The relationship between size, diversification and risk

Property portfolio diversification takes many forms, most of which can be associated with asset size. In other words larger property portfolios are assumed to have greater diversification potential than small portfolios. In addition, since greater diversification is generally associated with lower risk it is assumed that larger property portfolios will also have reduced return variability compared with smaller portfolios. If large property portfolios can simply be regarded as scaled-up, better-diversified versions of small property portfolios, then the greater a portfolio’s asset size, the lower its risk. This suggests a negative relationship between asset size and risk. However, if large property portfolios are not simply scaled-up versions of small portfolios, the relationship between asset size and risk may be unclear. For instance, if large portfolios hold riskier assets or pursue more volatile investment strategies, it may be that a positive relationship between asset size and risk would be observed, even if large property portfolios are more diversified. This paper tests the empirical relationship between property portfolio size, diversification and risk, in Institutional portfolios in the UK, during the period from 1989 to 1999 to determine which of these two characterisations is more appropriate.

Farmers’ attitudes to disease risk management in England: a comparative analysis of sheep and pig farmers

The UK Department for Environment, Food and Rural Affairs (Defra) identified practices to reduce the risk of animal disease outbreaks. We report on the response of sheep and pig farmers in England to promotion of these practices. A conceptual framework was established from research on factors influencing adoption of animal health practices, linking knowledge, attitudes, social influences and perceived constraints to the implementation of specific practices. Qualitative data were collected from nine sheep and six pig enterprises in 2011. Thematic analysis explored attitudes and responses to the proposed practices, and factors influencing the likelihood of implementation. Most feel they are doing all they can reasonably do to minimise disease risk and that practices not being implemented are either not relevant or ineffective. There is little awareness and concern about risk from unseen threats. Pig farmers place more emphasis than sheep farmers on controlling wildlife, staff and visitor management and staff training. The main factors that influence livestock farmers’ decision on whether or not to implement a specific disease risk measure are: attitudes to, and perceptions of, disease risk; attitudes towards the specific measure and its efficacy; characteristics of the enterprise which they perceive as making a measure impractical; previous experience of a disease or of the measure; and the credibility of information and advice. Great importance is placed on access to authoritative information with most seeing vets as the prime source to interpret generic advice from national bodies in the local context. Uptake of disease risk measures could be increased by: improved risk communication through the farming press and vets to encourage farmers to recognise hidden threats; dissemination of credible early warning information to sharpen farmers’ assessment of risk; and targeted information through training events, farming press, vets and other advisers, and farmer groups, tailored to the different categories of livestock farmer.

Interpretation bias in preschool children at risk for anxiety: a prospective study

A story-stem paradigm was used to assess interpretation bias in preschool children. Data were available for 131 children. Interpretation bias, behavioural inhibition (BI) and anxiety were assessed when children were aged between 3 years 2 months and 4 years 5 months. Anxiety was subsequently assessed 12-months, 2-years and 5-years later. A significant difference in interpretation bias was found between participants who met criteria for an anxiety diagnosis at baseline, with clinically anxious participants more likely to complete the ambiguous story-stems in a threat-related way. Threat interpretations significantly predicted anxiety symptoms at 12-month follow-up, after controlling for baseline symptoms, but did not predict anxiety symptoms or diagnoses at either 2-year or 5- year follow-up. There was little evidence for a relationship between BI and interpretation bias. Overall, the pattern of results was not consistent with the hypothesis that interpretation bias plays a role in the development of anxiety. Instead, some evidence for a role in the maintenance of anxiety over relatively short periods of time was found. The use of a story-stem methodology to assess interpretation bias in young children is discussed along with the theoretical and clinical implications of the findings.

Accounting for risk aversion in repeated prisoners’ dilemma games: an experimental test

We apply experimental methods to study the role of risk aversion on players’ behavior in repeated prisoners’ dilemma games. Faced with quantitatively equal discount factors, the most risk-averse players will choose Nash strategies more often in the presence of uncertainty than when future profits are discounted in a deterministic way. Overall, we find that risk aversion relates negatively with the frequency of collusive outcomes.

Assessing the impact on chronic disease of incorporating the societal cost of greenhouse gases into the price of food: an econometric and comparative risk assessment modelling study

Objectives To model the impact on chronic disease of a tax on UK food and drink that internalises the wider costs to society of greenhouse gas (GHG) emissions and to estimate the potential revenue. Design An econometric and comparative risk assessment modelling study. Setting The UK. Participants The UK adult population. Interventions Two tax scenarios are modelled: (A) a tax of £2.72/tonne carbon dioxide equivalents (tCO2e)/100 g product applied to all food and drink groups with above average GHG emissions. (B) As with scenario (A) but food groups with emissions below average are subsidised to create a tax neutral scenario. Outcome measures Primary outcomes are change in UK population mortality from chronic diseases following the implementation of each taxation strategy, the change in the UK GHG emissions and the predicted revenue. Secondary outcomes are the changes to the micronutrient composition of the UK diet. Results Scenario (A) results in 7770 (95% credible intervals 7150 to 8390) deaths averted and a reduction in GHG emissions of 18 683 (14 665to 22 889) ktCO2e/year. Estimated annual revenue is £2.02 (£1.98 to £2.06) billion. Scenario (B) results in 2685 (1966 to 3402) extra deaths and a reduction in GHG emissions of 15 228 (11 245to 19 492) ktCO2e/year. Conclusions Incorporating the societal cost of GHG into the price of foods could save 7770 lives in the UK each year, reduce food-related GHG emissions and generate substantial tax revenue. The revenue neutral scenario (B) demonstrates that sustainability and health goals are not always aligned. Future work should focus on investigating the health impact by population subgroup and on designing fiscal strategies to promote both sustainable and healthy diets.

Using an individual-based model to select among alternative foraging strategies of woodpigeons: data support a memory-based model with a flocking mechanism

Population modelling is increasingly recognised as a useful tool for pesticide risk assessment. For vertebrates that may ingest pesticides with their food, such as woodpigeon (Columba palumbus), population models that simulate foraging behaviour explicitly can help predicting both exposure and population-level impact. Optimal foraging theory is often assumed to explain the individual-level decisions driving distributions of individuals in the field, but it may not adequately predict spatial and temporal characteristics of woodpigeon foraging because of the woodpigeons’ excellent memory, ability to fly long distances, and distinctive flocking behaviour. Here we present an individual-based model (IBM) of the woodpigeon. We used the model to predict distributions of foraging woodpigeons that use one of six alternative foraging strategies: optimal foraging, memory-based foraging and random foraging, each with or without flocking mechanisms. We used pattern-oriented modelling to determine which of the foraging strategies is best able to reproduce observed data patterns. Data used for model evaluation were gathered during a long-term woodpigeon study conducted between 1961 and 2004 and a radiotracking study conducted in 2003 and 2004, both in the UK, and are summarised here as three complex patterns: the distributions of foraging birds between vegetation types during the year, the number of fields visited daily by individuals, and the proportion of fields revisited by them on subsequent days. The model with a memory-based foraging strategy and a flocking mechanism was the only one to reproduce these three data patterns, and the optimal foraging model produced poor matches to all of them. The random foraging strategy reproduced two of the three patterns but was not able to guarantee population persistence. We conclude that with the memory-based foraging strategy including a flocking mechanism our model is realistic enough to estimate the potential exposure of woodpigeons to pesticides. We discuss how exposure can be linked to our model, and how the model could be used for risk assessment of pesticides, for example predicting exposure and effects in heterogeneous landscapes planted seasonally with a variety of crops, while accounting for differences in land use between landscapes.

Using high-frequency water quality data to assess sampling strategies for the EU Water Framework Directive

The EU Water Framework Directive (WFD) requires that the ecological and chemical status of water bodies in Europe should be assessed, and action taken where possible to ensure that at least "good" quality is attained in each case by 2015. This paper is concerned with the accuracy and precision with which chemical status in rivers can be measured given certain sampling strategies, and how this can be improved. High-frequency (hourly) chemical data from four rivers in southern England were subsampled to simulate different sampling strategies for four parameters used for WFD classification: dissolved phosphorus, dissolved oxygen, pH and water temperature. These data sub-sets were then used to calculate the WFD classification for each site. Monthly sampling was less precise than weekly sampling, but the effect on WFD classification depended on the closeness of the range of concentrations to the class boundaries. In some cases, monthly sampling for a year could result in the same water body being assigned to three or four of the WFD classes with 95% confidence, due to random sampling effects, whereas with weekly sampling this was one or two classes for the same cases. In the most extreme case, the same water body could have been assigned to any of the five WFD quality classes. Weekly sampling considerably reduces the uncertainties compared to monthly sampling. The width of the weekly sampled confidence intervals was about 33% that of the monthly for P species and pH, about 50% for dissolved oxygen, and about 67% for water temperature. For water temperature, which is assessed as the 98th percentile in the UK, monthly sampling biases the mean downwards by about 1 °C compared to the true value, due to problems of assessing high percentiles with limited data. Low-frequency measurements will generally be unsuitable for assessing standards expressed as high percentiles. Confining sampling to the working week compared to all 7 days made little difference, but a modest improvement in precision could be obtained by sampling at the same time of day within a 3 h time window, and this is recommended. For parameters with a strong diel variation, such as dissolved oxygen, the value obtained, and thus possibly the WFD classification, can depend markedly on when in the cycle the sample was taken. Specifying this in the sampling regime would be a straightforward way to improve precision, but there needs to be agreement about how best to characterise risk in different types of river. These results suggest that in some cases it will be difficult to assign accurate WFD chemical classes or to detect likely trends using current sampling regimes, even for these largely groundwater-fed rivers. A more critical approach to sampling is needed to ensure that management actions are appropriate and supported by data.

Anticipating future risk in social-ecological systems using fuzzy cognitive mapping: the case of wildfire in the Chiquitania, Bolivia

Understanding complex social-ecological systems, and anticipating how they may respond to rapid change, requires an approach that incorporates environmental, social, economic, and policy factors, usually in a context of fragmented data availability. We employed fuzzy cognitive mapping (FCM) to integrate these factors in the assessment of future wildfire risk in the Chiquitania region, Bolivia. In this region, dealing with wildfires is becoming increasingly challenging due to reinforcing feedbacks between multiple drivers. We conducted semi-structured interviews and constructed different FCMs in focus groups to understand the regional dynamics of wildfire from diverse perspectives. We used FCM modelling to evaluate possible adaptation scenarios in the context of future drier climatic conditions. Scenarios also considered possible failure to respond in time to the emergent risk. This approach proved of great potential to support decision-making for risk management. It helped identify key forcing variables and generate insights into potential risks and trade-offs of different strategies. All scenarios showed increased wildfire risk in the event of more droughts. The ‘Hands-off’ scenario resulted in amplified impacts driven by intensifying trends, affecting particularly the agricultural production. The ‘Fire management’ scenario, which adopted a bottom-up approach to improve controlled burning, showed less trade-offs between wildfire risk reduction and production compared to the ‘Fire suppression’ scenario. Findings highlighted the importance of considering strategies that involve all actors who use fire, and the need to nest these strategies for a more systemic approach to manage wildfire risk. The FCM model could be used as a decision-support tool and serve as a ‘boundary object’ to facilitate collaboration and integration of different forms of knowledge and perceptions of fire in the region. This approach has also the potential to support decisions in other dynamic frontier landscapes around the world that are facing increased risk of large wildfires.

Human toxocariasis in rural Brazilian Amazonia: Seroprevalence, risk factors, and spatial distribution

This population-based cross-sectional study of 403 rural settlers in Brazilian Amazonia revealed an overall rate of IgG seropositivity to Toxocara canis excretory-secretory larval antigen of 26.8% (95% confidence interval [CI], 22.5-31.4%). Multilevel logistic regression analysis identified current infection with hookworm (odds ratio [OR], 2.32; 95% CI, 1.11-4.86) and residence in the most recently occupied sectors of the settlement (OR, 1.81.; 95%CI, 1.3-2.52) as significant risk factors for Toxocara seropositivity; age > 14 years (OR, 0.46; 95% CI, 0.28-0.73) and the presence of cats in the household (OR, 0.57; 95% CI, 0.32-1.02) appeared to be protective. Two significant high-prevalence clusters were detected in the area, together comprising 38.9% of the seropositive subjects; households in the clusters had slightly lower socioeconomic status and were less likely to have cats as pets. The obstacles for controlling human toxocariasis in this and other tropical rural settings are discussed.

Strategies for Supporting Students on Academic Probation

Students who are placed on academic probation often require institutional support to correct unproductive study habits and return to good academic standing. This report reviews academic probation policies and academic recovery plans at four small, private colleges. It includes a discussion of the importance of interventions for at-risk students prior to their placement on academic probation, and concludes with a review of outcomes for students on probation.

Fundos de pensão e práticas de responsabilidade socioempresarial: o caso Previ

Esta dissertação tem como objetivo principal investigar por que os fundos de pensão têm propensão a buscar que as empresas nas quais mantém investimentos persigam práticas de responsabilidade socioempresarial. Para atingir os objetivos propostos foi realizado estudo de caso no maior fundo de pensão da América Latina - PREVI, e que ocupa a primeira posição dentre os fundos de pensão brasileiros em volume financeiro de ativos e tem participação relevante na estrutura de propriedade em 38 empresas. Por meio de entrevistas semiestruturadas foi possível capturar o posicionamento adotado pelos gestores do fundo de pensão com relação às estratégias de responsabilidade socioempresarial nas empresas investidas. Em função da necessidade de melhor compreender a cadeia de valor das organizações, esta dissertação tratou da teoria dos stakeholders, importante na definição estratégica e filosófica das empresas, e da teoria da agência, pois alguns conflitos são identificados na relação entre acionistas majoritários (PREVI) e minoritários. O estudo permitiu identificar que os gestores, não obstante apresentarem discurso voltado para o atendimento dos stakeholders das empresas investidas, têm como foco principal mitigar os riscos ambientais e sociais, em função dos impactos econômicos que estes problemas podem representar para as organizações nas quais investem. Apesar do objetivo instrumental que tem movido o fundo de pensão, suas ações têm levado a um crescimento na adoção de práticas responsáveis pelos participantes do mercado. Foi possível concluir que os gestores do fundo de pensão objeto do estudo de caso ao adotarem princípios de investimentos responsáveis atendem de forma eficaz também a seu dever fiduciário.

Nonparametric tail risk, macroeconomics and stock returns: predictability and risk premia

This paper proposes a new novel to calculate tail risks incorporating risk-neutral information without dependence on options data. Proceeding via a non parametric approach we derive a stochastic discount factor that correctly price a chosen panel of stocks returns. With the assumption that states probabilities are homogeneous we back out the risk neutral distribution and calculate five primitive tail risk measures, all extracted from this risk neutral probability. The final measure is than set as the first principal component of the preliminary measures. Using six Fama-French size and book to market portfolios to calculate our tail risk, we find that it has significant predictive power when forecasting market returns one month ahead, aggregate U.S. consumption and GDP one quarter ahead and also macroeconomic activity indexes. Conditional Fama-Macbeth two-pass cross-sectional regressions reveal that our factor present a positive risk premium when controlling for traditional factors.

Global supply chain risk management: a multicase study in the mango exportation chain

The purpose of this study is to understand how different members manage risk in the global supply chain. Through a multi-case study of the Brazilian mango exportation chain to the United States, four actors of this chain were investigated: supplier, exporter, importer and logistics operator. A research protocol was developed based on previous research conducted by Christopher, et al. (2011). Main results show that risk management is heterogeneous among members of the mango chain, the exporter is the most penalized by the results of the risk chain and collaboration is the main mitigation strategy observed

Asymmetric auctions and risk aversion within independent private valoues

We study tournaments with many ex-ante asymmetric (heterogeneous) contestants as an independent-private-values all-pay auction. The asymmetry is either with respect to the distribution of valuations for the prize or the risk preferences. By characterizing equilibria in tnonotone strategies we show that tournaments \:vith man~y heterogenous contestants are qualitatively distinct. First, with two (or many ex-ante identical) participants, a contestant always exerts some effort with positive probability. In contrast, with many asymmetric participants, one 1night not exert any effort at all, even if there is a positive probability that he has the highest valuation among ali. Second, in tournan1ents with t'wo (o r n1any ex-ante h01nogenous) contestants, equilibrium effort densities are decreasing. This prediction is at odds with experimental evidence that shows the empírica! density might be increasing at high effort levels. V\.lith rnany heterogeneous contestants, however. the increasing bid density is consistent with an equilibrium behavior.

Ambiente para avaliação de controladores fuzzy aplicados ao método de elevação artificial por bombeio centrífugo submerso

From their early days, Electrical Submergible Pumping (ESP) units have excelled in lifting much greater liquid rates than most of the other types of artificial lift and developed by good performance in wells with high BSW, in onshore and offshore environments. For all artificial lift system, the lifetime and frequency of interventions are of paramount importance, given the high costs of rigs and equipment, plus the losses coming from a halt in production. In search of a better life of the system comes the need to work with the same efficiency and security within the limits of their equipment, this implies the need for periodic adjustments, monitoring and control. How is increasing the prospect of minimizing direct human actions, these adjustments should be made increasingly via automation. The automated system not only provides a longer life, but also greater control over the production of the well. The controller is the brain of most automation systems, it is inserted the logic and strategies in the work process in order to get you to work efficiently. So great is the importance of controlling for any automation system is expected that, with better understanding of ESP system and the development of research, many controllers will be proposed for this method of artificial lift. Once a controller is proposed, it must be tested and validated before they take it as efficient and functional. The use of a producing well or a test well could favor the completion of testing, but with the serious risk that flaws in the design of the controller were to cause damage to oil well equipment, many of them expensive. Given this reality, the main objective of the present work is to present an environment for evaluation of fuzzy controllers for wells equipped with ESP system, using a computer simulator representing a virtual oil well, a software design fuzzy controllers and a PLC. The use of the proposed environment will enable a reduction in time required for testing and adjustments to the controller and evaluated a rapid diagnosis of their efficiency and effectiveness. The control algorithms are implemented in both high-level language, through the controller design software, such as specific language for programming PLCs, Ladder Diagram language.