Non-normal real estate return distributions by property type in the U.K.

Investment risk models with infinite variance provide a better description of distributions of individual property returns in the IPD database over the period 1981 to 2003 than Normally distributed risk models, which mirrors results in the U.S. and Australia using identical methodology. Real estate investment risk is heteroscedastic, but the Characteristic Exponent of the investment risk function is constant across time yet may vary by property type. Asset diversification is far less effective at reducing the impact of non-systematic investment risk on real estate portfolios than in the case of assets with Normally distributed investment risk. Multi-risk factor portfolio allocation models based on measures of investment codependence from finite-variance statistics are ineffectual in the real estate context.

The impact of uncertain precipitation data on insurance loss estimates using a flood catastrophe model

Catastrophe risk models used by the insurance industry are likely subject to significant uncertainty, but due to their proprietary nature and strict licensing conditions they are not available for experimentation. In addition, even if such experiments were conducted, these would not be repeatable by other researchers because commercial confidentiality issues prevent the details of proprietary catastrophe model structures from being described in public domain documents. However, such experimentation is urgently required to improve decision making in both insurance and reinsurance markets. In this paper we therefore construct our own catastrophe risk model for flooding in Dublin, Ireland, in order to assess the impact of typical precipitation data uncertainty on loss predictions. As we consider only a city region rather than a whole territory and have access to detailed data and computing resources typically unavailable to industry modellers, our model is significantly more detailed than most commercial products. The model consists of four components, a stochastic rainfall module, a hydrological and hydraulic flood hazard module, a vulnerability module, and a financial loss module. Using these we undertake a series of simulations to test the impact of driving the stochastic event generator with four different rainfall data sets: ground gauge data, gauge-corrected rainfall radar, meteorological reanalysis data (European Centre for Medium-Range Weather Forecasts Reanalysis-Interim; ERA-Interim) and a satellite rainfall product (The Climate Prediction Center morphing method; CMORPH). Catastrophe models are unusual because they use the upper three components of the modelling chain to generate a large synthetic database of unobserved and severe loss-driving events for which estimated losses are calculated. We find the loss estimates to be more sensitive to uncertainties propagated from the driving precipitation data sets than to other uncertainties in the hazard and vulnerability modules, suggesting that the range of uncertainty within catastrophe model structures may be greater than commonly believed.

Wastewater irrigation: the state of play

As demand for fresh water intensifies, wastewater is frequently being seen as a valuable resource. Furthermore, wise reuse of wastewater alleviates concerns attendant with its discharge to the environment. Globally, around 20 million ha of land are irrigated with wastewater, and this is likely to increase markedly during the next few decades as water stress intensifies. In 1995, around 2.3 billion people lived in water-stressed river basins and this could increase to 3.5 billion by 2025. We review the current status of wastewater irrigation by providing an overview of the extent of the practice throughout the world and through synthesizing the current understanding of factors influencing sustainable wastewater irrigation. A theme that emerges is that wastewater irrigation is not only more common in water-stressed regions such as the Near East, but the rationale for the practice also tends to differ between the developing and developed worlds. In developing nations, the prime drivers are livelihood dependence and food security, whereas environmental agendas appear to hold greater sway in the developed world. The following were identified as areas requiring greater understanding for the long-term sustainability of wastewater irrigation: (i) accumulation of bioavailable forms of heavy metals in soils, (ii) environmental fate of organics in wastewater-irrigated soils, (iii) influence of reuse schemes on catchment hydrology, including transport of salt loads, (iv) risk models for helminth infections (pertinent to developing nations), (v) microbiological contamination risks for aquifers and surface waters, (vi) transfer efficiencies of chemical contaminants from soil to plants, (vii) health effects of chronic exposure to chemical contaminants, and (viii) strategies for engaging the public.

Back to basics : empirical support for the importance of release planning in reducing sex offender recidivism

This article reports findings from a series of empirical studies investigating whether poor release planning might contribute to sex offender recidivism. A coding protocol was developed to measure the comprehensiveness of release planning which included items relating to accommodation, employment, pro-social support, community based treatment, and the Good Lives Model (T. Ward & C.A. Stewart, 2003) secondary goods. The protocol was retrospectively applied to groups of recidivist and non recidivist child molesters, matched on static risk level and time since release. As predicted, overall release planning was significantly poorer for recidivists compared to non recidivists. The accommodation, employment, and social support items combined to best predict recidivism, with predictive accuracy comparable to that obtained using static risk models. Results highlighted the importance of release planning in efforts to reduce sex offender recidivism. Implications for policy makers and community members are briefly discussed.

Assessment of community reintegration planning for sex offenders

Poor planning for reintegrating child molesters from prison to the community is a likely risk factor for sexual recidivism. The quality of reintegration planning was retrospectively measured for groups of recidivist (n = 30) and nonrecidivist (n = 30) child molesters who were individually matched on static risk level and time since release. Recidivists had significantly poorer reintegration planning scores than nonrecidivists, consistent with a previous study by the authors. Data from both studies were combined (total N = 141), and survival analyses showed that poor reintegration planning predicted an increased rate of recidivism. Accommodation, employment, and social support planning combined to predict recidivism, with predictive validity comparable to static risk models (area under the curve = .71). Summing these items yielded a scale of reintegration planning quality that differentiated well between recidivists and nonrecidivists and may have practical utility for risk assessment as an adjunct to static models.

Effects of infection-induced migration delays on the epidemiology of avian influenza in wild mallard populations

Wild waterfowl populations form a natural reservoir of Avian Influenza (AI) virus, and fears exist that these birds may contribute to an AI pandemic by spreading the virus along their migratory flyways. Observational studies suggest that individuals infected with AI virus may delay departure from migratory staging sites. Here, we explore the epidemiological dynamics of avian influenza virus in a migrating mallard (Anas platyrhynchos) population with a specific view to understanding the role of infection-induced migration delays on the spread of virus strains of differing transmissibility. We develop a host-pathogen model that combines the transmission dynamics of influenza with the migration, reproduction and mortality of the host bird species. Our modeling predicts that delayed migration of individuals influences both the timing and size of outbreaks of AI virus. We find that (1) delayed migration leads to a lower total number of cases of infection each year than in the absence of migration delay, (2) when the transmission rate of a strain is high, the outbreak starts at the staging sites at which birds arrive in the early part of the fall migration, (3) when the transmission rate is low, infection predominantly occurs later in the season, which is further delayed when there is a migration delay. As such, the rise of more virulent AI strains in waterfowl could lead to a higher prevalence of infection later in the year, which could change the exposure risk for farmed poultry. A sensitivity analysis shows the importance of generation time and loss of immunity for the effect of migration delays. Thus, we demonstrate, in contrast to many current transmission risk models solely using empirical information on bird movements to assess the potential for transmission, that a consideration of infection-induced delays is critical to understanding the dynamics of AI infection along the entire flyway.

Credit cycle dependent spread determinants in emerging sovereign debt markets

We address credit cycle dependent sovereign credit risk determinants. In our model, the spread determinants' magnitude is conditional on an unobservable endogenous sovereign credit cycle as represented by the underlying state of a Markov regime switching process. Our explanatory variables are motivated in the tradition of structural credit risk models and include changes in asset prices, interest rates, implied market volatility, gold price changes and foreign exchange rates. We examine daily frequency variations of U.S. dollar denominated Eurobond credit spreads of four major Latin American sovereign bond issuers (Brazil, Colombia, Mexico and Venezuela) with liquid bond markets during March 2000 to June 2011. We find that spread determinants are statistically significant and consistent with theory, while their magnitude remarkably varies with the state of the credit cycle. Crisis states are characterized by high spread change uncertainty and high sensitivities with respect to the spread change determinants. We further document that not only changes of local currencies, but also changes of the Euro with respect to the U.S. dollar are significant spread drivers and argue that this is consistent with the sovereigns' ability to pay.

Ensaios em macroeconometria e finanças

This thesis is composed of three essays referent to the subjects of macroeconometrics and Önance. In each essay, which corresponds to one chapter, the objective is to investigate and analyze advanced econometric techniques, applied to relevant macroeconomic questions, such as the capital mobility hypothesis and the sustainability of public debt. A Önance topic regarding portfolio risk management is also investigated, through an econometric technique used to evaluate Value-at-Risk models. The Örst chapter investigates an intertemporal optimization model to analyze the current account. Based on Campbell & Shillerís (1987) approach, a Wald test is conducted to analyze a set of restrictions imposed to a VAR used to forecast the current account. The estimation is based on three di§erent procedures: OLS, SUR and the two-way error decomposition of Fuller & Battese (1974), due to the presence of global shocks. A note on Granger causality is also provided, which is shown to be a necessary condition to perform the Wald test with serious implications to the validation of the model. An empirical exercise for the G-7 countries is presented, and the results substantially change with the di§erent estimation techniques. A small Monte Carlo simulation is also presented to investigate the size and power of the Wald test based on the considered estimators. The second chapter presents a study about Öscal sustainability based on a quantile autoregression (QAR) model. A novel methodology to separate periods of nonstationarity from stationary ones is proposed, which allows one to identify trajectories of public debt that are not compatible with Öscal sustainability. Moreover, such trajectories are used to construct a debt ceiling, that is, the largest value of public debt that does not jeopardize long-run Öscal sustainability. An out-of-sample forecast of such a ceiling is also constructed, and can be used by policy makers interested in keeping the public debt on a sustainable path. An empirical exercise by using Brazilian data is conducted to show the applicability of the methodology. In the third chapter, an alternative backtest to evaluate the performance of Value-at-Risk (VaR) models is proposed. The econometric methodology allows one to directly test the overall performance of a VaR model, as well as identify periods of an increased risk exposure, which seems to be a novelty in the literature. Quantile regressions provide an appropriate environment to investigate VaR models, since they can naturally be viewed as a conditional quantile function of a given return series. An empirical exercise is conducted for daily S&P500 series, and a Monte Carlo simulation is also presented, revealing that the proposed test might exhibit more power in comparison to other backtests.

A utilização de modelos de duração para gerenciar risco de crédito

Os modelos hazard, também conhecidos por modelos de tempo até a falência ou duração, são empregados para determinar quais variáveis independentes têm maior poder explicativo na previsão de falência de empresas. Consistem em uma abordagem alternativa aos modelos binários logit e probit, e à análise discriminante. Os modelos de duração deveriam ser mais eficientes que modelos de alternativas discretas, pois levam em consideração o tempo de sobrevivência para estimar a probabilidade instantânea de falência de um conjunto de observações sobre uma variável independente. Os modelos de alternativa discreta tipicamente ignoram a informação de tempo até a falência, e fornecem apenas a estimativa de falhar em um dado intervalo de tempo. A questão discutida neste trabalho é como utilizar modelos hazard para projetar taxas de inadimplência e construir matrizes de migração condicionadas ao estado da economia. Conceitualmente, o modelo é bastante análogo às taxas históricas de inadimplência e mortalidade utilizadas na literatura de crédito. O Modelo Semiparamétrico Proporcional de Cox é testado em empresas brasileiras não pertencentes ao setor financeiro, e observa-se que a probabilidade de inadimplência diminui sensivelmente após o terceiro ano da emissão do empréstimo. Observa-se também que a média e o desvio-padrão das probabilidades de inadimplência são afetados pelos ciclos econômicos. É discutido como o Modelo Proporcional de Cox pode ser incorporado aos quatro modelos mais famosos de gestão de risco .de crédito da atualidade: CreditRisk +, KMV, CreditPortfolio View e CreditMetrics, e as melhorias resultantes dessa incorporação

Tomada de decisão em relação ao crédito em uma instituição financeira : um estudo de caso do Banco do Brasil

Há uma intensa transformação nas empresas, exigindo uma efetividade maior em seus processos. Neste contexto repleto de incertezas, tem grande importância a tomada de decisão. O processo decisório de uma organização é o reflexo de como ela interage com seu ambiente (Simon,1965). A Tomada de Decisão se toma muito importante para a organização, passando por diversas variáveis na constituição de um modelo decisório. Esta pesquisa tem como objetivo o estudo dos modelos adotados por uma instituição financeira, que refletem sua fonna de decidir. A escolha deste tema justifica-se pela importância que o mesmo representa para as organizações financeiras e pela necessidade de melhorar a efetividade decisória. A empresa estudada é o Banco do Brasil, através de uma análise do processo de crédito dos clientes "pessoas jurídicas", onde se procura descrever a fonna como as decisões são tomadas. Há uma descrição da hierarquia do processo decisório, juntamente com os modelos de análise do risco de crédito como fatores preponderantes no sucesso do negócio crédito. No capítulo Metodologia, é caracterizada a empresa, a situação problema e o tema de estudo. No referencial teórico, foi feita uma análise do processo decisório, onde são analisados os modelos de análise do risco de crédito e a formação de sistemas de apoio à decisão nas instituições financeiras. Os resultados do estudo proposto, respondem o problema da pesqUIsa, onde é analisada, com aplicação de pesquisa documental e observação empírica, a empresa pesquisada. Através desta pesquisa, observou-se uma organização com modelo decisório extremamente planejado, porém não utilizando ainda as práticas modernas de tomada de decisão com relação ao crédito. A conclusão deste trabalho, além de trazer várias observações em tomo do tema analisado, também faz algumas sugestões à empresa pesquisada.

Modelo de risco controlado por resseguro e desigualdades para a probabilidade de ruína

In the work reported here we present theoretical and numerical results about a Risk Model with Interest Rate and Proportional Reinsurance based on the article Inequalities for the ruin probability in a controlled discrete-time risk process by Ros ario Romera and Maikol Diasparra (see [5]). Recursive and integral equations as well as upper bounds for the Ruin Probability are given considering three di erent approaches, namely, classical Lundberg inequality, Inductive approach and Martingale approach. Density estimation techniques (non-parametrics) are used to derive upper bounds for the Ruin Probability and the algorithms used in the simulation are presented

Uso de modelos estatísticos para dados de escore de crédito de uma instituição financeira

Pós-graduação em Engenharia de Produção - FEB

Risco de crédito: uma abordagem utilizando análise discriminante, regressão logística e redes neurais artificiais

Considering the relevance of researches concerning credit risk, model diversity and the existent indicators, this thesis aimed at verifying if the Fleuriet Model contributes in discriminating Brazilian open capital companies in the analysis of credit concession. We specifically intended to i) identify the economic-financial indicators used in credit risk models; ii) identify which economic-financial indicators best discriminate companies in the analysis of credit concession; iii) assess which techniques used (discriminant analysis, logistic regression and neural networks) present the best accuracy to predict company bankruptcy. To do this, the theoretical background approached the concepts of financial analysis, which introduced themes relative to the company evaluation process; considerations on credit, risk and analysis; Fleuriet Model and its indicators, and, finally, presented the techniques for credit analysis based on discriminant analysis, logistic regression and artificial neural networks. Methodologically, the research was defined as quantitative, regarding its nature, and explanatory, regarding its type. It was developed using data derived from bibliographic and document analysis. The financial demonstrations were collected by means of the Economática ® and the BM$FBOVESPA website. The sample was comprised of 121 companies, being those 70 solvents and 51 insolvents from various sectors. In the analyses, we used 22 indicators of the Traditional Model and 13 of the Fleuriet Model, totalizing 35 indicators. The economic-financial indicators which were a part of, at least, one of the three final models were: X1 (Working Capital over Assets), X3 (NCG over Assets), X4 (NCG over Net Revenue), X8 (Type of Financial Structure), X9 (Net Thermometer), X16 (Net Equity divided by the total demandable), X17 (Asset Turnover), X20 (Net Equity Profitability), X25 (Net Margin), X28 (Debt Composition) and X31 (Net Equity over Asset). The final models presented setting values of: 90.9% (discriminant analysis); 90.9% (logistic regression) and 97.8% (neural networks). The modeling in neural networks presented higher accuracy, which was confirmed by the ROC curve. In conclusion, the indicators of the Fleuriet Model presented relevant results for the research of credit risk, especially if modeled by neural networks.

Uranium mining industry views on ICRP statement on radon

In 2009, the International Commission on Radiological Protection issued a statement on radon which stated that the dose conversion factor for radon progeny would likely double, and the calculation of risk from radon should move to a dosimetric approach, rather than the longstanding epidemiological approach. Through the World Nuclear Association, whose members represent over 90% of the world's uranium production, industry has been examining this issue with a goal of offering expertise and knowledge to assist with the practical implementation of these evolutionary changes to evaluating the risk from radon progeny. Industry supports the continuing use of the most current epidemiological data as a basis for risk calculation, but believes that further examination of these results is needed to better understand the level of conservatism in the potential epidemiological-based risk models. With regard to adoption of the dosimetric approach, industry believes that further work is needed before this is a practical option. In particular, this work should include a clear demonstration of the validation of the dosimetric model which includes how smoking is handled, the establishment of a practical measurement protocol, and the collection of relevant data for modern workplaces. Industry is actively working to address the latter two items.

Effects of management on native and exotic plant communities in Pictured Rocks National Lakeshore in the Upper Peninsula of Michigan

Ecological disturbances may be caused by a range of biotic and abiotic factors. Among these are disturbances that result from human activities such as the introduction of exotic plants and land management activities. This dissertation addresses both of these types of disturbance in ecosystems in the Upper Peninsula of Michigan. Invasive plants are a significant cause of disturbance at Pictured Rocks Natural Lakeshore. Management of invasive plants is dependent on understanding what areas are at risk of being invaded, what the consequences of an invasion are on native plant communities and how effective different tools are for managing the invasive species. A series of risk models are described that predict three stages of invasion (introduction, establishment and spread) for eight invasive plant species at Pictured Rocks National Lakeshore. These models are specific to this location and include species for which models have not previously been produced. The models were tested by collecting point data throughout the park to demonstrate their effectiveness for future detection of invasive plants in the park. Work to describe the impacts and management of invasive plants focused on spotted knapweed in the sensitive Grand Sable Dunes area of Pictured Rocks National Lakeshore. Impacts of spotted knapweed were assessed by comparing vegetation communities in areas with varying amounts of spotted knapweed. This work showed significant increases in species diversity in areas invaded by knapweed, apparently as a result of the presence of a number of non-dune species that have become established in spotted knapweed invaded areas. An experiment was carried out to compare annual spot application of two herbicides, Milestone® and Transline® to target spotted knapweed. This included an assessment of impacts of this type of treatment on non-target species. There was no difference in the effectiveness of the two herbicides, and both significantly reduced the density of spotted knapweed during the course of the study. Areas treated with herbicide developed a higher percent cover of grasses during the study, and suffered limited negative impacts on some sensitive dune species such as beach pea and dune stitchwort, and on some other non-dune species such as hawkweed. The use of these herbicides to reduce the density of spotted knapweed appears to be feasible over large scales.