New Economics Papers
on Risk Management
Issue of 2010‒07‒31
thirteen papers chosen by

  1. Local Housing Market Cycle and Loss Given Default: Evidence from Sub-Prime Residential Mortgages By Yanan Zhang; Lu Ji; Fei Liu
  3. Burying the Stability Pact: The Reanimation of Default Risk in the Euro Area By Christian Fahrholz; Roman Goldbach
  4. The Fundamental Determinants of Credit Default Risk for European Large Complex Financial Institutions By Inci Ötker; Jiri Podpiera
  5. Risk Assessment for a Structured Product Specific to the CO2 Emission Permits Market By Marius-Cristian Frunza; Dominique Guegan
  6. From deterministic to stochastic surrender risk models: impact of correlation crises on economic capital By Stéphane Loisel; Xavier Milhaud
  7. Currency Hedging for International Portfolios By Jochen M. Schmittmann
  8. Correlation crises in insurance and finance, and the need for dynamic risk maps in ORSA By Stéphane Loisel; Pierre Arnal; Romain Durand
  9. Of Runes and Sagas: Perspectives on Liquidity Stress Testing Using an Iceland Example By Li L. Ong; Martin Cihák
  10. Nonparametric Analysis of Hedge Funds Lifetimes By Darolles, Serge; Florens, Jean-Pierre; Simon, Guillaume
  11. Credit risk management in financing agriculture By Wenner, Mark D.
  12. Predicting bank loan recovery rates with neural networks By Joao A. Bastos
  13. The Effects of the Subprime Crisis on the Latin American Financial Markets: An Empirical Assessment By Gilles Dufrenot; Valerie Mignon; Anne Peguin-Feissolle

  1. By: Yanan Zhang; Lu Ji; Fei Liu
    Abstract: This paper studies the impact of housing market cycles on loss given default (LGD). Previous studies have shown that the current loan-to-value ratio (CLTV) is the most important determinant of LGD. This paper establishes another linkage which is between the house price cycles before the time of mortgage origination and LGD. The empirical analysis is based on a large loan-level sub-prime residential mortgage loss dataset from 1998 to 2009. Results show that house price history has a long memory in explaining LGD. Its explanatory power far exceeds the original LTV and other loan characteristics. This paper offers a countercyclical view of LGD risk. The model can be combined with a default probability model to serve as a regulatory prudential tool. Such a tool provides a solution to the inherent procyclical bias in BASEL II capital requirements, and can contribute to the safety and soundness of banking institutions.
    Date: 2010–07–16
  2. By: Mohamed Belhaj (GREQAM - Groupement de Recherche en Économie Quantitative d'Aix-Marseille - Université de la Méditerranée - Aix-Marseille II - Université Paul Cézanne - Aix-Marseille III - Ecole des Hautes Etudes en Sciences Sociales (EHESS) - CNRS : UMR6579)
    Abstract: This paper proposes a simple continuous time model to analyze capital charges for operational risk. We find that undercapitalized banks have less incentives to reduce their operational risk exposure. We view operational risk charge as a tool to reduce the moral hazard problem. Our results show, that only Advanced Measurement Approach may create appropriate incentives to reduce the frequency of operational losses, while Basic Indicator Approach appears counterproductive.
    Keywords: Operational Risk, Capital Requirements, Dividends, Basel Accords
    Date: 2010–07–20
  3. By: Christian Fahrholz (School of Economics and Business Administration, Friedrich-Schiller-University Jena); Roman Goldbach
    Abstract: -
    Keywords: -
    JEL: E62 G12 G14 H30 H61
    Date: 2010–06–14
  4. By: Inci Ötker; Jiri Podpiera
    Abstract: This paper attempts to identify the fundamental variables that drive the credit default swaps during the initial phase of distress in selected European Large Complex Financial Institutions (LCFIs). It uses yearly data over 2004 - 08 for 29 European LCFIs. The results from a dynamic panel data estimator show that LCFIs’ business models, earnings potential, and economic uncertainty (represented by market expectations about the future risks of a particular LCFI and market views on prospects for economic growth) are among the most significant determinants of credit risk. The findings of the paper are broadly consistent with those of the literature on bank failure, where the determinants of the latter include the entire CAMELS structure - that is, Capital Adequacy, Asset Quality, Management Quality, Earnings Potential, Liquidity, and Sensitivity to Market Risk. By establishing a link between the financial and market fundamentals of LCFIs and their CDS spreads, the paper offers a potential tool for fundamentals-based vulnerability and early warning system for LCFIs.
    Date: 2010–06–29
  5. By: Marius-Cristian Frunza (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Panthéon-Sorbonne - Paris I, Sagacarbon - Sagacarbon SA); Dominique Guegan (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Panthéon-Sorbonne - Paris I, EEP-PSE - Ecole d'Économie de Paris - Paris School of Economics - Ecole d'Économie de Paris)
    Abstract: The aim of this work is to use a new modelling technique for CO2 emission prices, in order to estimate the risk associated with a related, structured product. After a short discussion of the specificities of this market, we investigate several modelling methods for CO2 emission prices. We use these results for risk modeling of the swap between two CO2 related instruments : the European Union Allowances and the Certified Emission Reductions. We estimate the counterparty risk for this kind of transaction and evaluate the impact of different models on the risk measure and the allocated capital.
    Keywords: Carbon ; Generalized Hyperbolic Distribution ; CER ; EUA ; Swap ; Value at Risk
    Date: 2010–06
  6. By: Stéphane Loisel (SAF - Laboratoire de Sciences Actuarielle et Financière - Université Claude Bernard - Lyon I : EA2429); Xavier Milhaud (SAF - Laboratoire de Sciences Actuarielle et Financière - Université Claude Bernard - Lyon I : EA2429, Axa Global Life - AXA)
    Abstract: In this paper we raise the matter of considering a stochastic modeling of the surrender rate instead of the classical S-shaped deterministic curve (in function of the spread), still used in almost all insurance companies. A stochastic model in which surrenders are conditionally independent with respect to a S-curve disturbance would be tempting in some extreme scenarii, especially to address the question of the lack of data. However, we explain why this conditional independence between policyholders, which has the advantage to be the simplest assumption, looks particularly maladaptive when the spread increases. Indeed the correlation between policyholders' decisions is most likely to increase in this situation. We suggest and develop a simple model which integrates those phenomena. With stochastic orders it is possible to compare it to the conditional independence approach qualitatively. In an partially internal Solvency II model, we quantify the impact of the correlation phenomenon on a real life portfolio for a global risk management strategy.
    Date: 2010–07–08
  7. By: Jochen M. Schmittmann
    Abstract: This paper examines the benefits from hedging the currency exposure of international investments in single- and multi-country equity and bond portfolios from the perspectives of German, Japanese, British and American investors. Over the period 1975 to 2009, hedging of currency risk substantially reduced the volatility of foreign investments at a quarterly investment horizon. Contrary to previous studies, the paper finds that at longer investment horizons of up to five years the case for hedging for risk reduction purposes remained strong.In addition to its impact on risk, hedging affected returns in economically meaningful magnitudes in some cases.
    Keywords: Exchange risk , Foreign exchange transactions , Foreign investment , International capital markets , Risk management , Multiple currency practices ,
    Date: 2010–06–28
  8. By: Stéphane Loisel (SAF - Laboratoire de Sciences Actuarielle et Financière - Université Claude Bernard - Lyon I : EA2429); Pierre Arnal (Actuaris - Actuaris); Romain Durand (Actuaris - Actuaris)
    Abstract: We explain why correlation crises may occur in insurance and finance. These phenomena are not taken into account in Solvency II standard formula. We show the importance of taking them into account in internal models or partial internal models. Given the variety of scenarios that could lead to correlation crises and their different potential impacts, we support the idea that ORSA (Own Risk and Solvency Assessment) reports of insurance companies should include dynamic and causal correlation crises analyzes.
    Date: 2010–07–02
  9. By: Li L. Ong; Martin Cihák
    Abstract: The global financial crisis revealed weaknesses in the stress testing exercises performed on financial institutions and systems around the world. These failures were most evident in the area of liquidity risk, where now-obvious vulnerabilities were left largely undetected, with stress tests having largely focused on solvency risk. This paper uses publicly available data from a now-defunct bank in Iceland, where liquidity shocks were immense, to demonstrate how a combination of stress tests of the various risks would have provided a clearer picture of existing vulnerablities. We show that, ultimately, stress test models do not necessarily need to be complex or overly sophisticated. Basic stress tests, using appropriate assumptions and shocks, could reveal key areas of risk to inform contingency planning. The liquidity stress test templates used in this paper are included.
    Date: 2010–07–07
  10. By: Darolles, Serge; Florens, Jean-Pierre; Simon, Guillaume
    Abstract: Most of hedge funds databases are now keeping history of dead funds in order to control biases in empirical analysis. It is then possible to use these data for the analysis of hedge funds lifetimes and survivorship. This paper proposes two nonparametric specifications of duration models. First, the single risk model is an alternative to parametric duration models used in the literature. Second, the competing risks model consider the two reasons why hedge funds stop reporting. We apply the two models to hedge funds data and compare our results to the literature. In particular, we show that a cohort eect must be considered. Moreover, the reason of the exit is a crucial information for the analysis of funds' survival as for a large part of disappearing funds, exit cannot be explained by low performance or low level of assets.
    Date: 2010–03
  11. By: Wenner, Mark D.
    Abstract: A griculture is an inherently risky economic activity. A large array of uncontrollable elements can affect output production and prices, resulting in highly variable economic returns to farm households. In developing countries, farmers also lack access to both modern instruments of risk management—such as agricultural insurance, futures contracts, or guarantee funds—and ex post emergency government assistance. Such farmers rely on different “traditional” coping strategies and risk-mitigation techniques, but most of these are inefficient. Formal and semiformal arrangements—such as contract farming, joint-liability lending, and value-chain integration—have arisen in recent decades, but they too are limited and can be very context sensitive. One consequence of inadequate overall financial risk management is that farmers in general face constrained access to formal finance. The smaller the net worth of the farm household, the worse the degree of exclusion. Formal lenders avoid financing agriculture for a host of reasons: high cost of service delivery, information asymmetries, lack of branch networks, perceptions of low profitability in agriculture, lack of collateral, high levels of rural poverty, or low levels of farmer education and financial literacy. But, predominantly, bank managers around the world say they will not finance agriculture because of the high degree of uncontrolled production and price risk that confronts the sector. A farmer can be an able and diligent manager with an excellent reputation for repayment, guaranteed access to a market, and high-quality technical assistance, but an unexpected drought or flood can force him or her to involuntarily default. In emerging countries with fair to high levels of agricultural market and trade integration, large commercial farmers may escape this predicament because they have the ability to purchase insurance, engage in price hedging, obtain financing overseas, or liquidate assets quickly in the event of a default. Consequently, formal lenders tend to overemphasize the use of immoveable collateral as the primary buffer against default risk, which means they provide services to a limited segment of the farm population. Small- and medium-sized farmers, who constitute the vast majority of farm operators, often do not have secured-title land, which is the preferred type of collateral; if they do, its value may be insufficient to cover the loan in question. Even if farmers have sufficient titled land to collateralize loans, they may refuse low-interest formal loans and assume high-interest informal ones that have no collateral requirements instead. They may also use savings to finance agricultural production because they are averse to risking their most prized possession—land. The result is limited supply or access to formal agricultural financing, even though much of the population of Sub-Saharan Africa and South Asia is rural and depends on agriculture and livestock rearing for their main livelihood activities.
    Keywords: agricultural finance, agriculture finance, Risk management, Rural finance,
    Date: 2010
  12. By: Joao A. Bastos (CEMAPRE, School of Economics and Management (ISEG), Technical University of Lisbon)
    Abstract: This study evaluates the performance of feed-forward neural networks to model and forecast recovery rates of defaulted bank loans. In order to guarantee that the predictions are mapped into the unit interval, the neural networks are implemented with a logistic activation function in the output neuron. The statistical relevance of explanatory variables is assessed using the bootstrap technique. The results indicate that the variables which the neural network models use to derive their output coincide, to a great extent, with those that are significant in parametric fractional regression models. Out-of-sample estimates of prediction errors are evaluated. The results suggest that neural networks may have better predictive ability than fractional regression models, provided the number of observations is sufficiently large.
    Keywords: Loss given default, Recovery rate, Forecasting, Bank loan, Fractional regression, Neural network
    JEL: G21 G33
    Date: 2010–07
  13. By: Gilles Dufrenot; Valerie Mignon; Anne Peguin-Feissolle
    Abstract: The aim of this article is to answer the following question: can the considerable rise in the volatility of the LAC stock markets in the aftermath of the 2007/2008 crisis be explained by the worsening financial environment in the US markets? To this end, we rely on a timevarying transition probability Markov-switching model, in which “crisis” and “non-crisis” periods are identified endogenously. Using daily data from January 2004 to April 2009, our findings do not validate the “financial decoupling” hypothesis since we show that the financial stress in the US markets is transmitted to the LAC’s stock market volatility, especially in Mexico.
    Keywords: Stock markets; volatility; financial stress; regime-switching; Markovswitching model
    JEL: C13 C22 G15
    Date: 2010–07

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