recent developments in consumer credit risk assessment consumer credit risk assessment involves the use of risk assessment tools to manage a borrower s account from the time of pre screening a potential application through to the management of the account during its life and possible write off the riskiness of lending to a credit applicant is usually estimated using a logistic regression model though researchers have considered many other types of classifier and whilst preliminary evidence suggest support vector machines seem to be the most accurate data quality issues may prevent these laboratory based results from being achieved in practice the training of a classifier on a sample of accepted applicants rather than on a sample representative of the applicant population seems not to result in bias though it does result in difficulties in setting the cut off profit scoring is a promising line of research and the basel 2 accord has had profound implications for the way in which credit applicants are assessed and bank policies adopted

economic and regulatory capital allocation for revolving retail exposures abstract we present two internal capital allocation models and compare the capital ratios they generate with those prescribed by the latest revision of basel s new capital accord proposal for advanced retail portfolios which allows for explicit future margin income recognition given a test portfolio of credit card exposures that we assemble we find that basel s ratios are closer to those generated by our models for low credit risk segments we attribute the discrepancies to the different ways basel and our models account for future margin income to basel s assumptions about asset correlations and to one model taking macroeconomic conditions into account

the public s willingness to pay for securing a reliable natural gas supply in korea with the increasing importance of natural gas ng in the energy mix the search for a reliable liquefied ng lng supply has received great attention along with energy security in korea however the current level of lng supply reliability in korea is much lower than that in other industrialized countries in order to improve the reliability of the lng supply diverse policy measures are required which come at an additional cost paid by society this study aims to investigate the public s willingness to pay wtp for improving the reliability of the lng supply by increasing the lng storage rate from the current level 11 to 20 to this end the contingent valuation cv method is applied by using national survey data of 1000 households in particular this study employs a one and one half bound oohb dichotomous choice model combined with a spike model to address the responses from the cv survey with zero wtp the annual mean wtp is estimated to be krw 9641 usd 8 68 per household expanding the value to the national population provides a value of krw 169 43 billion usd 152 55 million the results indicate that people are willing to shoulder the burden of safeguarding a reliable supply of lng

distributed utility planning using probabilistic production costing and generalized benders decomposition summary form only given as follows regulatory changes and advances in distributed resources dr technology have lead utilities to consider drs as alternatives to central station generation and t d investments this paper presents a comprehensive planning and production simulation model that simultaneously evaluates central and local investments to determine the optimal mix for long term expansion the model can also be viewed as optimizing drs while simulating a perfectly competitive wholesale power market the model is a mixed integer linear stochastic program that enforces kirchhoff s current and voltage laws and is solved using generalized benders decomposition gbd the formulation includes multiarea probabilistic production costing as a subproblem drs and local distribution reinforcements are modeled as integer variables while transmission and central generation options are represented as continuous variables the model is applied to a ten year multi area example that suggests that drs are able to modify capacity additions and production costs by changing demand and power flows

credit scoring for profitability objectives in consumer credit markets lending decisions are usually represented as a set of classification problems the objective is to predict the likelihood of customers ending up in one of a finite number of states such as good bad payer responder non responder and transactor non transactor decision rules are then applied on the basis of the resulting model estimates however this represents a misspecification of the true objectives of commercial lenders which are better described in terms of continuous financial measures such as bad debt revenue and profit contribution in this paper an empirical study is undertaken to compare predictive models of continuous financial behaviour with binary models of customer default the results show models of continuous financial behaviour to outperform classification approaches they also demonstrate that scoring functions developed to specifically optimize profit contribution using genetic algorithms outperform scoring functions derived from optimizing more general functions such as sum of squared error

linear programming based analysis of marginal cost pricing in electric utility capacity expansion abstract this paper concerns methods for discretizing and approximating the annual load duration curve in the context of a linear programming model and its interpretation in electric utility expansion planning the emphasis is upon the interpretation of the linear programming dual variables and their relationship with classical results of peak load pricing in particular for capacity planning in which one can choose from a diverse number of technological alternatives we support the work of wenders by precisely characterizing how off peak periods bear partial responsibility of the capacity cost

structural models in consumer credit abstract we propose a structural credit risk model for consumer lending using option theory and the concept of the value of the consumer s reputation using brazilian empirical data and a credit bureau score as proxy for creditworthiness we compare a number of alternative models before suggesting one that leads to a simple analytical solution for the probability of default we apply the proposed model to portfolios of consumer loans introducing a factor to account for the mean influence of systemic economic factors on individuals this results in a hybrid structural reduced form model and comparisons are made with the basel ii approach our conclusions partially support that approach for modelling the credit risk of portfolios of retail credit

quantitative methods in credit management a survey many static and dynamic models have been used to assist decision making in the area of consumer and commercial credit the decisions of interest include whether to extend credit how much credit to extend when collections on delinquent accounts should be initiated and what action should be taken we survey the use of discriminant analysis decision trees and expert systems for static decisions and dynamic programming linear programming and markov chains for dynamic decision models since these models do not operate in a vacuum we discuss some important aspects of credit management in practice e g legal considerations sources of data and statistical validation of the methodology we provide our perspective on the state of the art in theory and in practice

asset portfolio securitizations and cyclicality of regulatory capital this paper analyzes the level and cyclicality of regulatory bank capital for asset portfolio securitizations in relation to the cyclicality of capital requirements for the underlying loan portfolio as under basel ii iii we find that the cyclicality of capital requirements is higher for i asset portfolio securitizations relative to primary loan portfolios ii ratings based approach rba relative to the supervisory formula approach iii given the rba for a point in time rating methodology relative to a rate and forget rating methodology and iv under the passive reinvestment rule relative to alternative rules capital requirements of the individual tranches reveal that the volatility of aggregated capital charges for the securitized portfolio is triggered by the most senior tranches this is due to the fact that senior tranches are more sensitive to the macroeconomy an empirical analysis provides evidence that current credit ratings are time constant and that economic losses for securitizations have exceeded the required capital in the recent financial crisis

a review of trade credit literature opportunities for research in operations abstract trade credit arises when a buyer delays payment for purchased goods or services its nature has predominantly been an area of inquiry for researchers from the disciplines of finance marketing and economics but it has received relatively little attention in other domains in our article we provide an integrative review of the existing literature and discuss conflicting study outcomes we organize the relevant literature into seven areas of inquiry and analyze four in detail trade credit motives order quantity decisions credit term decisions and settlement period decisions additionally we derive a detailed agenda for future research in these areas

electricity supply reliability estimating the value of lost load the office of electricity regulation offer reviews the performance of electricity distribution companies on reliability of supply while physical indicators of supply reliability such as number of outages and minutes of electricity lost per customer per year are readily available little is known about the monetary value placed on supply reliability by customers this paper briefly reviews different methods to derive monetary values of power interruptions avoided before arguing that a method which values the lost utility to consumers from outages is the most appropriate a contingent ranking method is used to derive such lost utility values from a survey of industrial firms the value customers place on outages avoided is higher than that currently used in appraisals of infrastructure investment and in the determination of electricity prices in the uk

public support for reducing us reliance on fossil fuels investigating household willingness to pay for energy research and development abstract in order to reduce future dependence on foreign oil and emissions of co2 how much would us households be willing to pay annually to support increased energy research and development r d activities designed to replace fossil fuels does it matter whether the r d includes nuclear energy options we explore these questions using data from a unique set of national telephone and internet surveys using a national advisory referendum format the contingent valuation method is applied to estimate annual household willingness to pay wtp for us household support of a national energy research and development fund erdf for investments in energy sources not reliant on fossil fuels while accounting for the level of un certainty in voting responses the wtp modeling includes a comparison of both classic maximum likelihood estimation mle and bayesian analysis evidence indicates that mle and bayesian analysis achieve similar statistical inference while the bayesian analysis provides a narrower confidence interval around estimated wtp

alternative bankruptcy prediction models using option pricing theory abstract we examine the empirical properties of the theoretical black scholes merton bsm bankruptcy model we evaluate the predictive ability of various existing modifications of the bsm model and extend prior studies by estimating volatility directly from market observable returns on firm value we show that parsimonious models using our direct market observable volatility estimate perform better than alternative more sophisticated models our findings suggest the adoption of simpler modelling approaches relying on market data when implementing the bsm model

identifying future defaulters a hierarchical bayesian method abstract traditional methods of applying classification models into the area of credit scoring may ignore the effect from censoring survival analysis has been introduced with its ability to deal with censored data the mixture cure model one important branch of survival models is also applied in the context of credit scoring assuming that the study population is a mixture of never default and will default customers we extend the standard mixture cure model through 1 relaxing the independence assumption of the probability and the time of default 2 treating the missing defaulting labels as latent variables and applying an augmentation technique and 3 introducing a discrete truncated exponential distribution to model the time of default our full model is written in a hierarchical form so that the markov chain monte carlo method is applied to estimate corresponding parameters through an empirical analysis we show that both mixture models the standard mixture cure model and the hierarchical mixture cure model hmcm are more advanced in identifying future defaulters while compared with logistic regression it is also concluded that our hierarchical bayesian extension increases the model s predictability and provides meaningful output for risk management

accuracy of mortgage portfolio risk forecasts during financial crises abstract this paper explores whether factor based credit portfolio risk models are able to predict losses in severe economic downturns such as the recent global financial crisis gfc within standard confidence levels the paper analyzes i the accuracy of default rate forecasts and ii whether forecast downturn percentiles value at risk var are sufficient to cover default rate outcomes over a quarterly and an annual forecast horizon uninformative maximum likelihood and informative bayesian techniques are compared as they imply different degrees of uncertainty we find that quarterly var estimates are generally sufficient but annual var estimates may be insufficient during economic downturns in addition the paper develops and analyzes models based on auto regressive adjustments of scores which provide a higher forecast accuracy the consideration of parameter uncertainty and auto regressive error terms mitigates the shortfall

multiple event incidence and duration analysis for credit data incorporating non stochastic loan maturity summary applications of duration analysis in economics and finance exclusively employ methods for events of stochastic duration in application to credit data previous research incorrectly treats the time to pre determined maturity events as censored stochastic event times the medical literature has binary parametric cure rate models that deal with populations that never experienced the modelled event we propose and develop a multinomial parametric incidence and duration model incorporating such populations in the class of cure rate models this is the first fully parametric multinomial model and is the first framework to accommodate an event with pre determined duration the methodology is applied to unsecured personal loan credit data provided by one of australia s largest financial services organizations this framework is shown to be more flexible and predictive through a simulation and empirical study that reveals simulation results of estimated parameters with a large reduction in bias superior forecasting of duration explanatory variables can act in different directions upon incidence and duration and variables exist that are statistically significant in explaining only incidence or duration

forecasting and decomposition of portfolio credit risk using macroeconomic and frailty factors this paper presents a dynamic portfolio credit model following the regulatory framework using macroeconomic and latent risk factors to predict the aggregate loan portfolio loss in a banking system the latent risk factors have three levels global across the entire banking system parent sectoral for the intermediate loan sectors and sector specific for the individual loan sectors the aggregate credit loss distribution of the banking system over a risk horizon is generated by monte carlo simulation and a quantile estimator is used to produce the aggregate risk measure and economic capital the risk contributions of the individual sectors and risk factors are measured by combining the hoeffding decomposition with the euler capital allocation rule for the u s banking system we find that the real gdp growth rate the global and sector wide frailty risk factors and their spillovers significantly affect loan defaults and the impacts of the frailty factors are not only economy wide but also sector specific we also find that the frailty risk factors make more significant risk contributions to the aggregate portfolio risk than the macroeconomic factors while the macroeconomic factors help to improve the accuracy and efficiency of the credit risk forecasts

market based coordination of transmission and generation capacity planning we propose an iso model for coordinating transmission expansion planning with competitive generation capacity planning in electricity markets the purpose of the model is a holistic simulation of generation and transmission capacity expansion in the market environment the solution represents an iterative process for simulating the interactions among gencos transcos and the iso which might be terminated by the iso based on a pre specified stopping criterion the proposed model adopts a joint energy and transmission auction market and a capacity mechanism the joint auction market enables competition to occur among generation and transmission resources the capacity mechanism offers incentives for market participant investments that reflect the locational values of additional capacity transmission capacity expansion decisions are made by merchant transmission lines that recover their capacity investments through transmission marginal pricing and capacity payments transmission network security is reflected in the proposed competitive resource planning model the examples illustrate a coordinated planning of generation and transmission in restructured power systems

korean public s preference for supply security of oil and gas and the impact of protest bidders abstract the korean governmental support for supply security of oil and gas via overseas exploration and production e p projects are publicly criticized because of some poor projects lacking of economic feasibility even though it should be expanded from a long term perspective applying the contingent valuation this study investigates the korean public s preferences for governmental support for overseas oil and gas e p projects the result shows that the governmental support for overseas e p projects rather decreases public utility the primary reason behind this utility decrease is that some respondents protested to bid because of their resistance toward tax increase without guaranteeing the efficient government support this result implies that simple tax increases for expansion of the governmental support may bring about public s strong opposition in order to overcome this public opposition this study suggests that it is necessary to arouse public understanding of the necessity of overseas oil and gas e p projects

spike models in contingent valuation spike models allow for a nonzero probability of zero willingness to pay in referendum style contingent valuation experiments they include many of the often used models as special cases and allow various analyses that are not possible in standard applications in this paper the economic rationale for the spike models and their estimation techniques are discussed and empirical illustrations are provided one study suggests that mean willingness to pay is zero and both studies strongly suggest that median wtp is zero these results have some bearing on the continuing debate of the incentive properties of hypothetical surveys and the construction of scenarios in contingent valuation experiments

protest beliefs in contingent valuation explaining their motivation abstract the definition and treatment of protest responses in contingent valuation cv can have a significant influence on the estimated values of the good in question if these responses are censored in order to understand how protest responses are motivated in a cv about forest biodiversity in germany we used an item battery to identify respondents protest beliefs the items were measured for all respondents irrespective of their willingness to pay wtp in principle then a scale based on these beliefs is taken as a dependent variable of regression analyses in addition to environmental concern we used norms the warm glow of giving and dilemma concern as further explanatory variables the latter focuses on cooperation problems in protecting the environment our results show that protest beliefs are significantly influenced by the explanatory factors furthermore the protest beliefs themselves have a significant effect on the decision to be wtp as well as on the amount of money stated by those who are wtp the censoring of protest responses may therefore be indefensible

predicting loss severities for residential mortgage loans a three step selection approach abstract this paper develops a novel framework to model the loss given default lgd of residential mortgage loans which is the dominant consumer loan category for many commercial banks lgds in mortgage lending are subject to two selection processes default and cure where the collateral value exceeds the outstanding loan amount we propose a three step selection approach with a joint probability framework for default cure i e zero lgd and non zero loss severity information the proposed methodology demonstrates improved performance in out of time predictions compared to widely used ols regressions

assessment of korean customers willingness to pay with rps abstract to increase the use of renewable energy the korean government will introduce the renewable portfolio standard rps in 2012 the rps places responsibility for extra renewable energy costs on the consumers and allows price competition among different renewable sources accordingly this study analyzes through the contingent valuation cv the willingness of korean households to pay more for electricity generated by wind photovoltaic pv and hydropower our empirical results show that although the willingness to pay or wtp was highest for wind power and lowest for hydropower the differences in wtp among the renewable sources were statistically insignificant this suggests that korean consumers prefer a renewable portfolio that minimizes power supply costs the average wtp for all three energy types was krw 1562 7 usd 1 350 per month per household which was approximately 3 7 of the average monthly electricity bill in 2010 this amount represents only 58 2 of what the korean government allocated in its budget to the new and renewable energy dissemination program in 2010 thus our results imply that the promotion of the new and renewable energy dissemination program may be difficult only with the wtp for electricity generated from renewable sources specifically the mean wtp will not support the set aside dissemination capacity for pv after 2014

credit granting a comparative analysis of classification procedures financial classification issues and particularly the financial distress problem continue to be subject to vigorous investigation the corporate credit granting process has not received as much attention in the literature this paper examines the relative effectiveness of parametric nonparametric and judgemental classification procedures on a sample of corporate credit data the judgemental model is based on the analytic hierarchy process evidence indicates that nonparametric recursive partitioning methods provide greater information than simultaneous partitioning procedures the judgemental model is found to perform as well as statistical models a complementary relationship is proposed between the statistical and the judgemental models as an effective paradigm for granting credit the credit granting process involves a tradeoff between the perceived default risk of the credit applicant and potential returns from granting requested credit the main objective in credit granting is to determine the optimal amount of credit to grant the amount of credit requested along with other financial and nonfinancial factors influences the assessment of default risk while default risk assessment can be appropriately modeled using classificatory models integration of such risk assessment with potential returns can be accomplished using a dynamic expected value framework academic research on credit granting can be grouped into two basic categories 2 i attempts to apply classification procedures to customer attribute data and develop classification models to assign group membership in the future and ii attempts to explicitly recognize the need to integrate such risk assessment with potential return as well as allow for differing degrees of credit investigation depending on the costs of such investigation to our knowledge this study represents the first attempt at examining the relative performance of classification procedures for corporate credit granting relative performance is measured in terms of how well the models replicate expert judgement we examine four statistical models multiple discriminant analysis mda logistic regression northeastern university and university of cincinnati respectively we are grateful to robert eisenbeis and sangit chatterjee for their insightful comments on an earlier draft we also thank an anonymous fortune 500 corporation as well as the credit research foundation for their support the usual disclaimer applies 1 this paper is primarily concerned with the credit granting decision in an industrial nonfinancial setting a more detailed version of this paper is available from the authors further for a review of the various motives for corporations to extend credit refer emery 10 2 we do not make any attempts to present a comprehensive review of the literature interested readers are referred to an excellent review by altman et al 1

linear complementarity models of nash cournot competition in bilateral and poolco power markets two cournot models of imperfect competition among electricity producers are formulated as mixed linear complementarity problems lcps and a simple example is presented to illustrate their application the two models simulate bilateral markets the models include a congestion pricing scheme for transmission but other transmission pricing approaches can also be represented in this framework the two models differ from each other in that one has no arbitrage between nodes of the network while in the other model arbitragers erase any noncost based differences in price the latter bilateral model turns out to be equivalent to a cournot model of a poolco the models differ from other cournot market models in that they include both of kirchhoff s laws via a dc approximation can include arbitragers possess unique solutions and are readily solved by efficient lcp algorithms the key assumption that permits their formulation as lcps is that each producer naively assumes that its output will not affect transmission prices

dynamic valuation of delinquent credit card accounts this paper introduces a dynamic model of the stochastic repayment behavior exhibited by delinquent credit card accounts based on this model we construct a dynamic collectability score dcs that estimates the account specific probability of collecting a given portion of the outstanding debt over any given time horizon the model integrates a variety of information sources including historical repayment data account specific and time varying macroeconomic covariates as well as scheduled account treatment actions two model identification methods are examined based on maximum likelihood estimation and the generalized method of moments the latter allows for an operational statistics approach combining model estimation and performance optimization by tailoring the estimation error to business relevant loss functions the dcs framework is applied to a large set of account level repayment data the improvements in classification and prediction performance compared to standard bank internal scoring meth

modeling long term electricity forward prices in contrast to forwards and futures on storable commodities prices of long term electricity forwards exhibit a dynamics different to that of short term and midterm prices we model long term electricity forward prices through demand and supply of electricity adjusted with a risk premium long term prices of electricity oil coal natural gas emission allowance imported electricity and aluminum are modeled with a vector autoregressive model var for estimation we use weekly prices of far maturity forwards relevant for the nordic electricity market although electricity prices experienced a few substantial shocks during the period we analyzed there is no evidence of a structural break cointegration analysis reveals two stationary long run relationships between all variables except the gas price indicating that these variables move together over time we find some influence of the risk premium however not on the long term electricity forwards at nord pool