Small-time asymptotics for fast mean-reverting stochastic volatility models

In this paper, we study stochastic volatility models in regimes where the maturity is small, but large compared to the mean-reversion time of the stochastic volatility factor. The problem falls in the class of averaging/homogenization problems for nonlinear HJB-type equations where the "fast variable" lives in a noncompact space. We develop a general argument based on viscosity solutions which we apply to the two regimes studied in the paper. We derive a large deviation principle, and we deduce asymptotic prices for out-of-the-money call and put options, and their corresponding implied volatilities. The results of this paper generalize the ones obtained in Feng, Forde and Fouque [SIAM J. Financial Math. 1 (2010) 126-141] by a moment generating function computation in the particular case of the Heston model.Comment: Published in at http://dx.doi.org/10.1214/11-AAP801 the Annals of Applied Probability (http://www.imstat.org/aap/) by the Institute of Mathematical Statistics (http://www.imstat.org

Energy Dependence of Direct-Quarkonium Production in pp Collisions from Fixed-Target to LHC Energies: Complete One-Loop Analysis

We compute the energy dependence of the P_T-integrated cross section of directly produced quarkonia in pp collisions at next-to-leading order (NLO), namely up to alpha_s^3, within nonrelativistic QCD (NRQCD). Our analysis is based on the idea that the P_T-integrated and the P_T-differential cross sections can be treated as two different observables. The colour-octet NRQCD parameters needed to predict the P_T-integrated yield can thus be extracted from the fits of the P_T-differential cross sections at mid and large P_T. For the first time, the total cross section is evaluated in NRQCD at full NLO accuracy using the recent NLO fits of the P_T-differential yields at RHIC, the Tevatron and the LHC. Both the normalisation and the energy dependence of the J/psi, psi' and Upsilon(1S), we obtained, are in disagreement with the data irrespective of the fit method. The same is true if one uses CEM-like colour-octet NRQCD parameters. If, on the contrary, one disregards the colour-octet contribution, the existing data in the TeV range are well described by the alpha_s^3 contribution in the colour-singlet model --which, at alpha_s^4, however shows an unphysical energy dependence. A similar observation is made for eta(c,b). This calls for a full NNLO or for a resummation of the initial-state radiation in this channel. In any case, past claims that colour-octet transitions are dominantly responsible for low-P_T quarkonium production are not supported by our results. This may impact the interpretation of quarkonium suppression in high-energy proton-nucleus and nucleus-nucleus collisions.Comment: 15 pages, 22 Figures, LaTeX uses svepjc3.clo, svglov3.clo, svjour3.cls (included

An Empirical Investigation of the Linkages Between Government Payments and Leasing Arrangements

Replaced with revised version of poster 07/22/10.Agricultural and Food Policy, Industrial Organization, Land Economics/Use,

Micromobility evolution and expansion: Understanding how docked and dockless bikesharing models complement and compete – A case study of San Francisco

Shared micromobility – the shared use of bicycles, scooters, or other low-speed modes – is an innovative transportation strategy growing across the United States that includes various service models such as docked, dockless, and e-bike service models. This research focuses on understanding how docked bikesharing and dockless e-bikesharing models complement and compete with respect to user travel behaviors. To inform our analysis, we used two datasets from February 2018 of Ford GoBike (docked) and JUMP (dockless electric) bikesharing trips in San Francisco. We employed three methodological approaches: 1) travel behavior analysis, 2) discrete choice analysis with a destination choice model, and 3) geospatial suitability analysis based on the Spatial Temporal Economic Physiological Social (STEPS) to Transportation Equity framework. We found that dockless e-bikesharing trips were longer in distance and duration than docked trips. The average JUMP trip was about a third longer in distance and about twice as long in duration than the average GoBike trip. JUMP users were far less sensitive to estimated total elevation gain than were GoBike users, making trips with total elevation gain about three times larger than those of GoBike users, on average. The JUMP system achieved greater usage rates than GoBike, with 0.8 more daily trips per bike and 2.3 more miles traveled on each bike per day, on average. The destination choice model results suggest that JUMP users traveled to lower-density destinations, and GoBike users were largely traveling to dense employment areas. Bike rack density was a significant positive factor for JUMP users. The location of GoBike docking stations may attract users and/or be well-placed to the destination preferences of users. The STEPS-based bikeability analysis revealed opportunities for the expansion of both bikesharing systems in areas of the city where high-job density and bike facility availability converge with older resident populations

HV discharge acceleration by sequences of UV laser filaments with visible and near-infrared pulses

We investigate the triggering and guiding of DC high-voltage discharges over a distance of 37 cm by filaments produced by ultraviolet (266 nm) laser pulses of 200 ps duration. The latter reduce the breakdown electric field by half and allow up to 80% discharge probability in an electric field of 920 kV/m. This high efficiency is not further increased by adding nanosecond pulses in the Joule range at 532 nm and 1064 nm. However, the latter statistically increases the guiding length, thereby accelerating the discharge by a factor of 2. This effect is due both to photodetachment and to the heating of the plasma channel, that increases the efficiency of avalanche ionization and reduces electron attachment and recombination.Comment: 12 pages, 6 figure

Survival analysis of DNA mutation motifs with penalized proportional hazards

Antibodies, an essential part of our immune system, develop through an intricate process to bind a wide array of pathogens. This process involves randomly mutating DNA sequences encoding these antibodies to find variants with improved binding, though mutations are not distributed uniformly across sequence sites. Immunologists observe this nonuniformity to be consistent with "mutation motifs", which are short DNA subsequences that affect how likely a given site is to experience a mutation. Quantifying the effect of motifs on mutation rates is challenging: a large number of possible motifs makes this statistical problem high dimensional, while the unobserved history of the mutation process leads to a nontrivial missing data problem. We introduce an $\ell_1$-penalized proportional hazards model to infer mutation motifs and their effects. In order to estimate model parameters, our method uses a Monte Carlo EM algorithm to marginalize over the unknown ordering of mutations. We show that our method performs better on simulated data compared to current methods and leads to more parsimonious models. The application of proportional hazards to mutation processes is, to our knowledge, novel and formalizes the current methods in a statistical framework that can be easily extended to analyze the effect of other biological features on mutation rates