Option Pricing and Hedging under a Markov Switching Lévy Process Model

In this paper,we consider a Markov switching Lévy process model in which the underlying risky assets are driven by the stochastic exponential of Markov switching Lévy process and then apply the model to option pricing and hedging.In this model,the market interest rate,the volatility of the underlying risky assets and the N-state compensator,depend on unobservable states of the economy which are modeled by a continuous-time Hidden Markov process.We use the MEMM(minimal entropy martingale measure) as the equivalent martingale measure.The option price using this model is obtained by the Fourier transform method.We obtain a closed-form solution for the hedge ratio by applying the local risk minimizing hedging.     

“禁摩限电”效果综合评价模型

将交通需求级别进行划分后,通过数据包络分析法计算交通需求匹配度和交通运行效率,近乎绝对细化交通运行表现,依据具有时间轴的四维交通状况模拟建立了全新多维度的交通评价体系。此外,利用模糊层次分析法确定道路交通安全评价指标体系中各个指标的权重,同时作出基于差异驱动原理的综合评价。最后,将交通的污染指标提炼为机动车的排放指标和电动车的耗电指标来衡量交通工具对环境的影响。     

On a single discrete scale for preventive maintenance with two shock processes affecting a complex system

A new approach to optimal maintenance of systems (networks) is suggested. It is applied to systems subject to two external independent shock processes. A system ‘consists’ of two parts, and each shock process affects only its own part. A new notion of bivariate signature is suggested and used for obtaining survival characteristics of a system and further optimization of the preventive maintenance actions. The preventive maintenance optimization is considered in the univariate discrete scale that counts the overall numbers of shocks of both types. An example of a transportation network is considered. Copyright © 2016 John Wiley & Sons, Ltd.     

Semiparametric Bayesian inference for mean-covariance regression models

In this paper, we propose a Bayesian semiparametric mean-covariance regression model with known covariance structures. A mixture model is used to describe the potential non-normal distribution of the regression errors. Moreover, an empirical likelihood adjusted mixture of Dirichlet process model is constructed to produce distributions with given mean and variance constraints. We illustrate through simulation studies that the proposed method provides better estimations in some non-normal cases. We also demonstrate the implementation of our method by analyzing the data set from a sleep deprivation study.     

Besov空间中双参数Volterra型重分数过程的弱逼近

In this paper, we prove that two-parameter Volterra multifractional process can be approximated in law in the topology of the anisotropic Besov spaces by the family of processes{B_n(s,t)},n∈N defined by B_n(s,t)=∫_0~s ∫_0~tk_(a(s))(s,u)K_(β(t))(t,u)θ_(n(u,v))dudv,here {θ_n(u, v)}n∈N is a family of processes, converging in law to a Brownian sheet as n→∞,based on the well known Donsker's theorem.     

基于Aspen Plus耦合生命周期评价的科研案例在环境工程原理教学中的应用

将化工流程模拟Aspen Plus软件与环境影响评估领域常用的生命周期评价(LCA)进行集成应用,围绕环境工程原理教学中有关化工过程质量能量衡算与环境污染防治内容的协同应用与拓展,构建化工流程模拟-环境风险评估科研案例“苯酐生产流程模拟及环境风险研究”,并将其作为环境工程原理的综合教学案例。教学实践经验表明,通过引入工程相关综合教学案例,不仅使得抽象的理论知识更加生动具体,而且在深化学生对课程理论知识理解的同时,提高学生应用专业知识分析和解决化工生产环境污染工程问题的综合能力和素质,为学生将来步入相关领域工作奠定扎实的基础。     

Study on gas adsorption and desorption characteristics on water injection coal

To study the desorption mechanism of methane in coal by H₂O injection and establish the Wiser molecular structure model of bituminous coal, the Grand Canonical Monte Carlo method was used to study the desorption behavior of CH₄ in coal with different amounts of H₂O injection at molecular scale. The results showed that at 293 K, the maximum adsorption capacity of H₂O was about 16 mmol/g, and that of CH₄ was about 8 mmol/g, which was about twice that of CH₄. This indicates that H₂O has a stronger adsorption capacity than CH₄. For methane-bearing coal, when the amount of water injected is 100, the average relative concentration of CH₄ is 0.5446, and the average relative concentration of CH₄ decreases by 33.77% compared to the water content of 20. Under the same time conditions, the root mean square displacement and diffusion coefficient of CH₄ decrease with the increase of H₂O injection quantity. With the increase of H₂O injection, the motion velocity of CH₄ in vacuum layer decreased. When water was injected, methane was trapped in the coal by water. The more H₂O injected, the more methane trapped in the coal, and the less methane desorption. This research lays a theoretical foundation for further research involving coal-water interaction.     

Benefiting from information-rich multi-frequency AC voltammetry coupled with chemometrics on the example of on-line monitoring of leveler component of electroplating bath

Simultaneous application of multiple sinusoidal waveforms perturbations superimposed onto DC staircase step significantly enriches current response. The measured current is characterized by a matrix of data rather than a conventional voltammetric output in a form of a vector. This increase of the dimensionality of the current response and therefore the wealth of analytical information is achieved without compromising the time of analysis. The natural approach for compression of such data and extraction of relevant information is by utilizing multi-way chemometric decomposition techniques. An electroplating solution presents a very challenging analyte for electroanalysis as its constituents interact synergistically with each other during both the plating process and its simulation during electroanalysis. For some components the mechanism is not entirely understood. Therefore, the only way to benefit from the analytical data is by employing soft modeling. The electrode processes involving additives rely heavily on adsorption and, indirectly, on electron transfer kinetics for which AC voltammetry is an analytical technique capable of delivering informative signals. This paper presents a rigorous universal method for calculating and validating an exemplary multi-way calibration of a leveler component in a copper electroplating bath used in the semiconductor industry. The method presented employs comparatively Parallel Factor Analysis coupled with Inverse Least Squares Regression and multi-linear Partial Least Squares. The calibration training set consists of multi-frequency AC voltammetric data subjected to pretreatments aiming to select informative independent variables and exclude outliers.     

Mechanism of Cations Suppressing Proton Diffusion Kinetics for Electrocatalysis

Proton transfer is crucial for electrocatalysis. Accumulating cations at electrochemical interfaces can alter the proton transfer rate and then tune electrocatalytic performance. However, the mechanism for regulating proton transfer remains ambiguous. Here, we quantify the cation effect on proton diffusion in solution by hydrogen evolution on microelectrodes, revealing the rate can be suppressed by more than 10 times. Different from the prevalent opinions that proton transport is slowed down by modified electric field, we found water structure imposes a more evident effect on kinetics. FTIR test and path integral molecular dynamics simulation indicate that proton prefers to wander within the hydration shell of cations rather than to hop rapidly along water wires. Low connectivity of water networks disrupted by cations corrupts the fast-moving path in bulk water. This study highlights the promising way for regulating proton kinetics via a modified water structure.     

Hydrogen Peroxide Production of Individual Nanosecond Pulsed Discharges Submerged in Water of Elevated Conductivity

The production of hydrogen peroxide (H₂O₂) is a key parameter for the performance of pulsed discharges submerged in water utilized as advanced oxidation process. So far, any related assessment of the underlying mechanism was conducted for the application of several hundred discharges, which did not allow for a correlation with physical processes. Moreover, the production was rarely investigated depending on water conductivity as one of the most important parameters for the development of submerged discharges. Accordingly, hydrogen peroxide generation was investigated here for individual single discharge events instigated with 100 ns high-voltage pulses in water with three different conductivities and was associated with the discharge development, i. e. spatial expansion and dissipated electrical energy. The approach necessitated the improvement of an electrochemical flow injection analysis based on the reaction of Prussian blue with H₂O₂. Hydrogen peroxide concentrations were quadratically increasing with propagation time and stable for different water conductivities. H₂O₂ production per unit volume of a discharge was constant over time with an estimated rate constant of 3.2 mol ⋅ m⁻¹ s⁻¹, averaged over the crosssectional area of all discharge filaments. However, the individually dissipated energy increased with conductivity, hence, the production efficiency decreased from 6.1 g ⋅ kWh⁻¹ to 1.4 g ⋅ kWh⁻¹, which was explained by increased resistive losses within the bulk liquid.