Asymptotic Implied Volatility at the Second Order with Application to the SABR Model

We provide a general method to compute a Taylor expansion in time of implied volatility for stochastic volatility models, using a heat kernel expansion. Beyond the order 0 implied volatility which is already known, we compute the first order correction exactly at all strikes from the scalar coefficient of the heat kernel expansion. Furthermore, the first correction in the heat kernel expansion gives the second order correction for implied volatility, which we also give exactly at all strikes. As an application, we compute this asymptotic expansion at order 2 for the SABR model.Comment: 27 pages; v2: typos fixed and a few notation changes; v3: published version, typos fixed and comments added. in Large Deviations and Asymptotic Methods in Finance, Springer (2015) 37-6

Calibration of probabilistic quantitative precipitation forecasts with an artificial neural network

A feed-forward neural network is configured to calibrate the bias of a high-resolution probabilistic quantitative precipitation forecast (PQPF) produced by a 12-km version of the NCEP Regional Spectral Model (RSM) ensemble forecast system. Twice-daily forecasts during the 2002-2003 cool season (1 November-31 March, inclusive) are run over four U.S. Geological Survey (USGS) hydrologic unit regions of the southwest United States. Calibration is performed via a cross-validation procedure, where four months are used for training and the excluded month is used for testing. The PQPFs before and after the calibration over a hydrological unit region are evaluated by comparing the joint probability distribution of forecasts and observations. Verification is performed on the 4-km stage IV grid, which is used as "truth." The calibration procedure improves the Brier score (BrS), conditional bias (reliability) and forecast skill, such as the Brier skill score (BrSS) and the ranked probability skill score (RPSS), relative to the sample frequency for all geographic regions and most precipitation thresholds. However, the procedure degrades the resolution of the PQPFs by systematically producing more forecasts with low nonzero forecast probabilities that drive the forecast distribution closer to the climatology of the training sample. The problem of degrading the resolution is most severe over the Colorado River basin and the Great Basin for relatively high precipitation thresholds where the sample of observed events is relatively small. © 2007 American Meteorological Society

Short-range probabilistic quantitative precipitation forecasts over the southwest United States by the RSM ensemble system

The National Centers for Environmental Prediction (NCEP) Regional Spectral Model (RSM) is used to produce twice-daily (0000 and 1200 UTC), high-resolution ensemble forecasts to 24 h. The forecasts are performed at an equivalent horizontal grid spacing of 12 km for the period 1 November 2002 to 31 March 2003 over the southwest United States. The performance of 6-h accumulated precipitation is assessed for 32 U.S. Geological Survey hydrologic catchments. Multiple accuracy and skill measures are used to evaluate probabilistic quantitative precipitation forecasts. NCEP stage-IV precipitation analyses are used as "truth," with verification performed on the stage-IV 4-km grid. The RSM ensemble exhibits a ubiquitous wet bias. The bias manifests itself in areal coverage, frequency of occurrence, and total accumulated precipitation over every region and during every 6-h period. The biases become particularly acute starting with the 1800-0000 UTC interval, which leads to a spurious diurnal cycle and the 1200 UTC cycle being more adversely affected than the 0000 UTC cycle. Forecast quality and value exhibit marked variability over different hydrologic regions. The forecasts are highly skillful along coastal California and the windward slopes of the Sierra Nevada Mountains, but they generally lack skill over the Great Basin and the Colorado basin except over mountain peaks. The RSM ensemble is able to discriminate precipitation events and provide useful guidance to a wide range of users over most regions of California, which suggests that mitigation of the conditional biases through statistical postprocessing would produce major improvements in skill. © 2007 American Meteorological Society

Public Involvement in research within care homes: Benefits and challenges in the APPROACH Study

Public involvement in research (PIR) can improve research design and recruitment. Less is known about how PIR enhances the experience of participation and enriches the data collection process. In a study to evaluate how UK care homes and primary health care services achieve integrated working to promote older people’s health, PIR was integrated throughout the research processes. Objectives This paper aims to present one way in which PIR has been integrated into the design and delivery of a multi-site research study based in care homes. Design A prospective case study design, with an embedded qualitative evaluation of PIR activity. Setting and Participants Data collection was undertaken in six care homes in three sites in England. Six PIR members participated: all had prior personal or work experience in care homes. Data Collection Qualitative data collection involved discussion groups, and site-specific meetings to review experiences of participation, benefits and challenges, and completion of structured fieldwork notes after each care home visit. Results PIR members supported: recruitment, resident and staff interviews and participated in data interpretation. Benefits of PIR work were resident engagement that minimised distress and made best use of limited research resources. Challenges concerned communication and scheduling. Researcher support for PIR involvement was resource intensive. Discussion and Conclusions Clearly defined roles with identified training and support facilitated involvement in different aspectsPublic Involvement in Research members of the research team: Gail Capstick, Marion Cowie, Derek Hope, Rita Hewitt, Alex Mendoza, John Willmott. Also the involvement of Steven Iliffe and Heather Gag

Association between diabetes mellitus and active tuberculosis in Africa and the effect of HIV.

OBJECTIVE: To determine current evidence for the association between diabetes and active tuberculosis in Africa, and how HIV modifies, or not, any association between diabetes and active tuberculosis. METHODS: We conducted a systematic review by searching the EMBASE, Global Health and MEDLINE databases. Studies were eligible for inclusion if they explored the association between diabetes mellitus prevalence and active tuberculosis incidence or prevalence, used a comparison group, were conducted in an African population and adjusted the analysis for at least age. Study characteristics were compared, and risk of bias was assessed. The range of effect estimates was determined for the primary association and for effect modification by HIV. RESULTS: Three eligible studies were identified: two investigated the primary association and two investigated HIV as a potential effect modifier. All studies were case-control studies, including a combined total of 1958 tuberculosis cases and 2111 non-tuberculosis controls. Diabetes diagnostic methods and analysis strategies varied between studies. Individual study adjusted odds ratios of active tuberculosis for the effect of diabetes mellitus (unstratified) ranged from 0.88 (95% CI 0.17-4.58) to 10.7 (95% CI 4.5-26.0). Individual study P-values for HIV interaction ranged from 0.01 to 0.83. Quantitative synthesis of individual study data was not performed due to heterogeneity between studies. CONCLUSIONS: Few data currently exist on the association between diabetes and active tuberculosis in Africa, and on the effect of HIV on this association. Existing data are disparate. More regional research is needed to guide policy and practice on the care and control of tuberculosis and diabetes in Africa

Effects of l-dopa and tolcapone on COMT gene expression in human glial cells

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Scenes, Spaces, and Memory Traces: What Does the Hippocampus Do?

The hippocampus is one of the most closely scrutinized brain structures in neuroscience. While traditionally associated with memory and spatial cognition, in more recent years it has also been linked with other functions, including aspects of perception and imagining fictitious and future scenes. Efforts continue apace to understand how the hippocampus plays such an apparently wide-ranging role. Here we consider recent developments in the field and in particular studies of patients with bilateral hippocampal damage. We outline some key findings, how they have subsequently been challenged, and consider how to reconcile the disparities that are at the heart of current lively debates in the hippocampal literature