMR8174] - [Université Panthéon-Sorbonne - Paris I])
    Abstract: This paper investigates the relative importance of different types of news in driving significant stock price changes of firms in the defense industry. We implement a systematic event study with a sample of the 58 largest publicly listed companies in the defense industry, over the time period 1995-2005. We first identify, for each firm, the statistically significant abnormal returns over the time period, and then we look for information releases likely to cause such stock price movements. We find that stock price movements in the defense industry are, in many ways, influenced by the same events as in other industries (key role of formal earnings announcements or analysts' recommendations) but this industry also has some specific features, in particular the influence of geopolitical events and the relevance and frequency of bids and contracts on stock prices.
    Keywords: Event study, financial markets, defense industry, information releases, GARCH models.
    Date: 2006–11–22
  8. By: Minardi, Andrea Maria Accioly Fonseca
    Date: 2006–10
  9. By: Situngkir, Hokky
    Abstract: Basel II Accord secara implisit menuntut penggunaan berbagai perangkat statistika yang paling mutakhir dalam analisis risiko dalam analisis keuangan. Salah satu aspek yang sering menjadi perhatian adalah analisis risiko pada sistem keuangan, dalam hal ini perhitungan Value at Risk. Pendekatan VaR yang konvensional cenderung lebih terkait dengan asumsi distribusi normal sementara penemuan empiris kontemporer menunjukkan adanya pola ketaknormalan dalam sifat statistika data-data keuangan. Dalam makalah ini, penulis menunjukkan perbandingan dua metodologi perhitungan VaR: yang menggunakan standar normalitas dan yang memperhitungkan dua momen statistika lain dari data keuangan, yaitu skewness dan kelebihan kurtosis. Hasil simulasi menunjukkan bahwa metodologi terakhir menunjukkan akurasi perhitungan yang lebih baik daripada pendekatan tradisional.
    JEL: D81 G32 C53 G24 G21
    Date: 2006–04–27

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