Measuring and Modeling Risk Using High-Frequency Data

Measuring and modeling financial volatility is the key to derivative pricing, asset allocation and risk management. The recent availability of high-frequency data allows for refined methods in this field. In particular, more precise measures for the daily or lower frequency volatility can be obtained by summing over squared high-frequency returns. In turn, this so-called realized volatility can be used for more accurate model evaluation and description of the dynamic and distributional structure of volatility. Moreover, non-parametric measures of systematic risk are attainable, that can straightforwardly be used to model the commonly observed time-variation in the betas. The discussion of these new measures and methods is accompanied by an empirical illustration using high-frequency data of the IBM incorporation and of the DJIA index

Suicide with psychiatric diagnosis and without utilization of psychiatric service

<p>Abstract</p> <p>Background</p> <p>Considerable attention has been focused on the study of suicides among those who have received help from healthcare providers. However, little is known about the profiles of suicide deceased who had psychiatric illnesses but made no contact with psychiatric services prior to their death. Behavioural model of health service use is applied to identify factors associated with the utilization of psychiatric service among the suicide deceased.</p> <p>Methods</p> <p>With respect to completed suicide cases, who were diagnosed with a mental disorder, a comparison study was made between those who had (contact group; n = 52; 43.7%) and those who had not made any contact (non-contact group; n = 67; 56.3%) with a psychiatrist during the final six months prior to death. A <it>sample </it>of 119 deceased cases aged between 15 and 59 with at least one psychiatric diagnosis assessed by the Structured Clinical Interview for DSM-IV-TR (SCID I) were selected from a psychological autopsy study in Hong Kong.</p> <p>Results</p> <p>The contact and non-contact group could be well distinguished from each other by "<it>predisposing</it>" variables: age group & gender, and most of the "<it>enabling"</it>, and "<it>need" </it>variables tested in this study. Multiple logistic regression analysis has found four factors are statistically significantly associated with non-contact suicide deceased: (i) having non-psychotic disorders (OR = 13.5, 95% CI:2.9-62.9), (ii) unmanageable debts (OR = 10.5, CI:2.4-45.3), (iii) being full/partially/self employed at the time of death (OR = 10.0, CI:1.6-64.1) and (iv) having higher levels of social problem-solving ability (SPSI) (OR = 2.0, CI:1.1-3.6).</p> <p>Conclusion</p> <p>The non-contact group was clearly different from the contact group and actually comprised a larger proportion of the suicide population that they could hardly be reached by usual individual-based suicide prevention efforts. For this reason, both universal and strategic suicide prevention measures need to be developed specifically in non-medical settings to reach out to this non-contact group in order to achieve better suicide prevention results.</p

Surface Hardness Impairment of Quorum Sensing and Swarming for Pseudomonas aeruginosa

The importance of rhamnolipid to swarming of the bacterium Pseudomonas aeruginosa is well established. It is frequently, but not exclusively, observed that P. aeruginosa swarms in tendril patterns—formation of these tendrils requires rhamnolipid. We were interested to explain the impact of surface changes on P. aeruginosa swarm tendril development. Here we report that P. aeruginosa quorum sensing and rhamnolipid production is impaired when growing on harder semi-solid surfaces. P. aeruginosa wild-type swarms showed huge variation in tendril formation with small deviations to the “standard” swarm agar concentration of 0.5%. These macroscopic differences correlated with microscopic investigation of cells close to the advancing swarm edge using fluorescent gene reporters. Tendril swarms showed significant rhlA-gfp reporter expression right up to the advancing edge of swarming cells while swarms without tendrils (grown on harder agar) showed no rhlA-gfp reporter expression near the advancing edge. This difference in rhamnolipid gene expression can be explained by the necessity of quorum sensing for rhamnolipid production. We provide evidence that harder surfaces seem to limit induction of quorum sensing genes near the advancing swarm edge and these localized effects were sufficient to explain the lack of tendril formation on hard agar. We were unable to artificially stimulate rhamnolipid tendril formation with added acyl-homoserine lactone signals or increasing the carbon nutrients. This suggests that quorum sensing on surfaces is controlled in a manner that is not solely population dependent

Risk factors for suicide in Bali: a psychological autopsy study

<p>Abstract</p> <p>Background</p> <p>The suicide rate in Bali has significantly increased in recent years. However, to date, there have been no case-control studies investigating risk factors for suicide.</p> <p>Methods</p> <p>A psychological autopsy study was conducted comparing 60 suicide cases and 120 living controls matched in age, sex, and area of residence.</p> <p>Results</p> <p>Multiple logistic regression analysis identified the following risk factors for suicide: at least one diagnosis of axis-I mental disorder (OR: 14.84 CI: 6.12 - 35.94); low level of religious involvement (OR: 7.24 CI: 2.28 - 22.95); and severe interpersonal problems (OR: 3.86 CI: 1.36 - 11.01). Forty-eight (80.0%) of the suicide cases were diagnosed with mental disorders; however, only 16.7% visited a primary care health professional and none received psychiatric treatment during the 1 month prior to death.</p> <p>Conclusion</p> <p>Clinical, religious, and psychosocial factors were associated with suicide. These results highlight the significance of early recognition and treatment of mental disorders, religious activities, and interpersonal problem-solving strategies for suicide prevention in Bali.</p

Intracranial tumors of the central nervous system and air pollution - A nationwide case-control study from Denmark

Background: Inconclusive evidence has suggested a possible link between air pollution and central nervous system (CNS) tumors. We investigated a range of air pollutants in relation to types of CNS tumors. Methods: We identified all (n = 21,057) intracranial tumors in brain, meninges and cranial nerves diagnosed in Denmark between 1989 and 2014 and matched controls on age, sex and year of birth. We established personal 10- year mean residential outdoor exposure to particulate matter < 2.5 μm (PM2.5), nitrous oxides (NOX), primary emitted black carbon (BC) and ozone. We used conditional logistic regression to calculate odds ratios (OR) linearly (per interquartile range (IQR)) and categorically. We accounted for personal income, employment, marital status, use of medication as well as socio-demographic conditions at area level. Results: Malignant tumors of the intracranial CNS was associated with BC (OR: 1.034, 95%CI: 1.005–1.065 per IQR. For NOx the OR per IQR was 1.026 (95%CI: 0.998–1.056). For malignant non-glioma tumors of the brain we found associations with PM2.5 (OR: 1.267, 95%CI: 1.053–1.524 per IQR), BC (OR: 1.049, 95%CI: 0.996–1.106) and NOx (OR: 1.051, 95% CI: 0.996–1.110). Conclusion: Our results suggest that air pollution is associated with malignant intracranial CNS tumors and malignant non-glioma of the brain. However, additional studies are needed

Secondary Prevention of Suicide

Leo Sher and colleagues discuss recent research on interventions to prevent secondary suicide and discuss the additional research that is needed

Long-term air pollution exposure and Parkinson's disease mortality in a large pooled European cohort: An ELAPSE study

BACKGROUND: The link between exposure to ambient air pollution and mortality from cardiorespiratory diseases is well established, while evidence on neurodegenerative disorders including Parkinson's Disease (PD) remains limited. OBJECTIVE: We examined the association between long-term exposure to ambient air pollution and PD mortality in seven European cohorts. METHODS: Within the project 'Effects of Low-Level Air Pollution: A Study in Europe' (ELAPSE), we pooled data from seven cohorts among six European countries. Annual mean residential concentrations of fine particulate matter (PM2.5), nitrogen dioxide (NO2), black carbon (BC), and ozone (O3), as well as 8 PM2.5 components (copper, iron, potassium, nickel, sulphur, silicon, vanadium, zinc), for 2010 were estimated using Europe-wide hybrid land use regression models. PD mortality was defined as underlying cause of death being either PD, secondary Parkinsonism, or dementia in PD. We applied Cox proportional hazard models to investigate the associations between air pollution and PD mortality, adjusting for potential confounders. RESULTS: Of 271,720 cohort participants, 381 died from PD during 19.7 years of follow-up. In single-pollutant analyses, we observed positive associations between PD mortality and PM2.5 (hazard ratio per 5 µg/m3: 1.25; 95% confidence interval: 1.01-1.55), NO2 (1.13; 0.95-1.34 per 10 µg/m3), and BC (1.12; 0.94-1.34 per 0.5 × 10-5m-1), and a negative association with O3 (0.74; 0.58-0.94 per 10 µg/m3). Associations of PM2.5, NO2, and BC with PD mortality were linear without apparent lower thresholds. In two-pollutant models, associations with PM2.5 remained robust when adjusted for NO2 (1.24; 0.95-1.62) or BC (1.28; 0.96-1.71), whereas associations with NO2 or BC attenuated to null. O3 associations remained negative, but no longer statistically significant in models with PM2.5. We detected suggestive positive associations with the potassium component of PM2.5. CONCLUSION: Long-term exposure to PM2.5, at levels well below current EU air pollution limit values, may contribute to PD mortality

Development of Europe-Wide Models for Particle Elemental Composition Using Supervised Linear Regression and Random Forest.

We developed Europe-wide models of long-term exposure to eight elements (copper, iron, potassium, nickel, sulfur, silicon, vanadium, and zinc) in particulate matter with diameter <2.5 μm (PM2.5) using standardized measurements for one-year periods between October 2008 and April 2011 in 19 study areas across Europe, with supervised linear regression (SLR) and random forest (RF) algorithms. Potential predictor variables were obtained from satellites, chemical transport models, land-use, traffic, and industrial point source databases to represent different sources. Overall model performance across Europe was moderate to good for all elements with hold-out-validation R-squared ranging from 0.41 to 0.90. RF consistently outperformed SLR. Models explained within-area variation much less than the overall variation, with similar performance for RF and SLR. Maps proved a useful additional model evaluation tool. Models differed substantially between elements regarding major predictor variables, broadly reflecting known sources. Agreement between the two algorithm predictions was generally high at the overall European level and varied substantially at the national level. Applying the two models in epidemiological studies could lead to different associations with health. If both between- and within-area exposure variability are exploited, RF may be preferred. If only within-area variability is used, both methods should be interpreted equally

Optimised chronic infection models demonstrate that siderophore ‘cheating’ in Pseudomonas aeruginosa is context specific

The potential for siderophore mutants of Pseudomonas aeruginosa to attenuate virulence during infection, and the possibility of exploiting this for clinical ends, have attracted much discussion. This has largely been based on the results of in vitro experiments conducted in iron-limited growth medium, in which siderophore mutants act as social ‘cheats:’ increasing in frequency at the expense of the wild type to result in low-productivity, low-virulence populations dominated by mutants. We show that insights from in vitro experiments cannot necessarily be transferred to infection contexts. First, most published experiments use an undefined siderophore mutant. Whole-genome sequencing of this strain revealed a range of mutations affecting phenotypes other than siderophore production. Second, iron-limited medium provides a very different environment from that encountered in chronic infections. We conducted cheating assays using defined siderophore deletion mutants, in conditions designed to model infected fluids and tissue in cystic fibrosis lung infection and non-healing wounds. Depending on the environment, siderophore loss led to cheating, simple fitness defects, or no fitness effect at all. Our results show that it is crucial to develop defined in vitro models in order to predict whether siderophores are social, cheatable and suitable for clinical exploitation in specific infection contexts