Bayesian modeling and forecasting of 24-hour high-frequency volatility: A case study of the financial crisis

This paper estimates models of high frequency index futures returns using `around the clock' 5-minute returns that incorporate the following key features: multiple persistent stochastic volatility factors, jumps in prices and volatilities, seasonal components capturing time of the day patterns, correlations between return and volatility shocks, and announcement effects. We develop an integrated MCMC approach to estimate interday and intraday parameters and states using high-frequency data without resorting to various aggregation measures like realized volatility. We provide a case study using financial crisis data from 2007 to 2009, and use particle filters to construct likelihood functions for model comparison and out-of-sample forecasting from 2009 to 2012. We show that our approach improves realized volatility forecasts by up to 50% over existing benchmarks.Comment: 48 pages, 7 figure

Multiple-line inference of selection on quantitative traits

Trait differences between species may be attributable to natural selection. However, quantifying the strength of evidence for selection acting on a particular trait is a difficult task. Here we develop a population-genetic test for selection acting on a quantitative trait which is based on multiple-line crosses. We show that using multiple lines increases both the power and the scope of selection inference. First, a test based on three or more lines detects selection with strongly increased statistical significance, and we show explicitly how the sensitivity of the test depends on the number of lines. Second, a multiple-line test allows to distinguish different lineage-specific selection scenarios. Our analytical results are complemented by extensive numerical simulations. We then apply the multiple-line test to QTL data on floral character traits in plant species of the Mimulus genus and on photoperiodic traits in different maize strains, where we find a signatures of lineage-specific selection not seen in a two-line test.Comment: 21 pages, 11 figures; to appear in Genetic

Four-dimensional light shaping: manipulating ultrafast spatio-temporal foci in space and time

Spectral dispersion of ultrashort pulses allows simultaneous focusing of light in both space and time creating so-called spatio-temporal foci. Such space-time coupling may be combined with existing holographic techniques to give a further dimension of control when generating focal light fields. It is shown that a phase-only hologram placed in the pupil plane of an objective and illuminated by a spatially chirped ultrashort pulse can be used to generate three dimensional arrays of spatio-temporally focused spots. Exploiting the pulse front tilt generated at focus when applying simultaneous spatial and temporal focusing (SSTF), it is possible to overlap neighbouring foci in time to create a smooth intensity distribution. The resulting light field displays a high level of axial confinement, with experimental demonstrations given through two-photon microscopy and non-linear laser fabrication of glass

Particle Learning and Smoothing

Particle learning (PL) provides state filtering, sequential parameter learning and smoothing in a general class of state space models. Our approach extends existing particle methods by incorporating the estimation of static parameters via a fully-adapted filter that utilizes conditional sufficient statistics for parameters and/or states as particles. State smoothing in the presence of parameter uncertainty is also solved as a by-product of PL. In a number of examples, we show that PL outperforms existing particle filtering alternatives and proves to be a competitor to MCMC.Comment: Published in at http://dx.doi.org/10.1214/10-STS325 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

MR motility imaging in Crohn's disease improves lesion detection compared with standard MR imaging

Objective: To evaluate retrospectively in patients with Crohn's disease (CD) if magnetic resonance (MR) motility alterations correlate with CD typical lesions leading to an increased detection rate. Methods: Forty patients with histologically proven CD underwent MR enterography (MRE), including coronal cine sequences (cine MRE), in addition to the standard CD MR protocol. Two blinded readings were performed with and without cine MRE. Locations presenting motility alterations on the cine sequences were analysed on standard MRE for CD-related lesions. This was compared with a second reading using the standard clinical MRE protocol alone. Results: The number of lesions localised by cine MRE and identified on standard MRE compared with standard MRE alone were 35/24 for wall thickening (p = 0.002), 24/20 for stenoses (p = 0.05), 17/11 for wall layering (p = 0.02), 5/3 for mucosal ulcers (p = 0.02) and 21/17 for the comb sign (p = 0.05). Overall, cine MRE detected 35 more CD-specific findings than standard MRE alone (124/89; p = 0.007) and significantly more patients with CD-relevant MR findings (34/28; p = 0.03). Conclusion: CD lesions seem to be associated with motility changes and this leads to an increased lesion detection rate compared with standard-MRE imaging alon

Using Geospatial Data to Monitor and Optimize Face-to-Face Fieldwork

Interviewers occupy a key position in face-to-face interviews. Their behavior decisively contributes to the quality of surveys. However, monitoring interviewers in face-to-face surveys is much more challenging than in telephone surveys. It is often up to the interviewer when they conduct the interviews and which addresses they work on first. Nevertheless, homogeneous fieldwork, i.e. that which has a geographically similar processing status, is particularly essential for time- and eventdependent studies such as election studies. Irregular fieldwork combined with geographical differences can have substantial impacts on data quality. Using the example of the German Longitudinal Election Study (GLES), we propose and present a visual strategy by plotting key indicators of fieldwork onto a geographical map to monitor and optimize the fieldwork in face-toface interviews. The geographic visualization of fieldwork can be an additional tool not only for election studies, but also other studies

Towards Learning Self-Organized Criticality of Rydberg Atoms using Graph Neural Networks

Self-Organized Criticality (SOC) is a ubiquitous dynamical phenomenon believed to be responsible for the emergence of universal scale-invariant behavior in many, seemingly unrelated systems, such as forest fires, virus spreading or atomic excitation dynamics. SOC describes the buildup of large-scale and long-range spatio-temporal correlations as a result of only local interactions and dissipation. The simulation of SOC dynamics is typically based on Monte-Carlo (MC) methods, which are however numerically expensive and do not scale beyond certain system sizes. We investigate the use of Graph Neural Networks (GNNs) as an effective surrogate model to learn the dynamics operator for a paradigmatic SOC system, inspired by an experimentally accessible physics example: driven Rydberg atoms. To this end, we generalize existing GNN simulation approaches to predict dynamics for the internal state of the node. We show that we can accurately reproduce the MC dynamics as well as generalize along the two important axes of particle number and particle density. This paves the way to model much larger systems beyond the limits of traditional MC methods. While the exact system is inspired by the dynamics of Rydberg atoms, the approach is quite general and can readily be applied to other systems

Aperistaltic effect of hyoscine N -butylbromide versus glucagon on the small bowel assessed by magnetic resonance imaging

The aim of this prospective study was to compare the intraindividual aperistaltic effect of 40mg hyoscine N-butylbromide (HBB/Buscopan) with that of 1mg glucagon on small bowel motility by using magnetic resonance imaging (MRI). Ten healthy volunteers underwent two separate 1.5-T MRI studies (HBB/glucagon) after a standardized oral preparation with an aqueous solution of Gd-DOTA and ispaghula (Metamucil). A 2D T1-w GRE sequence was acquired (TR 2.7ms/TE 1.3ms, temporal resolution 0.25s) before and after intravenous (i.v.) drug administration and motility was followed over 1h. On the resulting images the cross-sectional luminal diameters were assessed and plotted over time. Baseline motility frequency, onset of aperistalsis, duration of arrest, reappearance of motility and return to normal motility were analysed. Significant differences regarding reliability and duration of aperistalsis were observed. In the HBB group aperistalsis lasted a mean of 6.8 ± 5.3min compared with 18.3 ± 7min after glucagon (p < 0.0001). In 50% of cases HBB did not accomplish aperistalsis, whereas glucagon always succeeded (p = 0.05). There were no significant differences in terms of baseline and end frequencies for the onset of aperistalsis (22.2 ± 37.5s HBB/13.4 ± 9.2s glucagon, p = 0.1), nor for the return to normal motility. Arrest of small bowel motion is achieved more reliably and lasts significantly longer after i.v. administration of 1mg glucagon compared with 40mg HB