New Economics Papers
on Risk Management
Issue of 2013‒08‒16
six papers chosen by

  1. The systemic risk of European banks during the financial and sovereign debt crises By Lamont Black; Ricardo Correa; Xin Huang; Hao Zhou
  2. Systemic Risk Measures By Solange Maria Guerra; Benjamin Miranda Tabak; Rodrigo Andrés de Souza Penaloza; Rodrigo César de Castro Miranda
  3. Contagion Risk within Firm-Bank Bivariate Networks By Rodrigo César de Castro Miranda; Benjamin Miranda Tabak
  4. Optimal Dynamic Portfolio with Mean-CVaR Criterion By Jing Li; Mingxin Xu
  5. Rollover risk and corporate bond spreads By Patricio Valenzuela
  6. Estimation of flexible fuzzy GARCH models for conditional density estimation By Almeida, R.J.; Basturk, N.; Kaymak, U.; Costa Sousa, J.M. da

  1. By: Lamont Black; Ricardo Correa; Xin Huang; Hao Zhou
    Abstract: We propose a hypothetical distress insurance premium (DIP) as a measure of the European banking systemic risk, which integrates the characteristics of bank size, default probability, and interconnectedness. Based on this measure, the systemic risk of European banks reached its height in late 2011 around € 500 billion. We find that the sovereign default spread is the factor driving this heightened risk in the banking sector during the European debt crisis. The methodology can also be used to identify the individual contributions of over 50 major European banks to the systemic risk measure. This approach captures the large contribution of a number of systemically important European banks, but Italian and Spanish banks as a group have notably increased their systemic importance. We also find that bank-specific fundamentals predict the one-year-ahead systemic risk contribution of our sample of banks in an economically meaningful way.
    Date: 2013
  2. By: Solange Maria Guerra; Benjamin Miranda Tabak; Rodrigo Andrés de Souza Penaloza; Rodrigo César de Castro Miranda
    Abstract: In this paper we present systemic risk measures based on contingent claims approach, banking sector multivariate density and cluster analysis. These indicators aim to capture credit risk stress and its potential to become systemic. The proposed measures capture not only individual bank vulnerability, but also the stress dependency structure between them. Furthermore, these measures can be quite useful for identifying systematically important banks. The empirical results show that these indicators capture with considerable fidelity the moments of increasing systemic risk in the Brazilian banking sector in recent years.
    Date: 2013–08
  3. By: Rodrigo César de Castro Miranda; Benjamin Miranda Tabak
    Abstract: This paper proposes a novel way to model a network of firm-bank and bank-bank interrelationships using a unique dataset for the Brazilian economy. We show that distress originating from firms can be propagated through the interbank network. Furthermore, we present evidence that the distribution of distress can have contagious effects due to correlated exposures. Our modeling approach and empirical results provide useful tools and information for policy makers and contribute to the discussion on assessing systemic risk in an interconnected world.
    Date: 2013–08
  4. By: Jing Li; Mingxin Xu
    Abstract: Value-at-Risk (VaR) and Conditional Value-at-Risk (CVaR) are popular risk measures from academic, industrial and regulatory perspectives. The problem of minimizing CVaR is theoretically known to be of Neyman-Pearson type binary solution. We add a constraint on expected return to investigate the Mean-CVaR portfolio selection problem in a dynamic setting: the investor is faced with a Markowitz type of risk reward problem at final horizon where variance as a measure of risk is replaced by CVaR. Based on the complete market assumption, we give an analytical solution in general. The novelty of our solution is that it is no longer Neyman-Pearson type where the final optimal portfolio takes only two values. Instead, in the case where the portfolio value is required to be bounded from above, the optimal solution takes three values; while in the case where there is no upper bound, the optimal investment portfolio does not exist, though a three-level portfolio still provides a sub-optimal solution.
    Date: 2013–08
  5. By: Patricio Valenzuela
    Abstract: Using a new data set on corporate bonds placed in international markets by advanced and emerging market borrowers, this paper demonstrates that the impact of debt market illiquidity on corporate bond spreads is exacerbated with a higher proportion of short-term debt. This effect is stronger in speculative-grade bonds and is smaller in the banking sector as banks may have the support of a lender of last resort in times of debt market illiquidity. The paper's major finding is consistent with the predictions of structural credit risk models that argue that a higher proportion of short-term debt increases the firm's exposure to debt market illiquidity through a 'rollover risk' channel.
    Date: 2013
  6. By: Almeida, R.J.; Basturk, N.; Kaymak, U.; Costa Sousa, J.M. da
    Abstract: In this work we introduce a new flexible fuzzy GARCH model for conditional density estimation. The model combines two different types of uncertainty, namely fuzziness or linguistic vagueness, and probabilistic uncertainty. The probabilistic uncertainty is modeled through a GARCH model while the fuzziness or linguistic vagueness is present in the antecedent and combination of the rule base system. The fuzzy GARCH model under study allows for a linguistic interpretation of the gradual changes in the output density, providing a simple understanding of the process. Such a system can capture different properties of data, such as fat tails, skewness and multimodality in one single model. This type of models can be useful in many fields such as macroeconomic analysis, quantitative finance and risk management. The relation to existing similar models is discussed, while the properties, interpretation and estimation of the proposed model are provided. The model performance is illustrated in simulated time series data exhibiting complex behavior and a real data application of volatility forecasting for the S&P 500 daily returns series.
    Keywords: Linguistic descriptions; Volatility forecasting;Conditional density estimation;Fuzzy GARCH models
    Date: 2013–07–31

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