The benefit of modeling jumps in realized volatility for risk prediction : evidence from Chinese mainland stocks

Recent literature has focused on realized volatility models to predict financial risk. This paper studies the benefit of explicitly modeling jumps in this class of models for value at risk (VaR) prediction. Several popular realized volatility models are compared in terms of their VaR forecasting performances through a Monte Carlo study and an analysis based on empirical data of eight Chinese stocks. The results suggest that careful modeling of jumps in realized volatility models can largely improve VaR prediction, especially for emerging markets where jumps play a stronger role than those in developed markets.

Cutaneous markers of photo-damage and risk of basal cell carcinoma of the skin : a meta-analysis

BACKGROUND: Epidemiologic research has demonstrated that cutaneous markers of photo-damage are associated with risk of basal cell carcinoma (BCC). However there has been no previous attempt to calculate pooled risk estimates. METHODS: We conducted a systematic review and meta-analysis after extracting relevant studies published up to January 2013 from five electronic databases. Eligible studies were those that permitted quantitative assessment of the association between histologically-confirmed BCC and actinic keratoses, solar elastosis, solar lentigines, or telangiectasia. RESULTS: Seven eligible studies were identified and summary odds ratios (OR) were calculated using both random and quality effects models. Having more than ten actinic keratoses was most strongly associated with BCC, conferring up to a 5-fold increase in risk (OR: 4.97; 95% CI: 3.26, 7.58). Other factors, including solar elastosis, solar lentigines, and telangiectasia had weaker but positive associations with BCC with ORs around 1.5. CONCLUSIONS: Markers of chronic photo-damage are positively associated with BCC. The presence of actinic keratoses was the most strongly associated with BCC of the markers examined. IMPACT: This work highlights the relatively modest association between markers of chronic ultraviolet exposure and BCC.

Natural disaster risk-informed for a better public infrastructure asset planning in Indonesian Central Government

The natural disasters incident that frequently hit Indonesia are floods, severe droughts, tsunamis, earth-quakes, volcano, eruptions, landslides, windstorm and forest fires. The impact of those natural disasters are significantly severe and affecting the quality of life of the community due to the breakdown of the public as-sets as one source to deliver public services. This paper is aimed to emphasis the importance of natural disaster risk-informed in relation to public asset management in Indonesian Central Government, particularly in asset planning stage where asset decision is made as the gate into the whole public asset management processes. A Case study in the Ministry of Finance Indonesia as the central government public asset manager and in 5 (five) line ministries/governmental agencies as public asset users was used as the approach to achieved the research objective. The case study devoured three data collection techniques i.e. interviews, observations and document archival which will be analysed by a content analysis approach. The result of the study indicates that Indonesian geographical position exposing many of public infra-structure assets as a high vulnerability to natural disasters. Information on natural-disaster trends and predictions to identify and measure the risks are available, however, such information are not utilise and integrated to the process of public infrastructure asset planning as the gate to the whole public asset management processes. Therefore, in order to accommodate and incorporate this natural disaster risk-information into public asset management processes, particularly in public asset planning, a public asset performance measurements framework should be adopted and applied in the process as one sources in making decision for infrastructure asset planning. Findings from this study provide useful input for the Ministry of Finance as public asset manager, scholars and private asset management practitioners in Indonesia to establish natural disaster risks awareness in public infrastructure asset management processes.

Risk factors for impaired respiratory function during nurse-administered procedural sedation and analgesia in the cardiac catheterisation laboratory : a matched case-control study

Background: Side effects of the medications used for procedural sedation and analgesia in the cardiac catheterisation laboratory are known to cause impaired respiratory function. Impaired respiratory function poses considerable risk to patient safety as it can lead to inadequate oxygenation. Having knowledge about the conditions that predict impaired respiratory function prior to the procedure would enable nurses to identify at-risk patients and selectively implement intensive respiratory monitoring. This would reduce the possibility of inadequate oxygenation occurring. Aim: To identify pre-procedure risk factors for impaired respiratory function during nurse-administered procedural sedation and analgesia in the cardiac catheterisation laboratory. Design: Retrospective matched case–control. Methods: 21 cases of impaired respiratory function were identified and matched to 113 controls from a consecutive cohort of patients over 18 years of age. Conditional logistic regression was used to identify risk factors for impaired respiratory function. Results: With each additional indicator of acute illness, case patients were nearly two times more likely than their controls to experience impaired respiratory function (OR 1.78; 95% CI 1.19–2.67; p = 0.005). Indicators of acute illness included emergency admission, being transferred from a critical care unit for the procedure or requiring respiratory or haemodynamic support in the lead up to the procedure. Conclusion: Several factors that predict the likelihood of impaired respiratory function were identified. The results from this study could be used to inform prospective studies investigating the effectiveness of interventions for impaired respiratory function during nurse-administered procedural sedation and analgesia in the cardiac catheterisation laboratory.

Acute illness is a risk factor for impaired respiratory function during nurse-administered procedural sedation and analgesia in the cardiac catheterization laboratory

Impaired respiratory function (IRF) during procedural sedation and analgesia (PSA) poses considerable risk to patient safety as it can lead to inadequate oxygenation and ventilation. Risk factors that can be screened prior to the procedure have not been identified for the cardiac catheterization laboratory (CCL).

Screening in early childhood for risk of later mental health problems : a longitudinal study

Depression in childhood or adolescence is associated with increased rates of depression in adulthood. Does this justify efforts to detect (and treat) those with symptoms of depression in early childhood or adolescence? The aim of this study was to determine how well symptoms of anxiety/depression (A-D) in early childhood and adolescence predict adult mental health. The study sample is taken from a population-based prospective birth cohort study. Of the 8556 mothers initially approached to participate 8458 agreed, of whom 7223 mothers gave birth to a live singleton baby. Children were screened using modified Child Behaviour Checklist (CBCL) scales for internalizing and total problems (T-P) at age 5 and the CBCL and Youth Self Report (YSR) A-D subscale and T-P scale at age 14. At age 21, a sub-sample of 2563 young adults in this cohort were administered the CIDI-Auto. Results indicated that screening at age 5 would detect few later cases of significant mental ill-health. Using a cut-point of 20% for internalizing at child age 5 years the CBCL had sensitivities of only 25% and 18% for major depression and anxiety disorders at 21 years, respectively. At age 14, the YSR generally performed a little better than the CBCL as a screening instrument, but neither performed at a satisfactory level. Of the children who were categorised as having YSR A-D at 14 years 30% and 37% met DSM-IV criteria for major depression and anxiety disorders, respectively, at age 21. Our findings challenge an existing movement encouraging the detection and treatment of those with symptoms of mental illness in early childhood.

Validating a screening tool for mental health and substance use risk in an Indigenous prison population

Introduction and Aims: The Indigenous Risk Impact Screen (IRIS) is a validated culturally appropriate and widely used tool in the community for assessing substance use and mental disorder. This research aimed to assess the utility of this tool in an Indigenous prison population. Design and Methods: The study used data collected from a cross-sectional study of mental health among indigenous inmates in Queensland custodial centres (n=395, 84% male). Participants were administered a modified version of the IRIS, and ICD-10 diagnoses of substance use, depressive and anxiety disorders obtained using the Composite International Diagnostic Interview (CIDI). The concurrent validity of the modified IRIS was assessed against those of the CIDI. Results: 312 people screened as high risk for a substance use disorder and 179 were high risk for mental problems. 73% of males and 88% of females were diagnosed with a mental disorder. The IRIS was an effective screener for substance use disorders, with high sensitivity (Se) of 94% and low specificity (Sp) of 33%. The screener was less effective in identifying depression (Se 82%, Sp 59%) and anxiety (Se 68%, Sp 60%). Discussion: The IRIS is the first culturally appropriate screening instrument to be validated for the risk of drug and alcohol and mental disorder among Indigenous adults in custody. Conclusions: This study demonstrated that the IRIS is a valid tool for screening of alcohol and drug use risk among an incarcerated Indigenous population. The IRIS could offer an opportunity to improve the identification, treatment and health outcomes for incarcerated Indigenous adults.

PCV13 Perceptions of health during pregnancy increase the risk of cardiovascular disease

OBJECTIVES: To examine the prospective association between perception of health during pregnancy and cardiovascular risk factor of mothers 21 years after the index pregnancy. METHODS: Data used were from the Mater University Study of Pregnancy (MUSP), a community- based prospective birth ohort study begun in Brisbane, Australia, in 1983. Logistic regression analyses were conducted. RESULTS: Data were available for 3692 women. Women who perceived themselves as not having a straight forward pregnancy had twice the odds (adjusted OR 2.0, 95% CI 1.1-3.8) of being diagnosed with heart disease 21 years after the indexpregnancyascomparedtowomenwith a straight forward pregnancy. Apart from that, women who had complications (other than serious pregnancy complications) during the pregnancy were also at30%increased odds (adjustedOR 1.3, 95% CI 1.0-1.6) of having hypertension 21 years later. CONCLUSIONS: As a whole, our study suggests that pregnant women who perceived that they had complications and did not have a straight forward pregnancy are likely to experience poorer cardiovascular outcomes 21 years after the pregnancy.

Re-framing infrastructure investment decision-making processes : a preliminary scoping study for urban flood risk management in Jakarta, Indonesia

Jakarta, Indonesia’s chronic housing shortage poses multiple challenges for contemporary policy-makers. While it may be in the city’s interest to increase the availability of housing, there is limited land to do so. Market pressures, in tandem with government’s desire for housing availability, demand consideration of even marginal lands, such as those within floodplains, for development. Increasingly, planning for a flood resilient Jakarta is complicated by a number of factors, including: the city is highly urbanized and land use data is limited; flood management is technically complex, creating potential barriers to engagement for both decision-makers and the public; inherent uncertainty exists throughout modelling efforts, central to management; and risk and liability for infrastructure investments is unclear. These obstacles require localized watershed-level participatory planning to address risks of flooding where possible and reduce the likelihood that informal settlements occur in areas of extreme risk. This paper presents a preliminary scoping study for determination of an effective participatory planning method to encourage more resilient development. First, the scoping study provides background relevant to the challenges faced in planning for contemporary Jakarta. Second, the study examines the current use of decision-support tools, such as Geographic Information Systems (GIS), in planning for Jakarta. Existing capacity in the use of GIS allows for consideration of the use of an emerging method of community consultation - Multi-Criteria Decision-Making (MCDM) support systems infused with geospatial information - to aid in engagement with the public and improve decision-making outcomes. While these methods have been used in Australia to promote stakeholder engagement in urban intensification, the planned research will be an early introduction of the method to Indonesia. As a consequence of this intervention, it is expected that planning activities will result in a more resilient city, capable of engaging with disaster risk management in a more effective manner.

Letter : anxiety score as a risk factor for radial artery vasospasm during radial interventions : a pilot study

I read with interest the article in Angiology that determined the role of anxiety level on radial artery spasm during transradial coronary angiography.1 As the importance of conducting more randomised controlled trials using anxiolytics to define the relation between anxiety and vasospasm was noted by the authors, I offer the following insights for investigators to consider when conducting such research. While previous research has already identified that moderate procedural sedation and opioid analgesia reduces the incidence of vasospasm,2 the identification of risk factors in the present study is hypothesis generating as to how outcomes might be even further improved. It is possible that selectively applying either even more intensive sedation and analgesia or complementary non-pharmacological stress-reducing therapies, such as music therapy or visualisation and attentive behaviour, to patients ‘at-risk’ of vasospasm (women and those with high levels of anxiety prior to the procedure) might lead to even better patient outcomes...

A data mining driven crash risk profiling method for road asset management

This thesis takes a new data mining approach for analyzing road/crash data by developing models for the whole road network and generating a crash risk profile. Roads with an elevated crash risk due to road surface friction deficit are identified. The regression tree model, predicting road segment crash rate, is applied in a novel deployment coined regression tree extrapolation that produces a skid resistance/crash rate curve. Using extrapolation allows the method to be applied across the network and cope with the high proportion of missing road surface friction values. This risk profiling method can be applied in other domains.

A multi-objective optimization approach for coordinating available transfer capability with risk control

In the electricity market environment, coordination of system reliability and economics of a power system is of great significance in determining the available transfer capability (ATC). In addition, the risks associated with uncertainties should be properly addressed in the ATC determination process for risk-benefit maximization. Against this background, it is necessary that the ATC be optimally allocated and utilized within relative security constraints. First of all, the non-sequential Monte Carlo stimulation is employed to derive the probability density distribution of ATC of designated areas incorporating uncertainty factors. Second, on the basis of that, a multi-objective optimization model is formulated to determine the multi-area ATC so as to maximize the risk-benefits. Then, the solution to the developed model is achieved by the fast non-dominated sorting (NSGA-II) algorithm, which could decrease the risk caused by uncertainties while coordinating the ATCs of different areas. Finally, the IEEE 118-bus test system is served for demonstrating the essential features of the developed model and employed algorithm.

Reducing the Risk of Alcohol and Other Drugs in Construction : An Australian Assessment

There is increasing concern about the impact of employees’ alcohol and other drug (AOD) consumption on workplace safety, particularly within the construction industry. No known study has scientifically evaluated the relationship between the use of drugs and alcohol and safety impacts in construction, and there has been only limited adoption of nationally coordinated strategies, supported by employers and employees to render it socially unacceptable to arrive at a construction workplace with impaired judgment from AODs. This research aims to scientifically evaluate the use of AODs within the Australian construction industry in order to reduce the potential resulting safety and performance impacts and engender a cultural change in the workforce. Using the Alcohol Use Disorders Identification Test (AUDIT), the study will adopt both quantitative and qualitative methods to evaluate the extent of general AOD use in the industry. Results indicate that a proportion of the construction sector may be at risk of hazardous alcohol consumption. A total of 286 respondents (58%) scored above the cut-off score for risky alcohol use with 43 respondents (15%) scoring in the significantly ‘at risk’ category. Other drug use was also identified as a major issue that must be addressed. Results support the need for evidence-based, preventative educational initiatives that are tailored specifically to the construction industry.

A data mining driven risk profiling method for road asset management

Road surface skid resistance has been shown to have a strong relationship to road crash risk, however, applying the current method of using investigatory levels to identify crash prone roads is problematic as they may fail in identifying risky roads outside of the norm. The proposed method analyses a complex and formerly impenetrable volume of data from roads and crashes using data mining. This method rapidly identifies roads with elevated crash-rate, potentially due to skid resistance deficit, for investigation. A hypothetical skid resistance/crash risk curve is developed for each road segment, driven by the model deployed in a novel regression tree extrapolation method. The method potentially solves the problem of missing skid resistance values which occurs during network-wide crash analysis, and allows risk assessment of the major proportion of roads without skid resistance values.