Option pricing under a jump-telegraph diffusion model with jumps of random size

ABSTRACT

We present a finite difference method to solve a system of two Partial-Integro Differential Equations which arise from pricing an option under a Jump-Telegraph Diffusion Model for the underlying asset, considering the risk-neutral valuation formula under an equivalent martingale measure. This system is fully discretized using an Implicit–Explicit two-time level scheme and quadrature formulas. The resulting two tridiagonal algebraic linear systems are solved recursively using the Thomas Algorithm. Some numerical results are presented and the numerical order of convergence for the method is estimated. Finally, the robustness of the method is validated against an exact solution obtained for a perturbed problem.     

A CCD-ADI method for two-dimensional linear and nonlinear hyperbolic telegraph equations with variable coefficients

In this paper, a combined compact finite difference method (CCD) together with alternating direction implicit (ADI) scheme is developed for two-dimensional linear and nonlinear hyperbolic telegraph equations with variable coefficients. The proposed CCD-ADI method is second-order accurate in time variable and sixth-order accurate in space variable. For the linear hyperbolic equation, the CCD-ADI method is shown to be unconditionally stable by using the Von Neumann stability analysis. Numerical results for both linear and nonlinear hyperbolic equations are presented to illustrate the high accuracy of the proposed method.     

Probabilistic tree-based representation for solving minimum cost integer flow problems with nonlinear non-convex cost functions

The minimum cost flow problem (MCFP) is the most generic variation of the network flow problem which aims to transfer a commodity throughout the network to satisfy demands. The problem size (in terms of the number of nodes and arcs) and the shape of the cost function are the most critical factors when considering MCFPs. Existing mathematical programming techniques often assume the cost functions to be linear or convex. Unfortunately, the linearity and convexity assumptions are too restrictive for modelling many real-world scenarios. In addition, many real-world MCFPs are large-scale, with networks having a large number of nodes and arcs. In this paper, we propose a probabilistic tree-based genetic algorithm (PTbGA) for solving large-scale minimum cost integer flow problems with nonlinear non-convex cost functions. We first compare this probabilistic tree-based representation scheme with the priority-based representation scheme, which is the most commonly-used representation for solving MCFPs. We then compare the performance of PTbGA with that of the priority-based genetic algorithm (PrGA), and two state-of-the-art mathematical solvers on a set of MCFP instances. Our experimental results demonstrate the superiority and efficiency of PTbGA in dealing with large-sized MCFPs, as compared to the PrGA method and the mathematical solvers.     

Analysis of the risk-sharing ratio in PPP projects based on government minimum revenue guarantees

Public-private partnership (PPP) projects have been widely applied in infrastructure construction. A suitable risk distribution strategy is crucial for promoting negotiations between the government and investors. The government usually provides guarantees to investors to distribute risk. However, an excessive guarantee increases the government's financial burden, whereas an insufficient guarantee reduces the confidence of the investors participating in the project. In a minimum revenue guarantee (MRG), the government subsidizes the investors the difference between the actual revenue and the government guarantee line if there is a loss. In PPP power plant and highway projects, investors' revenues come from two sources: government guarantees and the project company's self-sale. To support project companies and to optimize the projects' benefits, the government should set a reasonable benchmark for purchase amounts. Based on the traditional principal-agent model, this paper introduces the reciprocal preference theory to analyze the risk-sharing ratio most suitable for the government. Then, an optimal incentive mechanism is established to guarantee the project's income. The results indicate that by setting a different guarantee strategy for different participants, the government can utilize reciprocal preference to incentivize investors to exert more effort during a partnership and avoid moral hazard.     

Data sharing mechanism of various mineral resources based on blockchain

Basins with various mineral resources coexisting and enriching often occupy an important strategic position. The exploration of various mineral resources is repetitive at present due to unshared data and imperfect management mechanism. This situation greatly increases the cost of energy exploitation in the country. Traditional data-sharing mode has several disadvantages, such as high cost, difficulty in confirming the right of data, and lack of incentive mechanism, which make achieving real data sharing difficult. In this paper, we propose a data-sharing mechanism based on blockchain and provide implementation suggestions and technical key points. Compared with traditional data-sharing methods, the proposed data-sharing mechanism can realize data sharing, ensure data quality, and protect intellectual property. Moreover, key points in the construction are stated in the case study section to verify the feasibility of the data-sharing system based on blockchain proposed in this paper.     

Retracted: State estimation of Takagi-Sugeno fuzzy system in networked control system with stochastic time delays under unknown attacks

This article concerns the event-triggered fuzzy filter design for Takagi-Sugeno (T-S) fuzzy systems subject to deception attacks under the stochastic multiple time-varying delays. A sequence of random variables, which are mutually independent but obey the Bernoulli distribution, is introduced to account for the randomly occurring communication delays. In order to efficiently utilize limited network communication bandwidth resources, the event-triggering scheme is adopted. A fuzzy filter with the attacked input signal is presented. Moreover, due to communication delays caused by event-triggering schemes and transmission, the filter adopts non-synchronous premise variables with the system. Then, by utilizing a model transformation technique, the fuzzy systems are developed. Furthermore, using the piecewise Lyapunov functional method technique, the resulting criterion provides sufficient conditions to ensure that fuzzy systems under deception attacks are stochastically stable with an H_∞ performance. Accordingly, the conditions for the co-design of the fuzzy filter and event-triggering schemes are given. Finally, numerical simulation with the industrial process provided to verify the proposed event-triggered design.     

引水隧洞瓦斯封堵施工技术探讨

山西中部引黄工程24标西干29+089.4~29+278隧洞段地处煤层带,富含瓦斯、一氧化碳等有害气体,且围岩节理发育、变形严重。针对初期支护完成地段、掌子面及裸露洞段和IV类围岩地段提出瓦斯封堵专项施工方案。通过密切监测做好通风,并采用高分子材料马丽散对其注浆,可有效解决隧洞瓦斯封堵难题,为类似项目提供参考。     

生物氧化预处理中进气量实时预测数学模型研究

精准预测生物氧化预处理中的进气量对提高黄金提取率和节能降耗具有重要意义。以气体管流连续性方程和运动方程为控制方程，采用Preissmann隐格式法作为差分方法。同时，根据集合卡尔曼滤波(Ensemble Kalman filter，EnKF)算法原理，构造进气量、压强的状态空间模型。结果表明，基于气体管流控制方程建立的进气量模型预测结果与实际进气量观测值具有较好的一致性；与传统静态预测方法相比，EnKF同化方法引入实时观测值和模型参数的更新，有效提高了进气量的预测精度，其平均绝对误差、平均相对误差和均方根误差有明显的降低。可见，基于气体管流控制方程建立的预测模型结合EnKF同化方法是提高生物氧化槽进气量预测精度的有效手段。     

矿井地面风硐的改造方案比选与施工

为解决通风系统改造后原地面风硐断面偏小、风速超限的问题,通过在原有地面风硐东侧并联一道钢制矩形通风管道的方法,从而增加风硐断面积,降低风硐内的风速和通风阻力,效果明显。     

单相并联型有源电力滤波器主电路参数耦合关系研究

单相并联型有源电力滤波器(SAPF)主电路参数之间存在一定的耦合关系,这对各参数值的合理选择有较大的影响。通过分析现有单/三相SAPF主电路交流侧电感以及直流侧电压、电容值等参数的计算方法,得到了具体的单相SAPF电路参数解析表达式。针对所得表达式各变量之间的耦合关系,在MATLAB中进行建模优化分析,得出一套完整的参数设计方案。保证在特定负载下补偿后谐波含量低于2%的综合优化目标。仿真和实验过程验证了所选参数的正确性。