Reactive power planning under conditional-value-at-risk assessment using chance-constrained optimisation

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Non-smooth optimization methods for computation of the conditional value-at-risk and portfolio optimization

We examine numerical performance of various methods of calculation of the Conditional Value-at-risk (CVaR), and portfolio optimization with respect to this risk measure. We concentrate on the method proposed by Rockafellar and Uryasev in (Rockafellar, R.T. and Uryasev, S., 2000, Optimization of conditional value-at-risk. Journal of Risk, 2, 21-41), which converts this problem to that of convex optimization. We compare the use of linear programming techniques against a non-smooth optimization method of the discrete gradient, and establish the supremacy of the latter. We show that non-smooth optimization can be used efficiently for large portfolio optimization, and also examine parallel execution of this method on computer clusters.

An asymptotic test for the Conditional Value-at-Risk

Conditional Value-at-Risk (equivalent to the Expected Shortfall, Tail Value-at-Risk and Tail Conditional Expectation in the case of continuous probability distributions) is an increasingly popular risk measure in the fields of actuarial science, banking and finance, and arguably a more suitable alternative to the currently widespread Value-at-Risk. In my paper, I present a brief literature survey, and propose a statistical test of the location of the CVaR, which may be applied by practising actuaries to test whether CVaR-based capital levels are in line with observed data. Finally, I conclude with numerical experiments and some questions for future research.

Adding value to ecological risk assessment with population modeling

Current measures used to estimate the risks of toxic chemicals are not relevant to the goals of the environmental protection process, and thus ecological risk assessment (ERA) is not used as extensively as it should be as a basis for cost-effective management of environmental resources. Appropriate population models can provide a powerful basis for expressing ecological risks that better inform the environmental management process and thus that are more likely to be used by managers. Here we provide at least five reasons why population modeling should play an important role in bridging the gap between what we measure and what we want to protect. We then describe six actions needed for its implementation into management-relevant ERA.

A conditional probability approach to risk assessment for child sexual offenders with different classes of victim

Specific scales were developed for discriminating child sexual offenders with different classes of victim. The project demonstrates a method of individualising scores on actuarial risk assessment measured in a way that makes them more meaningful for those involved in decision-making about individual child sexual offenders. At present, the only quantifiable approach to specific decision-making relies on a general prediction of future behaviour, based on group data. The Bayesian approach is one method that can be used to assist decision-makers to use this information in ways that lead to the more appropriate management of risk. Ultimately, the better management of known child sexual offenders will lead to fewer offences and a reduction in the number of children who lives are profoundly affected by sexual victimisation.

Value of the SYNTAX score for risk assessment in the all-comers population of the randomized multicenter LEADERS (Limus Eluted from A Durable versus ERodable Stent coating) trial

OBJECTIVES: We aimed to assess the predictive value of the SYNTAX score (SXscore) for major adverse cardiac events in the all-comers population of the LEADERS (Limus Eluted from A Durable versus ERodable Stent coating) trial. BACKGROUND: The SXscore has been shown to be an effective predictor of clinical outcomes in patients with multivessel disease undergoing percutaneous coronary intervention. METHODS: The SXscore was prospectively collected in 1,397 of the 1,707 patients enrolled in the LEADERS trial (patients after surgical revascularization were excluded). Post hoc analysis was performed by stratifying clinical outcomes at 1-year follow-up, according to 1 of 3 SXscore tertiles. RESULTS: The 1,397 patients were divided into tertiles based on the SXscore in the following fashion: SXscore8 and 16 (SXhigh) (n=461). At 1-year follow-up, there was a significantly lower number of patients with major cardiac event-free survival in the highest tertile of SXscore (SXlow=92.2%, SXmid=91.1%, and SXhigh=84.6%; p<0.001). Death occurred in 1.5% of SXlow patients, 2.1% of SXmid patients, and 5.6% of SXhigh patients (hazard ratio [HR]: 1.97, 95% confidence interval [CI]: 1.29 to 3.01; p=0.002). The myocardial infarction rate tended to be higher in the SXhigh group. Target vessel revascularization was 11.3% in the SXhigh group compared with 6.3% and 7.8% in the SXlow and SXmid groups, respectively (HR: 1.38, 95% CI: 1.1 to 1.75; p=0.006). Composite of cardiac death, myocardial infarction, and clinically indicated target vessel revascularization was 7.8%, 8.9%, and 15.4% in the SXlow, SXmid, and SXhigh groups, respectively (HR: 1.47, 95% CI: 1.19 to 1.81; p<0.001). CONCLUSIONS: The SXscore, when applied to an all-comers patient population treated with drug-eluting stents, may allow prospective risk stratification of patients undergoing percutaneous coronary intervention. (LEADERS Trial Limus Eluted From A Durable Versus ERodable Stent Coating; NCT00389220).

Forecasting time-varying value-at-risk

In this thesis we are interested in financial risk and the instrument we want to use is Value-at-Risk (VaR). VaR is the maximum loss over a given period of time at a given confidence level. Many definitions of VaR exist and some will be introduced throughout this thesis. There two main ways to measure risk and VaR: through volatility and through percentiles. Large volatility in financial returns implies greater probability of large losses, but also larger probability of large profits. Percentiles describe tail behaviour. The estimation of VaR is a complex task. It is important to know the main characteristics of financial data to choose the best model. The existing literature is very wide, maybe controversial, but helpful in drawing a picture of the problem. It is commonly recognised that financial data are characterised by heavy tails, time-varying volatility, asymmetric response to bad and good news, and skewness. Ignoring any of these features can lead to underestimating VaR with a possible ultimate consequence being the default of the protagonist (firm, bank or investor). In recent years, skewness has attracted special attention. An open problem is the detection and modelling of time-varying skewness. Is skewness constant or there is some significant variability which in turn can affect the estimation of VaR? This thesis aims to answer this question and to open the way to a new approach to model simultaneously time-varying volatility (conditional variance) and skewness. The new tools are modifications of the Generalised Lambda Distributions (GLDs). They are four-parameter distributions, which allow the first four moments to be modelled nearly independently: in particular we are interested in what we will call para-moments, i.e., mean, variance, skewness and kurtosis. The GLDs will be used in two different ways. Firstly, semi-parametrically, we consider a moving window to estimate the parameters and calculate the percentiles of the GLDs. Secondly, parametrically, we attempt to extend the GLDs to include time-varying dependence in the parameters. We used the local linear regression to estimate semi-parametrically conditional mean and conditional variance. The method is not efficient enough to capture all the dependence structure in the three indices —ASX 200, S&P 500 and FT 30—, however it provides an idea of the DGP underlying the process and helps choosing a good technique to model the data. We find that GLDs suggest that moments up to the fourth order do not always exist, there existence appears to vary over time. This is a very important finding, considering that past papers (see for example Bali et al., 2008; Hashmi and Tay, 2007; Lanne and Pentti, 2007) modelled time-varying skewness, implicitly assuming the existence of the third moment. However, the GLDs suggest that mean, variance, skewness and in general the conditional distribution vary over time, as already suggested by the existing literature. The GLDs give good results in estimating VaR on three real indices, ASX 200, S&P 500 and FT 30, with results very similar to the results provided by historical simulation.

Health risk from the use of roof-harvested rainwater in Southeast Queensland, Australia, as potable or nonpotable water, determined using quantitative microbial risk assessment

A total of 214 rainwater samples from 82 tanks were collected in urban Southeast Queensland (SEQ) in Australia and analysed for the zoonotic bacterial and protozoan pathogen using real-time binary PCR and quantitative PCR (qPCR). Quantitative Microbial Risk Assessment (QMRA) analysis was used to quantify the risk of infection associated with the exposure to potential pathogens from potable and non-potable uses of roof-harvested rainwater. Of the 214 samples tested, 10.7%, 9.8%, and 5.6%, and 0.4% samples were positive for Salmonella invA, Giardia lamblia β-giardin , Legionella pneumophila mip, and Campylobacter jejuni mapA genes. Cryptosporidium parvum could not be detected. The estimated numbers of viable Salmonella spp., G. lamblia β-giradin, and L. pneumophila genes ranged from 1.6 × 101 to 9.5 × 101 cells, 1.4 × 10-1 to 9.0 × 10-1 cysts, and 1.5 × 101 to 4.3 × 101 per 1000 ml of water, respectively. Six risk scenarios were considered from exposure to Salmonella spp., G. lamblia and L. pneumophila. For Salmonella spp., and G. lamblia, these scenarios were: (1) liquid ingestion due to drinking of rainwater on a daily basis (2) accidental liquid ingestion due to garden hosing twice a week (3) aerosol ingestion due to showering on a daily basis, and (4) aerosol ingestion due to hosing twice a week. For L. pneumophila, these scenarios were: (5) aerosol inhalation due to showering on a daily basis, and (6) aerosol inhalation due to hosing twice a week. The risk of infection from Salmonella spp., G. lamblia, and L. pneumophila associated with the use of rainwater for showering and garden hosing was calculated to be well below the threshold value of one extra infection per 10,000 persons per year in urban SEQ. However, the risk of infection from ingesting Salmonella spp. and G. lamblia via drinking exceeds this threshold value, and indicates that if undisinfected rainwater were ingested by drinking, then the gastrointestinal diseases of Salmonellosis and Giardiasis is expected to range from 5.0 × 100 to 2.8 × 101 (Salmonellosis) and 1.0 × 101 to 6.4 × 101 (Giardiasis) cases per 10,000 persons per year, respectively. Since this health risk seems higher than that expected from the reported incidences of gastroenteritis, the assumptions used to estimate these infection risks are critically examined. Nonetheless, it would seem prudent to disinfect rainwater for potable use.

Diversification and value-at-risk

A pervasive and puzzling feature of banks’ Value-at-Risk (VaR) is its abnormally high level, which leads to excessive regulatory capital. A possible explanation for the tendency of commercial banks to overstate their VaR is that they incompletely account for the diversification effect among broad risk categories (e.g., equity, interest rate, commodity, credit spread, and foreign exchange). By underestimating the diversification effect, bank’s proprietary VaR models produce overly prudent market risk assessments. In this paper, we examine empirically the validity of this hypothesis using actual VaR data from major US commercial banks. In contrast to the VaR diversification hypothesis, we find that US banks show no sign of systematic underestimation of the diversification effect. In particular, diversification effects used by banks is very close to (and quite often larger than) our empirical diversification estimates. A direct implication of this finding is that individual VaRs for each broad risk category, just like aggregate VaRs, are biased risk assessments.

Riding the tide of biopharming in Africa: Considerations for risk assessment

In the past few years, plant biotechnology has gone beyond traditional agricultural production of food, feed and fibre, and moved to address more complex contemporary health, social and industrial challenges. The new era involves production of novel pharmaceutical products, speciality and fine chemicals, phytoremediation and production of renewable energy resources to replace non-renewable fossil fuels. Plants have been shown to provide a genuine and low-cost alternative production system for high-value products. Currently, the principal plant-made products include antibodies, feed additives, vaccine antigens and hormones for human and animal health, and industrial proteins. Despite the unique advantages of scalability, cost and product safety, issues of politics, environmental impact, regulation and socioeconomics still limit the adoption of biopharmaceuticals, especially in the developing world. Plant-based production systems have further complicated biosafety, gene flow and environmental impact assessments with generally genetically modified plants, topics that are already partially understood. This article provides a background to biopharming, highlighting basic considerations for risk assessment and regulation in developing countries, with an emphasis on plant-based vaccine production in South Africa.

Planning for transit system reliability using productive performance and risk assessment

Urban transit system performance may be quantified and assessed using transit capacity and productive capacity for planning, design and operational management. Bunker (4) defines important productive performance measures of an individual transit service and transit line. Transit work (p-km) captures transit task performed over distance. Transit productiveness (p-km/h) captures transit work performed over time. This paper applies productive performance with risk assessment to quantify transit system reliability. Theory is developed to monetize transit segment reliability risk on the basis of demonstration Annual Reliability Event rates by transit facility type, segment productiveness, and unit-event severity. A comparative example of peak hour performance of a transit sub-system containing bus-on-street, busway, and rail components in Brisbane, Australia demonstrates through practical application the importance of valuing reliability. Comparison reveals the highest risk segments to be long, highly productive on street bus segments followed by busway (BRT) segments and then rail segments. A transit reliability risk reduction treatment example demonstrates that benefits can be significant and should be incorporated into project evaluation in addition to those of regular travel time savings, reduced emissions and safety improvements. Reliability can be used to identify high risk components of the transit system and draw comparisons between modes both in planning and operations settings, and value improvement scenarios in a project evaluation setting. The methodology can also be applied to inform daily transit system operational management.

Planning for transit system reliability using productive performance and risk assessment

Urban transit system performance may be quantified and assessed using transit capacity and productive capacity for planning, design and operational management. Bunker (4) defines important productive performance measures of an individual transit service and transit line. Transit work (p-km) captures transit task performed over distance. Transit productiveness (p-km/h) captures transit work performed over time. This paper applies productive performance with risk assessment to quantify transit system reliability. Theory is developed to monetize transit segment reliability risk on the basis of demonstration Annual Reliability Event rates by transit facility type, segment productiveness, and unit-event severity. A comparative example of peak hour performance of a transit sub-system containing bus-on-street, busway, and rail components in Brisbane, Australia demonstrates through practical application the importance of valuing reliability. Comparison reveals the highest risk segments to be long, highly productive on street bus segments followed by busway (BRT) segments and then rail segments. A transit reliability risk reduction treatment example demonstrates that benefits can be significant and should be incorporated into project evaluation in addition to those of regular travel time savings, reduced emissions and safety improvements. Reliability can be used to identify high risk components of the transit system and draw comparisons between modes both in planning and operations settings, and value improvement scenarios in a project evaluation setting. The methodology can also be applied to inform daily transit system operational management.

Sorption, degradation and mobility of microcystins in Chinese agriculture soils: Risk assessment for groundwater protection

In the present paper, sorption, persistence, and leaching behavior of three microcystin variants in Chinese agriculture soils were examined. Based on this study, the values of capacity factor and slope for three MCs variants in three soils ranged from 0.69 to 6.00, and 1.01 to 1.54, respectively. The adsorption of MCs in the soils decreased in the following order: RR > Dha(7) LR > LR. Furthermore, for each MC variant in the three soils, the adsorption rate in the soils decreased in the following order: soil A > soil C > soil B. The calculated half-time ranged between 7.9 and 17.8 days for MC-RR, 6.0-17.1 days for MC-LR, and 7.1-10.2 days for MC-Dha(7) LR. Results from leaching experiments demonstrated that recoveries of toxins in leachates ranged from 0-16.7% for RR, 73.2-88.9% for LR, and 8.9-73.1% for Dha 7 LR. The GUS value ranged from 1.48 to 2.06 for RR, 1.82-2.88 for LR, and 1.76-2.09 for Dha(7) LR. Results demonstrated the use of cyanobacterial collections as plant fertilizer is likely to be unsafe in soils. (c) 2006 Elsevier Ltd. All rights reserved.

Assessing the environmental consequences of CO2 leakage from geological CCS: Generating evidence to support environmental risk assessment

At the start of the industrial revolution (circa 1750) the atmospheric concentration of carbon dioxide (CO2) was around 280 ppm. Since that time the burning of fossil fuel, together with other industrial processes such as cement manufacture and changing land use, has increased this value to 400 ppm, for the first time in over 3 million years. With CO2 being a potent greenhouse gas, the consequence of this rise for global temperatures has been dramatic, and not only for air temperatures. Global Sea Surface Temperature (SST) has warmed by 0.4–0.8 °C during the last century, although regional differences are evident (IPCC, 2007). This rise in atmospheric CO2 levels and the resulting global warming to some extent has been ameliorated by the oceanic uptake of around one quarter of the anthropogenic CO2 emissions (Sabine et al., 2004). Initially this was thought to be having little or no impact on ocean chemistry due to the capacity of the ocean’s carbonate buffering system to neutralise the acidity caused when CO2 dissolves in seawater. However, this assumption was challenged by Caldeira and Wickett (2005) who used model predictions to show that the rate at which carbonate buffering can act was far too slow to moderate significant changes to oceanic chemistry over the next few centuries. Their model predicted that since pre-industrial times, ocean surface water pH had fallen by 0.1 pH unit, indicating a 30% increase in the concentration of H+ ions. Their model also showed that the pH of surface waters could fall by up to 0.4 units before 2100, driven by continued and unabated utilisation of fossil fuels. Alongside increasing levels of dissolved CO2 and H+ (reduced pH) an increase in bicarbonate ions together with a decrease in carbonate ions occurs. These chemical changes are now collectively recognised as “ocean acidification”. Concern now stems from the knowledge that concentrations of H+, CO2, bicarbonate and carbonate ions impact upon many important physiological processes vital to maintaining health and function in marine organisms. Additionally, species have evolved under conditions where the carbonate system has remained relatively stable for millions of years, rendering them with potentially reduced capacity to adapt to this rapid change. Evidence suggests that, whilst the impact of ocean acidification is complex, when considered alongside ocean warming the net effect on the health and productivity of the oceans will be detrimental.