New Economics Papers
on Risk Management
Issue of 2010‒05‒29
nine papers chosen by



  1. Balance Sheet Network Analysis of Too-Connected-to-Fail Risk in Global and Domestic Banking Systems By Jorge A. Chan-Lau
  2. Value-at-Risk for Country Risk Ratings By Michael McAleer; Bernardo da Veiga; Suhejla Hoti
  3. Deriving the term structure of banking crisis risk with a compound option approach: The case of Kazakhstan By Eichler, Stefan; Karmann, Alexander; Maltritz, Dominik
  4. Multivariate heavy-tailed models for Value-at-Risk estimation By Carlo Marinelli; Stefano d'Addona; Svetlozar T. Rachev
  5. Cross-Border Financial Surveillance: A Network Perspective By Marco Espinosa-Vega; Juan Sole
  6. Asset Pair-Copula Selection with Downside Risk Minimization By Jin Zhang; Dietmar Maringer
  7. Risk and return dynamics. By Cosemans, Mathijs Maria Jacobus Elisabeth
  8. Liquidity and Capital Requirements and the Probability of Bank Failure By Philipp Johann König
  9. Modelling Stock Returns Volatility In Nigeria Using GARCH Models By Emenike, Kalu O.

  1. By: Jorge A. Chan-Lau
    Abstract: The 2008/9 financial crisis highlighted the importance of evaluating vulnerabilities owing to interconnectedness, or Too-Connected-to-Fail risk, among financial institutions for country monitoring, financial surveillance, investment analysis and risk management purposes. This paper illustrates the use of balance sheet-based network analysis to evaluate interconnectedness risk, under extreme adverse scenarios, in banking systems in mature and emerging market countries, and between individual banks in Chile, an advanced emerging market economy.
    Keywords: Bank accounting , Banking systems , Capital , Credit risk , Developed countries , Emerging markets , Financial institutions , Financial risk , Globalization , International banking , Risk management ,
    Date: 2010–04–27
    URL: http://d.repec.org/n?u=RePEc:imf:imfwpa:10/107&r=rmg
  2. By: Michael McAleer (University of Canterbury); Bernardo da Veiga; Suhejla Hoti
    Abstract: The country risk literature argues that country risk ratings have a direct impact on the cost of borrowings as they reflect the probability of debt default by a country. An improvement in country risk ratings, or country creditworthiness, will lower a country’s cost of borrowing and debt servicing obligations, and vice-versa. In this context, it is useful to analyse country risk ratings data, much like financial data, in terms of the time series patterns, as such an analysis would provide policy makers and the industry stakeholders with a more accurate method of forecasting future changes in the risks and returns of country risk ratings. This paper considered an extension of the Value-at-Risk (VaR) framework where both the upper and lower thresholds are considered. The purpose of the paper was to forecast the conditional variance and Country Risk Bounds (CRBs) for the rate of change of risk ratings for ten countries. The conditional variance of composite risk returns for the ten countries were forecasted using the Single Index (SI) and Portfolio Methods (PM) of McAleer and da Veiga [10,11]. The results suggested that the country risk ratings of Switzerland, Japan and Australia are much mode likely to remain close to current levels than the country risk ratings of Argentina, Brazil and Mexico. This type of analysis would be useful to lenders/investors evaluating the attractiveness of lending/investing in alternative countries.
    Keywords: Country risk; risk ratings; value-at-risk; risk bounds; risk management
    Date: 2010–05–01
    URL: http://d.repec.org/n?u=RePEc:cbt:econwp:10/29&r=rmg
  3. By: Eichler, Stefan; Karmann, Alexander; Maltritz, Dominik
    Abstract: We use a compound option-based structural credit risk model to infer a term structure of banking crisis risk from market data on bank stocks in daily frequency. Considering debt service payments with different maturities this term structure assigns a separate estimator for short- and long-term default risk to each maturity. Applying the Duan (1994) maximum likelihood approach, we find for Kazakhstan that the overall crisis probability was mainly driven by short-term risk, which increased from 25% in March 2007 to 80% in December 2008. Concurrently, the long-term default risk increased from 20% to only 25% during the same period. --
    Keywords: Banking crisis,bank default,option pricing theory,compound option,liability structure
    JEL: G21 G32 G12 G18
    Date: 2010
    URL: http://d.repec.org/n?u=RePEc:zbw:bubdp2:201001&r=rmg
  4. By: Carlo Marinelli; Stefano d'Addona; Svetlozar T. Rachev
    Abstract: For purposes of Value-at-Risk estimation, we consider three multivariate families of heavy-tailed distributions, which can be seen as multidimensional versions of Paretian stable and Student's t distributions allowing different marginals to have different tail thickness. After a discussion of relevant estimation and simulation issues, we conduct a backtesting study on a set of portfolios containing derivative instruments, using historical US stock price data.
    Date: 2010–05
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1005.2862&r=rmg
  5. By: Marco Espinosa-Vega; Juan Sole
    Abstract: Effective cross-border financial surveillance requires the monitoring of direct and indirect systemic linkages. This paper illustrates how network analysis could make a significant contribution in this regard by simulating different credit and funding shocks to the banking systems of a number of selected countries. After that, we show that the inclusion of risk transfers could modify the risk profile of entire financial systems, and thus an enriched simulation algorithm able to account for risk transfers is proposed. Finally, we discuss how some of the limitations of our simulations are a reflection of existing information and data gaps, and thus view these shortcomings as a call to improve the collection and analysis of data on cross-border financial exposures.
    Keywords: Bank credit , Banking systems , Chile , Credit risk , Cross country analysis , Economic models , External shocks , Financial crisis , Financial risk , Financial sector , Global Financial Crisis 2008-2009 , Risk management ,
    Date: 2010–04–23
    URL: http://d.repec.org/n?u=RePEc:imf:imfwpa:10/105&r=rmg
  6. By: Jin Zhang; Dietmar Maringer
    Abstract: Copulae provide investors with tools to model the dependency structure among financial products. The choice of copulae plays an important role in successful copula applications. However, selecting copulae usually relies on general goodness-of-fit (GoF) tests which are independent of the particular financial problem. This paper ¯rst proposes a pair-copula-GARCH model to construct the dependency structure and simulate the joint returns of five U.S. equites. It then discusses copula selection problem from the perspective of downside risk management with the so-called D-vine structure, which considers the Joe-Clayton copula and the Student t copula as building blocks for the vine pair-copula decomposition. Value at risk, expected shortfall, and Omega function are considered as downside risk measures in this study. As an alternative to the traditional bootstrap approaches, the proposed pair-copula-GARCH model provides simulated asset returns for generating future scenarios of portfolio value. It is found that, although the Student t pair-copula system performs better than the Joe-Clayton system in a GoF test, the latter is able to provide the loss distributions which are more consistent with the empirically examined loss distributions while optimizing the Omega ratio. Furthermore, the economic benefit of using the pair-copula-GARCH model is revealed by comparing the loss distributions from the proposed model and the conventional exponentially weighted moving average model of RiskMetrics in this case.
    Keywords: Downside Risk, AR-TGARCH, Pair-Copula, Vine Structure, Differential Evolution
    Date: 2010–05–17
    URL: http://d.repec.org/n?u=RePEc:com:wpaper:037&r=rmg
  7. By: Cosemans, Mathijs Maria Jacobus Elisabeth (Maastricht University)
    Date: 2010
    URL: http://d.repec.org/n?u=RePEc:ner:maastr:urn:nbn:nl:ui:27-22752&r=rmg
  8. By: Philipp Johann König
    Abstract: Using the model of Rochet and Vives (2004), this note shows that a prudential regulator can in general not mitigate a bank’s failure risk solely by means of liquidity requirements. However, their effectiveness can be restored if, in addition, minimum capital requirements are met. This provides a rationale for capital requirements beyond the commonly envoked reasoning that they are to be used to control the riskiness of banks’ asset portfolios.
    Keywords: prudential regulation, liquidity requirements, minimum capital requirements, global games
    JEL: G21 G28
    Date: 2010–05
    URL: http://d.repec.org/n?u=RePEc:hum:wpaper:sfb649dp2010-027&r=rmg
  9. By: Emenike, Kalu O.
    Abstract: There is quite an extensive literature documenting the behaviour of stock returns volatility in both developed and emerging stock markets, but such studies are scanty for the Nigerian Stock Exchange (NSE). Modelling volatility is an important element in pricing equity, risk management and portfolio management. For these reasons, this paper investigates the behaviour of stock return volatility of the Nigerian Stock Exchange returns using GARCH (1,1) and the GJR-GARCH(1,1) models assuming the Generalized Error Distribution (GED). Monthly All Share Indices of the NSE from January 1999, to December 2008, provided the empirical sample for investigating volatility persistence and asymmetric properties of the series. The results of GARCH (1,1) model indicate evidence of volatility clustering in the NSE return series. Also, the results of the GJR-GARCH (1,1) model show the existence of leverage effects in the series. Finally, the Generalized Error Distribution (GED) shape test reveals leptokurtic returns distribution. Overall results from this study provide evidence to show volatility persistence, fat-tail distribution, and leverage effects for the Nigeria stock returns data.
    Keywords: Modeling; Volatility; Stock Returns; GARCH Models; Nigerian Stock Exchange
    JEL: C52 C22 G10
    Date: 2010–01–15
    URL: http://d.repec.org/n?u=RePEc:pra:mprapa:22723&r=rmg

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