New Economics Papers
on Risk Management
Issue of 2009‒05‒16
twelve papers chosen by

  1. Forecasting bank loans loss-given-default By Joao A. Bastos
  2. Measurement of Farm Credit Risk: SUR Model and Simulation Approach By Yan, Yan; Barry, Peter; Paulson, Nicholas; Schnitkey, Gary
  3. Merits and drawbacks of variance targeting in GARCH models By Francq, Christian; Horvath, Lajos; Zakoian, Jean-Michel
  5. Can Crop Insurance Premiums be Reliably Estimated? By Ramirez, Octavio A.; Carpio, Carlos E.; Rejesus, Rod
  6. Spatial and Temporal On-Farm Risk Management - Crop Production Scheduling and Index Insurance Strategies By Lin, Shanshan; Mullen, Jeffrey D.; Hoogenboom, Gerrit
  7. Directional Spatial Dependence and Its Implications for Modeling Systemic Yield Risk By Zhu, Ying; Ghosh, Sujit K.; Goodwin, Barry K.
  8. Economic Loan Loss Provision and Expected Loss By Stefan Hlawatsch; Sebastian Ostrowski
  9. Channels of risk-sharing among Canadian provinces: 1961–2006 By Balli, Faruk; Basher, Syed; Louis, Rosmy
  10. The Volatility Spillover Effects and Optimal Hedging Strategy in the Corn Market By Wu, Feng; Guan, Zhengfei
  11. Risk-Neutral Monopolists are Variance-Averse By Roland Kirstein
  12. Risk Classification in Animal Disease Prevention: Who Benefits from Differentiated Policy? By Niemi, Jarkko K; Lyytikainen, Tapani; Sahlstrom, Leena; Virtanen, Terhi; Lehtonen, Heikki

  1. By: Joao A. Bastos (CEMAPRE, School of Economics and Management (ISEG), Technical University of Lisbon)
    Abstract: With the advent of the new Basel Capital Accord, banking organizations are invited to estimate credit risk capital requirements using an internal ratings based approach. In order to be compliant with this approach, institutions must estimate the expected loss-given-default, the fraction of the credit exposure that is lost if the borrower defaults. This study evaluates the ability of a parametric fractional response regression and a nonparametric regression tree model to forecast bank loan credit losses. The out-of-sample predictive ability of these models is evaluated at several recovery horizons after the default event. The out-of-time predictive ability is also measured for a recovery horizon of one year. The performance of the models is benchmarked against recovery estimates given by a naive model in which predicted recoveries are given by historical averages.
    Keywords: Forecasting, bank loans, loss-given-default, fractional response regression, regression trees
    JEL: G21
    Date: 2009–05
  2. By: Yan, Yan; Barry, Peter; Paulson, Nicholas; Schnitkey, Gary
    Abstract: The study addresses problems in measuring credit risk under the structure model, and then proposes a seemingly unrelated regression model (SUR) to predict farmsâ ability in meeting their current and anticipated obligations in the next 12 months. The empirical model accounts for both the dependence structure and the dynamic feature of the structure model, and is used for estimating asset correlation using FBFM data for 1995-2004. Farm credit risk is then predicted by copula based simulation process with historical default rates as benchmark. Results are reported and compared to previous studies on farm default.
    Keywords: Credit Risk Measurement, Seemingly Unrelated Regression Model, Simulation, Agribusiness, Agricultural Finance, Farm Management, Research Methods/ Statistical Methods, Risk and Uncertainty,
    Date: 2009
  3. By: Francq, Christian; Horvath, Lajos; Zakoian, Jean-Michel
    Abstract: Variance targeting estimation is a technique used to alleviate the numerical difficulties encountered in the quasi-maximum likelihood (QML) estimation of GARCH models. It relies on a reparameterization of the model and a first-step estimation of the unconditional variance. The remaining parameters are estimated by QML in a second step. This paper establishes the asymptotic distribution of the estimators obtained by this method in univariate GARCH models. Comparisons with the standard QML are provided and the merits of the variance targeting method are discussed. In particular, it is shown that when the model is misspecified, the VTE can be superior to the QMLE for long-term prediction or Value-at-Risk calculation. An empirical application based on stock market indices is proposed.
    Keywords: Consistency and Asymptotic Normality; GARCH; Heteroskedastic Time Series; Quasi Maximum Likelihood Estimation; Value-at-Risk; Variance Targeting Estimator.
    JEL: C13 C22
    Date: 2009
  4. By: John Galbraith; Dongming Zhu
    Abstract: Financial returns typically display heavy tails and some skewness, and cinditional vairance models with these features often outperform more limited models. The difference in performance may be especially important in estimating quantities that depend on tail features, including risk measures such as the expected shortfall. Here, using a recent generalization of the asymmetric Student-t distribution to allow separate parameters to control skewness and the thickness of each tail, we fit daily financial returns and forecast expected shortfall for the S&P 500 composite index; the generalized distribution is used for the standardized innovations in a nonlinear, asymmetric GARCH-type model. The results provide empirical evidence for the usefulness of the generalized distribution in improving prediction of downside market risk of financial assets.
    JEL: C16 G10
    Date: 2009–01
  5. By: Ramirez, Octavio A.; Carpio, Carlos E.; Rejesus, Rod
    Abstract: The objective of this paper is to compare the accuracy of crop insurance rating methods based on historical liability and indemnity data (similar to the procedure currently used by the Risk Management Agency) and âyield distributionâ approaches. Estimated rates are compared to âtrueâ rates using empirically-grounded simulation procedures that take into account common data availability constraints. Simulation results suggest that farm and county level rate estimates using the âyield distributionâ approach are significantly more accurate than those based on historical indemnity and liability records.
    Keywords: crop insurance premiums, non-normal distributions, simulation methods, Agribusiness, Agricultural Finance, Risk and Uncertainty,
    Date: 2009–04–30
  6. By: Lin, Shanshan; Mullen, Jeffrey D.; Hoogenboom, Gerrit
    Abstract: An agronomic crop growth model, Decision Support System for Agro-Technology Transfer (DSSAT), is used to find optimal crop management strategies for cotton production in Mitchell, Miller, and Lee Counties in Georgia during the past 10 years. Planting date and irrigation threshold are the two variables optimized to maximize farmer's expected utility. A decreasing absolute risk aversion - constant relative risk aversion (DARA-CRRA) utility function is used to examine crop management decision that can be influenced by changes in inter-temporal risk behavior. Comparison is made from management perspective - one is dynamic crop management strategy that varies each year; one is static (constant) strategy over 10 years. Based on the best crop management strategies, index insurance products are designed to help farmers further reduce production risk. The impact of geographical basis risk was assessed by comparing the risk reduction generated from index insurance contracts based on different weather stations; the impact of temporal basis risk is assessed by allowing separate contracts to be purchased for different sub-periods during the entire period.
    Keywords: Irrigation, Planting Date, Risk Management, Weather Derivative Contract, Basis Risk, Agribusiness, Agricultural Finance, Crop Production/Industries, Farm Management, Financial Economics, Risk and Uncertainty,
    Date: 2009
  7. By: Zhu, Ying; Ghosh, Sujit K.; Goodwin, Barry K.
    Abstract: The objective of this study is to evaluate and model the spatial dependence of systemic yield risk. Various spatial autoregressive models are explored to account for county level dependence of crop yields. The results show that the time trend parameters of yields are correlated across spaces and the spatial correlations are changing with time. In addition, the spatial correlation of neighborhood in west/east direction is stronger than that of north/south direction. The information of the spatial dependence of yield risk will help the construction of better risk management programs for protecting producers from systemic yield risks.
    Keywords: Spatial Autoregressive Model, Spatial Dependence, Risk and Uncertainty,
    Date: 2009
  8. By: Stefan Hlawatsch (Faculty of Economics and Management, Otto-von-Guericke University Magdeburg); Sebastian Ostrowski (Faculty of Economics and Management, Otto-von-Guericke University Magdeburg)
    Abstract: The intention of a loss provision is the anticipation of credit's expected losses by adjusting the book values of the credits. Furthermore, this loan loss provision has to be compared to the expected loss according to Basel II and if necessary, equity has to be adjusted. This however assumes that the loan loss provision and the expected loss are comparable, which is only valid conditionally in current loan loss provisioning methods according to IAS. The provisioning and accounting model developed in this paper overcomes the before mentioned shortcomings and is consistent with an economic rationale of expected losses. We introduce a de¯nition of expected loss referring to the whole maturity of the loan and show that this measure can be reasonably compared with loan loss provisions. Additionally, this model is based on a close-to-market valuation of the loan. Suggestions for changes in current accounting and capital requirement rules are provided.
    Keywords: loan loss provision, expected loss, IAS, Basel II
    JEL: G18 G21 M41
    Date: 2009–04
  9. By: Balli, Faruk; Basher, Syed; Louis, Rosmy
    Abstract: This paper incorporates recent developments in the literature to quantify the channels and the associated determinants of risk-sharing among Canadian provinces. We find that 40 percent of shocks to gross provincial product are smoothed by capital markets, 25 percent are smoothed by the federal government, and 16 percent are smoothed by credit markets. The remaining 19 percent are not smoothed. Our decomposition of federal government smoothing shows that transfers to provincial and local governments constitute a major part of smoothing. Our estimates reveal that the series of postwar Bank Act revisions facilitated the working of capital market smoothing over time. We also conduct an investigation understanding why the credit market smoothing has declined over time. Finally, we introduce a new dimension in the analysis of risk-sharing by conducting a pairwise risk-sharing approach. The pairwise results present numerous micro findings that can help decision makers in formulating policies to remedy the weak links of incomplete risk-sharing.
    Keywords: Risk-sharing; consumption smoothing; federal taxes and transfer; pairwise approach.
    JEL: H77 F36 E20
    Date: 2009
  10. By: Wu, Feng; Guan, Zhengfei
    Abstract: This article examines the volatility spillovers from energy market to corn market. Using a volatility spillover model from the finance literature, we found significant spillovers from energy market to corn cash and futures markets, and the spillover effects are time-varying. The business cycle proxied by crude oil prices is shown to affect the magnitude of spillover effects over time. Based on the strong informational linkage between energy market and corn market, a cross hedge strategy is proposed and its performance studied. The simulation outcomes show that compared to alternative strategies of no hedge, constant hedge, and GARCH hedge, the cross hedge does not yield superior risk-reduction performance.
    Keywords: Volatility Spillover, GARCH, Optimal Hedge Ratio, Energy Price, Corn Price, Risk and Uncertainty,
    Date: 2009–04
  11. By: Roland Kirstein (Faculty of Economics and Management, Otto-von-Guericke University Magdeburg)
    Abstract: If the production of a risk-neutral monopolist is in uenced by a random variable, then the expected prot is decreasing in the variance of the production process.
    Keywords: Risk-aversion, correlated random variables, market power
    JEL: D81 L12
    Date: 2009–04
  12. By: Niemi, Jarkko K; Lyytikainen, Tapani; Sahlstrom, Leena; Virtanen, Terhi; Lehtonen, Heikki
    Abstract: Risk classification of livestock farms can help stakeholders design and implement risk management measures according to the possessed risk. Our goal is to examine how differently pig farms may contribute to the societal costs of an animal disease outbreak, how valuable this information is to different stakeholders, and how it can be used to target risk management measures. We show that the costs of an outbreak starting from a certain farm can be quantified for the entire sector using bio-economic models. In further studies, this quantified risk can be differentiated so that farms and slaughterhouses internalise the full cost of risk in production decisions and inhibit animal densities, animal contact structures or other characteristics which pose a threat to the sector. Potential benefits due to risk classification could be received by society and producers, and in the long run also by consumers.
    Keywords: Risk classification, animal disease, simulation, dynamic programming, partial-equilibrium, losses, Agricultural and Food Policy, Agricultural Finance, Livestock Production/Industries, Risk and Uncertainty,
    Date: 2009–04–30

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