Forecasting Value-at-Risk with Time-Varying Variance, Skewness and Kurtosis in an Exponential Weighted Moving Average Framework

This paper provides an insight to the time-varying dynamics of the shape of the distribution of financial return series by proposing an exponential weighted moving average model that jointly estimates volatility, skewness and kurtosis over time using a modified form of the Gram-Charlier density in which skewness and kurtosis appear directly in the functional form of this density. In this setting VaR can be described as a function of the time-varying higher moments by applying the Cornish-Fisher expansion series of the first four moments. An evaluation of the predictive performance of the proposed model in the estimation of 1-day and 10-day VaR forecasts is performed in comparison with the historical simulation, filtered historical simulation and GARCH model. The adequacy of the VaR forecasts is evaluated under the unconditional, independence and conditional likelihood ratio tests as well as Basel II regulatory tests. The results presented have significant implications for risk management, trading and hedging activities as well as in the pricing of equity derivatives

Spatially distributed water-balance and meteorological data from the Wolverton catchment, Sequoia National Park, California

Accurate water-balance measurements in the seasonal, snow-dominated Sierra Nevada are important for forest and downstream water management. However, few sites in the southern Sierra offer detailed records of the spatial and temporal patterns of snowpack and soil-water storage and the fluxes affecting them, i.e., precipitation as rain and snow, snowmelt, evapotranspiration, and runoff. To explore these stores and fluxes we instrumented the Wolverton basin (2180-2750 m) in Sequoia National Park with distributed, continuous sensors. This 2006-2016 record of snow depth, soil moisture and soil temperature, and meteorological data quantifies the hydrologic inputs and storage in a mostly undeveloped catchment. Clustered sensors record lateral differences with regards to aspect and canopy cover at approximately 2250 and 2625 m in elevation, where two meteorological stations are installed. Meteorological stations record air temperature, relative humidity, radiation, precipitation, wind speed and direction, and snow depth. Data are available at hourly intervals by water year (1 October-30 September) in non-proprietary formats from online data repositories (https://doi.org/10.6071/M3S94T)

Comparison of Proxy and Multimodel Ensemble Means

Proxy‐model comparisons show large discrepancies in the impact of volcanic aerosols on the hydrology of the Asian monsoon region (AMR). This was mostly imputed to uncertainties arising from the use of a single model in previous studies. Here we compare two groups of CMIP5 multimodel ensemble mean (MMEM) with the tree‐ring‐based reconstruction Monsoon Asia Drought Atlas (MADA PDSI), to examine their reliability in reproducing the hydrological effects of the volcanic eruptions in 1300–1850 CE. Time series plots indicate that the MADA PDSI and the MMEMs agree on the significant drying effect of volcanic perturbation over the monsoon‐dominated subregion, while disparities exist over the westerlies‐dominated subregion. Comparisons of the spatial patterns suggest that the MADA PDSI and the MMEMs show better agreement 1 year after the volcanic eruption than in the eruption year and in subregions where more tree‐ring chronologies are available. The MADA PDSI and the CMIP5 MMEMs agree on the drying effect of volcanic eruptions in western‐East Asia, South Asian summer monsoon, and northern East Asian summer monsoon (EASM) regions. Model results suggest significant wetting effect in southern EASM and western‐South Asia, which agrees with the observed hydrological response to the 1991 Mount Pinatubo eruption. Analysis on model output from the Last Millennium Ensemble project shows similar hydrological responses. These results suggest that the CMIP5 MMEM is able to reproduce the impact of volcanic eruptions on the hydrology of the southern AMR

The rp-process and new measurements of beta-delayed proton decay of light Ag and Cd isotopes

Recent network calculations suggest that a high temperature rp-process could explain the abundances of light Mo and Ru isotopes, which have long challenged models of p-process nuclide production. Important ingredients to network calculations involving unstable nuclei near and at the proton drip line are $\beta$-halflives and decay modes, i.e., whether or not $\beta$-delayed proton decay takes place. Of particular importance to these network calculation are the proton-rich isotopes $^{96}$Ag, $^{98}$Ag, $^{96}$Cd and $^{98}$Cd. We report on recent measurements of $\beta$-delayed proton branching ratios for $^{96}$Ag, $^{98}$Ag, and $^{98}$Cd at the on-line mass separator at GSI.Comment: 4 pages, uses espcrc1.sty. Proceedings of the 4th International Symposium Nuclei in the Cosmos, June 1996, Notre Dame/IN, USA, Ed. M. Wiescher, to be published in Nucl.Phys.A. Also available at ftp://ftp.physics.ohio-state.edu/pub/nucex/nic96-gs

High-precision measurement of the half-life of 62^{62}Ga

The beta-decay half-life of 62Ga has been studied with high precision using on-line mass separated samples. The decay of 62Ga which is dominated by a 0+ to 0+ transition to the ground state of 62Zn yields a half-life of T_{1/2} = 116.19(4) ms. This result is more precise than any previous measurement by about a factor of four or more. The present value is in agreement with older literature values, but slightly disagrees with a recent measurement. We determine an error weighted average value of all experimental half-lives of 116.18(4) ms.Comment: 9 pages, 5 figures, accepted for publication in PR

Criticality of the Mean-Field Spin-Boson Model: Boson State Truncation and Its Scaling Analysis

The spin-boson model has nontrivial quantum phase transitions at zero temperature induced by the spin-boson coupling. The bosonic numerical renormalization group (BNRG) study of the critical exponents $\beta$ and $\delta$ of this model is hampered by the effects of boson Hilbert space truncation. Here we analyze the mean-field spin boson model to figure out the scaling behavior of magnetization under the cutoff of boson states $N_{b}$. We find that the truncation is a strong relevant operator with respect to the Gaussian fixed point in $0<s<1/2$ and incurs the deviation of the exponents from the classical values. The magnetization at zero bias near the critical point is described by a generalized homogeneous function (GHF) of two variables $\tau=\alpha-\alpha_{c}$ and $x=1/N_{b}$. The universal function has a double-power form and the powers are obtained analytically as well as numerically. Similarly, $m(\alpha=\alpha_{c})$ is found to be a GHF of $\epsilon$ and $x$. In the regime $s>1/2$, the truncation produces no effect. Implications of these findings to the BNRG study are discussed.Comment: 9 pages, 7 figure

Topographic and vegetation effects on snow accumulation in the southern Sierra Nevada: a statistical summary from lidar data

Airborne light detection and ranging (lidar) measurements carried out in the southern Sierra Nevada in 2010 in the snow-free and peak-snow-accumulation periods were analyzed for topographic and vegetation effects on snow accumulation. Point-cloud data were processed from four primarily mixed-conifer forest sites covering the main snow-accumulation zone, with a total surveyed area of over 106 km2. The percentage of pixels with at least one snow-depth measurement was observed to increase from 65&ndash;90 to 99 % as the sampling resolution of the lidar point cloud was increased from 1 to 5 m. However, a coarser resolution risks undersampling the under-canopy snow relative to snow in open areas and was estimated to result in at least a 10 cm overestimate of snow depth over the main snow-accumulation region between 2000 and 3000 m, where 28 % of the area had no measurements. Analysis of the 1 m gridded data showed consistent patterns across the four sites, dominated by orographic effects on precipitation. Elevation explained 43 % of snow-depth variability, with slope, aspect and canopy penetration fraction explaining another 14 % over the elevation range of 1500&ndash;3300 m. The relative importance of the four variables varied with elevation and canopy cover, but all were statistically significant over the area studied. The difference between mean snow depth in open versus under-canopy areas increased with elevation in the rain–snow transition zone (1500&ndash;1800 m) and was about 35 &pm; 10 cm above 1800 m. Lidar has the potential to transform estimation of snow depth across mountain basins, and including local canopy effects is both feasible and important for accurate assessments

Design of an electrochemical micromachining machine

Electrochemical micromachining (μECM) is a non-conventional machining process based on the phenomenon of electrolysis. μECM became an attractive area of research due to the fact that this process does not create any defective layer after machining and that there is a growing demand for better surface integrity on different micro applications including microfluidics systems, stress-free drilled holes in automotive and aerospace manufacturing with complex shapes, etc. This work presents the design of a next generation μECM machine for the automotive, aerospace, medical and metrology sectors. It has three axes of motion (X, Y, Z) and a spindle allowing the tool-electrode to rotate during machining. The linear slides for each axis use air bearings with linear DC brushless motors and 2-nm resolution encoders for ultra precise motion. The control system is based on the Power PMAC motion controller from Delta Tau. The electrolyte tank is located at the rear of the machine and allows the electrolyte to be changed quickly. This machine features two process control algorithms: fuzzy logic control and adaptive feed rate. A self-developed pulse generator has been mounted and interfaced with the machine and a wire ECM grinding device has been added. The pulse generator has the possibility to reverse the pulse polarity for on-line tool fabrication.The research reported in this paper is supported by the European Commission within the project “Minimizing Defects in Micro-Manufacturing Applications (MIDEMMA)” (FP7-2011-NMPICT- FoF-285614)

An Improved BKW Algorithm for LWE with Applications to Cryptography and Lattices

In this paper, we study the Learning With Errors problem and its binary variant, where secrets and errors are binary or taken in a small interval. We introduce a new variant of the Blum, Kalai and Wasserman algorithm, relying on a quantization step that generalizes and fine-tunes modulus switching. In general this new technique yields a significant gain in the constant in front of the exponent in the overall complexity. We illustrate this by solving p within half a day a LWE instance with dimension n = 128, modulus $q = n^2$, Gaussian noise $\alpha = 1/(\sqrt{n/\pi} \log^2 n)$ and binary secret, using $2^{28}$ samples, while the previous best result based on BKW claims a time complexity of $2^{74}$ with $2^{60}$ samples for the same parameters. We then introduce variants of BDD, GapSVP and UniqueSVP, where the target point is required to lie in the fundamental parallelepiped, and show how the previous algorithm is able to solve these variants in subexponential time. Moreover, we also show how the previous algorithm can be used to solve the BinaryLWE problem with n samples in subexponential time $2^{(\ln 2/2+o(1))n/\log \log n}$. This analysis does not require any heuristic assumption, contrary to other algebraic approaches; instead, it uses a variant of an idea by Lyubashevsky to generate many samples from a small number of samples. This makes it possible to asymptotically and heuristically break the NTRU cryptosystem in subexponential time (without contradicting its security assumption). We are also able to solve subset sum problems in subexponential time for density $o(1)$, which is of independent interest: for such density, the previous best algorithm requires exponential time. As a direct application, we can solve in subexponential time the parameters of a cryptosystem based on this problem proposed at TCC 2010.Comment: CRYPTO 201