配送中心订单处理作业流程仿真研究

对订单处理系统相关文献归纳总结的基础上,进一步分析订单处理的作业流程。分析认为,可以用排队系统建模仿真的方法解决订单处理的相关问题。以某网上商城订单处理流程为例,采用实体流程图法建立该流程的系统模型,并利用WITNESS仿真软件建立了仿真模型。仿真实验的结果指明最优人员配置和系统的进一步优化方向。     

基于EDA技术的EWB电路仿真——入门者提高分析与设计能力的基础

通过EWB电路仿真,将理论电原理图用直观的测量仪器仪表演示。体现出在合理可行的电路结构下的参数,也可进行相应的指标调试,得到最佳的工作状态。辅助抽象理论学习,系统掌握体系中的知识点,过程实现简洁,效果明显,引发自我学习兴趣。本文展开的分析仿真为初学者自学和后期深入EDA技术领域打下基础,拓宽思路,为分析与设计能力的提高做好铺垫。     

一种小功率LED驱动电源的设计与实现

为了保证小功率LED发光的高效性和均匀性,需提高驱动电源的性能。本文采用电容降压、桥式整流的方法针对LED交叉阵列连接方式设计了一种驱动电路,经仿真实验验证本驱动电路可靠性较高,实用性较强。     

天津西站特殊高大空间室内热环境模拟分析

天津西站高架候车室采用大面积玻璃穹顶,太阳辐射通过玻璃直射到人体上,会大幅增加人体的热感觉,这给室内热环境控制提出了新的要求。从空调系统的设置、气流组织模拟及人体热舒适性分析等三个方面模拟分析候车室内热环境,以期得到满足人体热舒适性要求的玻璃遮阳系数、温湿度、风速参数及地板辐射供冷参数等内容,为同类项目设计提供参考。     

水轮机轴摆度实时控制探析

基于水轮发电机组的振动类型、危害、产生原因及应对策略,建立水轮机组轴摆度实时控制仿真系统进行验证,分析系统运行情况的优劣,并论证系统在现实中的可行性。     

A Technique for Reducing Discretization Bias from Monte Carlo Simulations: Option Pricing under Stochastic Interest Rates

Abstract

Control variates are often used to reduce variability in Monte Carlo estimates and their effectiveness is traditionally measured by the so-called speed-up factor. The main objective of this paper is to demonstrate that a control variate can also be applied to reduce the bias stemming from the discretization of the state variable dynamics. This is particularly valuable when stochastic interest rate models are discretized, since bias reduction through more grid points is computationally expensive.     

Risk management in the energy markets and Value-at-Risk modelling: a hybrid approach

This paper proposes a set of Value-at-Risk (VaR) models appropriate to capture the dynamics of energy prices and subsequently quantify energy price risk by calculating VaR and expected shortfall measures. Amongst the competing VaR methodologies evaluated in this paper, besides the commonly used benchmark models, a Monte Carlo (MC) simulation approach and a hybrid MC with historical simulation approach, both assuming various processes for the underlying spot prices, are also being employed. All VaR models are empirically tested on eight spot energy commodities that trade futures contracts on the New York Mercantile Exchange (NYMEX) and the constructed Spot Energy Index. A two-stage evaluation and selection process is applied, combining statistical and economic measures, to choose amongst the competing VaR models. Finally, both long and short trading positions are considered as it is of utmost importance for energy traders and risk managers to be able to capture efficiently the characteristics of both tails of the distributions.     

A new closed-form solution as an extension of the Black–Scholes formula allowing smile curve plotting

In this paper, as a generalization of the Black–Scholes (BS) model, we elaborate a new closed-form solution for a uni-dimensional European option pricing model called the J-model. This closed-form solution is based on a new stochastic process, called the J-process, which is an extension of the Wiener process satisfying the martingale property. The J-process is based on a new statistical law called the J-law, which is an extension of the normal law. The J-law relies on four parameters in its general form. It has interesting asymmetry and tail properties, allowing it to fit the reality of financial markets with good accuracy, which is not the case for the normal law. Despite the use of one state variable, we find results similar to those of Heston dealing with the bi-dimensional stochastic volatility problem for pricing European calls. Inverting the BS formula, we plot the smile curve related to this closed-form solution. The J-model can also serve to determine the implied volatility by inverting the J-formula and can be used to price other kinds of options such as American options.     

Approximation of aggregate and extremal losses within the very heavy tails framework

The loss distribution approach is one of the three advanced measurement approaches to the Pillar I modeling proposed by Basel II in 2001. In this paper, one possible approximation of the aggregate and maximum loss distribution in the extremely low frequency/high severity case is given, i.e. the case of infinite mean of the loss sizes and loss inter-arrival times. In this study, independent but not identically distributed losses are considered. The minimum loss amount is considered increasing over time. A Monte Carlo simulation algorithm is presented and several quantiles are estimated. The same approximation is used for modeling the maximum and aggregate worldwide economy losses caused by very rare and very extreme events such as 9/11, the Russian rouble crisis, and the U.S. subprime mortgage crisis. The model parameters are fit on a data sample of operational losses. The respective aggregate and extremal loss quantiles are calculated.     

The impact of the choice of VaR models on the level of regulatory capital according to Basel II

The Basel II framework allows the calculation of the capital requirements for market risk with Value-at-Risk models. Since no special model is prescribed in the framework, banks may use simple models with questionable assumptions concerning their underlying distributions. Our numerical analysis reveals that simple VaR models that perform noticeably worse than comparable simple models with more realistic assumptions may lead to a lower level of regulatory capital for banks. For this reason, banks have a major incentive to implement bad models. This is obviously contrary to the interests of regulatory authorities.