Testing for expected return and market price of risk in Chinese A and B share markets: A geometric Brownian motion and multivariate GARCH model approach

There exist dual listed stocks which are issued by the same company in some stock markets. Although these stocks bare the same firm-specific risks and enjoy identical dividends and voting policies, they are priced differently. Some previous studies show this seeming deviation from the law of one price can be solved by allowing different expected returns and market prices of risk for investors holding heterogeneous beliefs. This paper provides empirical evidence for that argument by testing the expected return and market price of risk between Chinese A and B shares listed in Shanghai and Shenzhen stock markets. Models with dynamic of Geometric Brownian Motion are adopted. Multivariate GARCH models are also introduced to capture the feature of time-varying volatility in stock returns. The results suggest that the different pricing can be explained by the difference in expected returns between A and B shares. However, the difference between market price of risk is insignificant for both markets if GARCH models are adopted.     

A genetic algorithm and the Monte Carlo method for stochastic job-shop scheduling

This paper proposes a method for solving stochastic job‐shop scheduling problems using a hybrid of a genetic algorithm in uncertain environments and the Monte Carlo method. First, the genetic algorithm in uncertain environments is applied to stochastic job‐shop scheduling problems where the processing times are treated as stochastic variables. The Roulette strategy is adopted for selecting the optimum solution having the minimum expected value for makespan. Applying crossover based on Giffler and Thompson's algorithm results in two offspring inheriting the ancestor's characteristics as the operation completion times averaged up to the parent's generation. Individuals having very high frequency through all generations are selected as the good solutions. Second, the Monte Carlo method is effectively used for finding out the approximately optimum solution among these good solutions.     

A hardware generator of multi-point distributed random numbers for Monte Carlo simulation

Monte Carlo simulation of weak approximations of stochastic differential equations constitutes an intensive computational task. In applications such as finance, for instance, to achieve “real time” execution, as often required, one needs highly efficient implementations of the multi-point distributed random number generator underlying the simulations. In this paper, a fast and flexible dedicated hardware solution on a field programmable gate array is presented. A comparative performance analysis between a software-only and the proposed hardware solution demonstrates that the hardware solution is bottleneck-free, retains the flexibility of the software solution and significantly increases the computational efficiency. Moreover, simulations in applications such as economics, insurance, physics, population dynamics, epidemiology, structural mechanics, chemistry and biotechnology can benefit from the obtained speedups.     

Nonlinear stochastic receding horizon control: stability,robustness and Monte Carlo methods for control approximation

This work considers the stability of nonlinear stochastic receding horizon control when the optimal controller is only computed approximately. A number of general classes of controller approximation error are analysed including deterministic and probabilistic errors and even controller sample and hold errors. In each case, it is shown that the controller approximation errors do not accumulate (even over an infinite time frame) and the process converges exponentially fast to a small neighbourhood of the origin. In addition to this analysis, an approximation method for receding horizon optimal control is proposed based on Monte Carlo simulation. This method is derived via the Feynman–Kac formula which gives a stochastic interpretation for the solution of a Hamilton–Jacobi–Bellman equation associated with the true optimal controller. It is shown, and it is a prime motivation for this study, that this particular controller approximation method practically stabilises the underlying nonlinear process.     

The effects of misspecified marginals and copulas on computing the value at risk: A Monte Carlo study

The effect on the estimation of the Value at Risk when dealing with multivariate portfolios when there is a misspecification both in the marginals and in the copulas is investigated. It is first shown that, when there is skewness in the data and symmetric marginals are used, the estimated elliptical (normal or t) copula correlations are negatively biased, reaching values as high as 70% of the true values. Besides, the bias almost doubles if negative correlations are considered, compared to positive correlations. As for the t copula degrees of freedom parameter, the use of wrong marginals delivers large positive biases, instead. If the dependence structure is represented by a copula which is not elliptical, e.g. the Clayton copula, the effects of marginal misspecifications on the copula parameter estimation can be rather different, depending on the sign of marginal skewness. Extensive Monte Carlo studies then show that the misspecifications in the marginal volatility equation more than offset the biases in copula parameters when VaR forecasting is of concern, small samples are considered and the data are leptokurtic. The biases in the volatility parameters are much smaller, whereas those ones in the copula parameters remain almost unchanged or even increase when the sample dimension increases. In this case, copula misspecifications do play a role for VaR estimation. However, these effects depend heavily on the sign of the dependence.     

JetWeb: A WWW interface and database for Monte Carlo tuning and validation

A World Wide Web interface to a Monte Carlo tuning facility is described. The aim of the package is to allow rapid and reproducible comparisons to be made between detailed measurements at high-energy physics colliders and general physics simulation packages. The package includes a relational database, a Java servlet query and display facility, and clean interfaces to simulation packages and their parameters.     

COOL: A code for dynamic Monte Carlo simulation of molecular dynamics

COOL is a program to simulate evaporative and sympathetic cooling for a mixture of two gases co-trapped in a harmonic potential. The collisions involved are assumed to be exclusively elastic, and losses are due to evaporation from the trap. Each particle is followed individually in its trajectory, consequently properties such as spatial densities or energy distributions can be readily evaluated. The code can be used sequentially, by employing one output as input for another run. The code can be easily generalised to describe more complicated processes, such as the inclusion of inelastic collisions, or the possible presence of more than two species in the trap.

Program summary

Program title: COOLCatalogue identifier: AEHJ_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEHJ_v1_0.htmlProgram obtainable from: CPC Program Library, Queen's University, Belfast, N. IrelandLicensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.htmlNo. of lines in distributed program, including test data, etc.: 1 111 674No. of bytes in distributed program, including test data, etc.: 18 618 045Distribution format: tar.gzProgramming language: C++Computer: DesktopOperating system: LinuxRAM: 500 MbytesClassification: 16.7, 23Nature of problem: Simulation of the sympathetic process occurring for two molecular gases co-trapped in a deep optical trap.Solution method: The Direct Simulation Monte Carlo method exploits the decoupling, over a short time period, of the inter-particle interaction from the trapping potential. The particle dynamics is thus exclusively driven by the external optical field. The rare interparticle collisions are considered with an acceptance/rejection mechanism, that is by comparing a random number to the collisional probability defined in terms of the inter-particle cross section and centre-of-mass energy. All particles in the trap are individually simulated so that at each time step a number of useful quantities, such as the spatial densities or the energy distributions, can be readily evaluated.Restrictions: The in-trap motion of the particles is treated classically.Running time: The running time is relatively short, 1–2 hours. However it is convenient to replicate each simulation several times with different initialisations of the random sequence.     

Electron-phonon interaction in nanowires: A Monte Carlo study of the effect of the field

The femtosecond dynamics of highly non-equilibrium, confined carriers is analyzed within a Monte Carlo approach. The physical process considered corresponds to a locally excited or injected into a semiconductor nanowire distribution of heated carriers, which evolve under the action of an applied electric field. The carriers are cooled down by dissipation processes caused by phonons. The process is described by a quantum-kinetic equation which generalizes the classical Boltzmann equation with respect to two classical assumptions, namely for temporal and spatial locality of the carrier-phonon interaction. We investigate the effect of the field on the electron-phonon interaction—the intra-collisional field effect (ICFE). A Monte Carlo method for simulation of the considered process has been utilized. Simulation results for carrier evolution in a GaAs nanowire are obtained and analyzed for phenomena related to the ICFE.     

The polarized emissivity of a wind-roughened sea surface: A Monte Carlo model

We use a Monte Carlo ray-tracing model to compute the thermal-infrared emissivity of a wind-roughened sea surface. The model includes the effects of both shadowing and the reflected component of surface emission. By using Stokes vectors to quantify the radiation along a given ray path, we compute the effects of polarization as well. We separate the direct emission from surface reflections to show how each affects the nature of the emitted field. The reflected component is an important part of the radiative transfer and affects nearly 10% of the ray paths at emission angles between 60° and 80° at wind speeds ?5 m/s, increasing the effective emissivity by as much as 0.03. The modeled emissivities agree nicely with recent sea surface emissivity measurements. We also compare the Monte Carlo results to a recently published analytic model and show that the two vary somewhat due to differences in the amount of the reflected component included in the calculations. Surface roughness has a large effect on the polarization between 60° and 90° but less so at smaller angles. Including the reflected component has a small but noticeable effect which actually enhances the degree of polarization at intermediate angles.     

大分子蠕动的Monte Carlo模型及计算方法

高分子链分子量巨大而且分散,结构复杂多变,存在大量不确定的问题,给理论和实验研究造成许多困难。本文建立了一种基于高分子Monte Carlo模拟算法,分析分子蠕动阻力的模型。用链动力学法构造8配位点键长涨落格子链多链体系,通过高分子链的运动使任意的初始有序态演化到平衡态,可同时获得体系的动态和静态性质。将重要性抽样法和高分子多链体系的链动力学构造法,在键长涨落模型中结合起来,形成多链体系的链动力学求解法。引入空格扩散算法,用以研究高浓度态的高分子体系。统计平衡后元胞内高分子多链体系在链动力学算法作用下蠕动失败机率,对高聚物多链体系内分子蠕动的困难程度的定量模拟,能更直观分析高分子玻璃化转变的现象。     

Finite-Sample Adjustments for Homogeneity and Symmetry Tests in Systems of Demand Equations: A Monte Carlo Evaluation

This paper gives simulation results comparing the finite-sample performance of three commonly used homogeneity and symmetry asymptotic tests, and some size-corrected tests that can be used when the sample size is small. The results suggest that such finite-sample corrections can be effective in bringing the empirical sizes of the tests closer to their nominal levels. They also suggest that the likelihood ratio test is, in general, more reliable than the Wald and Lagrange multiplier tests. Finally, it is shown that size-corrections of homogeneity tests tend to introduce reductions in power, which can be very large when bootstrap corrections are used. An application to a well known data set is also presented.     

Portmanteau Model Diagnostics and Tests for Nonlinearity: A Comparative Monte Carlo Study of Two Alternative Methods

This paper employs an extensive Monte Carlo study to test the size and power of the BDS and close return methods of testing for departures from independent and identical distribution. It is found that the finite sample properties of the BDS test are far superior and that the close return method cannot be recommended as a model diagnostic. Neither test can be reliably used for very small samples, while the close return test has low power even at large sample sizes.     

数字喷墨制网机数据卡的设计与实现

基于喷墨制网机下位机与上位机进行高速可靠地传输大容量数据的性能要求,以USB设备芯片PDIUSBD12与S3C44B0X为核心,设计并实现喷墨制网机的数据卡,给出了建立在μC/OS-Ⅱ操作系统上的USB驱动程序。     

A Monte Carlo C-code for calculating transmission efficiency of recoil separators and viewing residue trajectories

We present a semimicroscopic Monte Carlo code for calculating absolute transmission efficiency of recoil separators for heavy ion-induced complete fusion reactions. The code generates realistic distributions for energy, charge state and angle of evaporation residues. Residue trajectories are calculated using first order ion optical transfer matrices. Trajectory plots in the dispersive and the non-dispersive planes are generated. Using this code, we have obtained good agreement between calculated and measured transmission efficiencies for the Heavy Ion Reaction Analyzer at IUAC. The code can be adapted easily to any other electromagnetic recoil separator.

Program summary

Program title: TERSCatalogue identifier: AEBD_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEBD_v1_0.htmlProgram obtainable from: CPC Program Library, Queen's University, Belfast, N. IrelandLicensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.htmlNo. of lines in distributed program, including test data, etc.: 6818No. of bytes in distributed program, including test data, etc.: 1 216 097Distribution format: tar.gzProgramming language: CComputer: The code has been developed and tested on a PC with Intel Pentium IV processorOperating system: LinuxRAM: About 8 MbytesClassification: 17.7External routines: pgplot graphics subroutine library [1] should be installed in the system for generating residue trajectory plots.Nature of problem: Recoil separators are employed to select and identify nuclei of interest, produced in a nuclear reaction, rejecting unreacted beam and other undesired reaction products. It is important to know what fraction of the selected nuclei, leaving the target, reaches the detection system. This information is crucial for determining absolute cross section of the studied reaction.Solution method:Interaction of projectiles with target nuclei is treated event by event, semimicroscopically. Position and angle (with respect to beam direction), energy and charge state of the reaction products are calculated by Monte Carlo method. Trajectory of each nuclei inside the separator is then calculated by ion optical transfer matrix method. Ratio of the number of trajectories completing their journey up to the detection system to the total number of trajectories is a direct measure of absolute transmission efficiency of the separator.Restrictions: The present version of the code is applicable to complete fusion reactions only. The code can be applied to other types of reactions (e.g., few nucleon transfer) as well, by suitably modifying energy and angular distribution of reaction products. Also, ion optical specifications and acceptance are unique for each recoil separator. Transmission efficiency calculation has been done for a specific recoil separator, viz. the Heavy Ion Reaction Analyzer [2,3] at IUAC. One has to make necessary changes in the code, while performing calculations for other recoil separators. Further, atomic number of the residual nucleus should not exceed 92, as the method used for calculating stopping power of ions [4] is valid for Z?92.Running time: From few seconds to several minutes depending on the reaction, number of events and separator layout.References:

[1]

http://www.astro.caltech.edu/~tjp/pgplot/.

[2]

A.K. Sinha, N. Madhavan, J.J. Das, P. Sugathan, D.O. Kataria, A.P. Patro, G.K. Mehta, Nucl. Instr. Methods A 339 (1994) 543.

[3]

S. Nath, Nucl. Instr. Methods A 576 (2007) 403.

[4]

J.F. Ziegler, J.P. Biersack, U. Littmark, The Stopping and Range of Ions in Solids, vol. I, Pergamon Press, Oxford, 1984.

     

11-脱氧甘草次酸的合成及结构的理论研究

甘草次酸是甘草中的活性成分之一,具有广泛的药理活性,尤其是其衍生物具有显著的抗炎、抗过敏、止痛、抗癌、抗乙肝病毒、抗艾滋病毒等活性。但临床上长期应用该类药物常伴有假醛固酮增多症的副作用,限制了其在临床上的广泛应用。药理研究表明:甘草次酸的11-位羰基还原后将会降低其副作用,为了给11-脱氧甘草次酸的结构衍生化及构效关系研究提供了依据,本研究以18β-甘草次酸为原料,采用经典的克莱门森还原制备了11-脱氧甘草次酸,通过IR、~1H NMR、~(13)C NMR、HRMS等方法对其进行了表征。接着应用量子化学中的密度泛涵理论(DFT),在B3LYP/6-31G(d)水平下优化了其空间构型,计算了其结构参数、单点能、前线轨道能量和Mulliken电荷布局分布。     

SISAM and MIXIN: Two algorithms for the computation of posterior moments and densities using Monte Carlo integration

Two algorithms, and corresponding Fortran computer programs, for the computation of posterior moments and densities using the principle of importance sampling are described in detail. The first algorithm makes use of a multivariate Student t importance function as approximation of the posterior. It can be applied when the integrand is moderately skew. The second algorithm makes use of a decomposition: a multivariate normal importance function is used to generate directions (lines) and one-dimensional classical quadrature is used to evaluate the integrals defined on the generated lines. The second algorithm can be used in cases where the integrand is possibly very skew in any direction.     

A general approach for the machining quality evaluation of S-shaped specimen based on POS-SQP algorithm and Monte Carlo method

In S-shaped specimens which are frequently used to reflect the machining ability of machine tools, the surface error refers to the distance between the points on the actual machining surface to their relevant points on the design surface. The proper measurement of this error is crucial for evaluating the machining quality of S-shaped specimens. During the process of error measurement, improper registration between the measurement coordinate system and the design coordinate system, as well as neglected uncertainty remain the main obstacles for the quality evaluation of S-shaped specimens. This study proposes a general method for the high-precision machining quality evaluation of S-shaped specimens that overcomes both problems. By applying the non-uniform rational B-spline (NURBS) surface molding technology, the surface of S-shaped specimen was reconstructed. Based on the minimum area principle and the particle swarm optimization-sequential quadratic programming (POS-SQP) algorithm, a surface error model of S-shaped specimen was developed. This model minimizes the maximum distance of the transacted measurement points to the design surface. It can be used to obtain the optimal registration matrix of the measurement coordinate system, with minimal surface error of S-shaped specimen. Additional common algorithms were also adopted to search the optimal registration matrix for comparison. Accounting for the random characteristics of basic parameters and the nonlinearity of surface error model, an uncertainty model of the surface error of S-shaped specimen was established based on the Monte Carlo method. This could obtain the actual tolerance zone of the surface error, according to which, the allowable tolerance zone of the surface error was optimized and a defined evaluation result of machining quality of S-shaped specimen was obtained. Then, a general approach for the evaluation of the machining quality of S-shaped specimen was developed based on POS-SQP algorithm and Monte Carlo method. This approach was implemented in a case study though a series of experiments. The experimental results identified the proposed approach as effective in improving the measurement quality and the evaluation of the machining quality of S-shaped specimens can thus be performed within an allowable tolerance zone.