New Economics Papers
on Risk Management
Issue of 2014‒06‒14
eleven papers chosen by

  1. Complex Financial Networks and Systemic Risk: A Review By Spiros Bougheas; Alan Kirman
  2. Carrying the (paper) burden: A portfolio view of systemic risk and optimal bank size By Bos J.W.B.; Lamers M.A.J.; Purice V.
  3. Riesgo Agropecuario: Incidencia Económica e Innovaciones para su mitigación. El caso de Argentina. By Miguel, Fusco; Dario, Bacchini; Esteban Otto, Thomasz
  4. Collateral Composition, Diversification Risk, and Systemically Important Merchant Banks By Alexis Derviz
  5. Proportional loss functions for debris flow events By Christoph Rheinberger; Hans E. Romang; Michael Bründl
  6. Bank lending and capital By Gerbert Hebbink; Mark Kruidhof; Jan Willem Slingenberg
  7. A semi-APARCH approach for comparing long-term and short-term risk in Chinese financial market and in mature financial markets By Yuanhua Feng; Lixin Sun
  8. On Optimal Reinsurance Policy with Distortion Risk Measures and Premiums By Hirbod Assa
  9. Interpreting Financial Market Crashes as Earthquakes: A New early Warning System for Medium Term Crashes By Francine Gresnigt; Erik Kole; Philip Hans Franses
  10. Monetary policy effects on bank risk taking By Abbate, Angela; Thaler, Dominik
  11. Predicting the past: Understanding the causes of bank distress in the Netherlands in the 1920s By Colvin, Christopher L.; de Jong, Abe; Fliers, Philip T.

  1. By: Spiros Bougheas; Alan Kirman
    Abstract: In this paper we review recent advances in financial economics in relation to the measurement of systemic risk. We start by reviewing studies that apply traditional measures of risk to financial institutions. However, the main focus of the review is on studies that use network analysis paying special attention to those that apply complex analysis techniques. Applications of these techniques for the analysis and pricing of systemic risk has already provided significant benefits at least at the conceptual level but it also looks very promising from a practical point of view.
    Keywords: Comlex Financial Systems, Networks, Systemic Risk
    Date: 2014
  2. By: Bos J.W.B.; Lamers M.A.J.; Purice V. (GSBE)
    Abstract: We examine the relationship between bank size and financial stability by viewing the supervisor of a banking system as an investor holding a portfolio of banks. Based on this view, we investigate the role of large banks in determining the systemic risk in this portfolio. Our results, based on book data of U.S. banks and Bank Holding Companies, indicate that the largest banks are consistently overrepresented in the current portfolio compared with the minimum variance portfolio. Moreover, the risk level of the portfolio can be reduced by limiting concentration without sacrificing returns.
    Keywords: Optimization Techniques; Programming Models; Dynamic Analysis; Financial Markets and the Macroeconomy; Comparative or Joint Analysis of Fiscal and Monetary Policy; Stabilization; Treasury Policy; Banks; Depository Institutions; Micro Finance Institutions; Mortgages;
    JEL: C61 E44 E63 G21
    Date: 2014
  3. By: Miguel, Fusco; Dario, Bacchini; Esteban Otto, Thomasz
    Abstract: The aim of this paper is to summarise a variety of dimensions of agricultural risk in Argentina and to propose different lines of research related to an integrated risk management framework at the macro and micro levels. First, we analyse the incidence of the primary sector in the Argentinean economy, to have one first dimension of the exposure to external shocks. Then, we present some major risks that affect small agricultural producers at a micro level. Finally, we introduce some financial innovations that reduce climate and price risk exposure, such as weather derivatives and index-based insurances.
    Keywords: agricultural risk, macroeconomic vulnerability, financial innovations, index-based insurances
    JEL: E61 G22 Q12 Q14
    Date: 2014–06–03
  4. By: Alexis Derviz
    Abstract: We study the impact of collateral diversification by non-financial firms on systemic risk in a general equilibrium model with standard production functions and mixed debt-equity financing. Systemic risk comes about as soon as firms diversify their collateral by holding claims on a big wholesale bank (called merchant bank in the paper) whose asset side includes claims on the same producer set. The merchant bank sector proves to be fragile (has a short distance to default) regardless of competition. In this setting, the policy response, consisting in official guarantees for the merchant bank's liabilities, entails considerable government loss risk. An alternative without the need for public sector involvement is to encourage systemically important merchant banks to introduce a simple bail-in mechanism by restricting their liabilities to contingent convertible bonds. This line of regulatory policy is particularly relevant to the containment of systemic events in globally leveraged economies serviced by big international banks outside host country regulatory control.
    Keywords: CoCos, collateral, merchant bank, systemic risk
    JEL: C68 D21 F36 G24 G38
    Date: 2013–12
  5. By: Christoph Rheinberger (Economie des Ressources Naturelles, INRA); Hans E. Romang (Swiss Federal Office of Meteorology and Climatology); Michael Bründl (WSL Institute for Snow and Avalanche Research SLF)
    Abstract: Quantitative risk assessments of debris flows and other hydrogeological hazards require the analyst to predict damage potentials. A common way to do so is by use of proportional loss functions. In this paper, we analyze a uniquely rich dataset of 132 buildings that were damaged in one of five large debris flow events in Switzerland. Using the double generalized linear model, we estimate proportional loss functions thatmay be used for various prediction purposes including hazard mapping, landscape planning, and insurance pricing. Unlike earlier analyses, we control for confounding effects of building characteristics, site specifics, and process intensities as well as for overdispersion in the data. Our results suggest that process intensity parameters are the most meaningful predictors of proportional loss sizes. Cross-validation tests suggest that the mean absolute prediction errors of our models are in the range of 11 %, underpinning the accurateness of the approach.
    Keywords: risk-assessment, landslide risk, vulnerability, damage, management, regression, hazards
    Date: 2013
  6. By: Gerbert Hebbink; Mark Kruidhof; Jan Willem Slingenberg
    Abstract: The capital rules that banks have to comply with have become much more stringent since the financial crisis. The financial crisis brought home the fact that the capital buffers of banks were too small to absorb shocks. Financial aid from the state was required on a white scale to avoid more serious consequences for the financial system. In reaction to the crisis, the Basel Committee developed a new regulatory framework to make the banking system more resilient (Basel III). In Europa Basel III is being implemented through the CRD-IV/CRR legislative package. At the heart of the reforms, which should prevent new problems arising at banks, are the stricter rules governing bank capital.
    Date: 2014–04
  7. By: Yuanhua Feng (University of Paderborn); Lixin Sun (Shandong University)
    Abstract: The aim of this paper is to analyze the long-term and short-term risk components in Chinese financial market and to compare them with those in mature financial markets. For this purpose a most recently proposed Semi-APARCH is applied to the Shanghai Index and the Shenzhen Index, and four financial indexes in mature markets. A few important empirical findings are achieved. Firstly, the current long-term risk in Chinese financial market is stable and at a low level. Secondly, the dependence level between long-term risk in Chinese financial market and that in mature financial market is not high. Thirdly, the short-term risk in Chinese financial market differs to that in a mature financial market at least in two ways: 1) The leverage effect in Chinese financial market is much lower than that in a mature financial market. 2) The innovations in Chinese financial returns is nearly heavy-tailed distributed. This is however not the case in a mature market.
    Keywords: Chinese financial market, mature financial markets, long-term risk, short-term risk, semiparametric APARCH
    JEL: C14 G10
    Date: 2013–12
  8. By: Hirbod Assa
    Abstract: In this paper, we consider the problem of optimal reinsurance design, when the risk is measured by a distortion risk measure and the premium is given by a distortion risk premium. First, we show how the optimal reinsurance design for the ceding company, the reinsurance company and the social planner can be formulated in the same way. Second, by introducing the marginal indemnification functions, we characterize the optimal reinsurance contracts. We show that, for an optimal policy, the associated marginal indemnification function only takes the values zero and one. We will see how the roles of the market preferences and premiums and that of the total risk are separated.
    Date: 2014–06
  9. By: Francine Gresnigt (Erasmus University Rotterdam); Erik Kole (Erasmus University Rotterdam); Philip Hans Franses (Erasmus University Rotterdam)
    Abstract: We propose a modeling framework which allows for creating probability predictions on a future market crash in the medium term, like sometime in the next five days. Our framework draws upon noticeable similarities between stock returns around a financial market crash and seismic activity around earthquakes. Our model is incorporated in an Early Warning System for future crash days. Testing our EWS on S&P 500 data during the recent financial crisis, we find positive Hanssen-Kuiper Skill Scores. Furthermore our modeling framework is capable of exploiting information in the returns series not captured by well known and commonly used volatility models. EWS based on our models outperform EWS based on the volatility models forecasting extreme price movements, while forecasting is much less time-consuming.
    Keywords: Financial crashes; Hawkes process; self-exciting process; Early Warning System
    JEL: C13 C15 C53 G17
    Date: 2014–06–03
  10. By: Abbate, Angela; Thaler, Dominik
    Abstract: The contribution of this paper is twofold. First, we provide empirical evidence on the existence of a risk-taking channel in the US economy. By identifying a Bayesian VAR through sign restrictions, we find that an expansionary monetary policy shock causes a persistent increase in proxies for bank risk-taking behaviour. We then develop a New Keynesian model with a risk-taking channel, where low levels of the risk free rates induce banks to extend credit to riskier borrowers. Conditional on calibration values, the simulated responses of key banking sector variables is compatible with the transmission mechanism observed in the data.
    Keywords: Bank Risk; Monetary policy; DSGE Models; Bayesian Analysis
    JEL: E12 E44 E58 C11
    Date: 2014
  11. By: Colvin, Christopher L.; de Jong, Abe; Fliers, Philip T.
    Abstract: Why do some banks fail in financial crises while others survive? This article answers this question by analysing the effect of the Dutch financial crisis of the 1920s on 142 banks, of which 33 failed. We find that choices of balance sheet composition and product market strategy made in the lead-up to the crisis had a significant impact on banks' subsequent chances of experiencing distress. We document that high-risk banks - those operating highly-leveraged portfolios and attracting large quantities of deposits - were more likely to fail. Branching and international activities also increased banks´ default probabilities. We measure the effects of board interlocks, which have been characterized in the extant literature as contributing to the Dutch crisis. We find that boards mattered: failing banks had smaller boards, shared directors with smaller and very profitable banks and had a lower concentration of interlocking directorates in non-financial firms. --
    Keywords: financial crises,bank failures,bank business models,interlocking directorates,the Netherlands,the interwar period
    JEL: G01 G21 G33 G34 N24
    Date: 2014

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