A neural network versus Black–Scholes: a comparison of pricing and hedging performances

An Erratum has been published for this article in Journal of Forecasting 22(6‐7) 2003, 551 The Black–Scholes formula is a well‐known model for pricing and hedging derivative securities. It relies, however, on several highly questionable assumptions. This paper examines whether a neural network (MLP) can be used to find a call option pricing formula better corresponding to market prices and the properties of the underlying asset than the Black–Scholes formula. The neural network method is applied to the out‐of‐sample pricing and delta‐hedging of daily Swedish stock index call options from 1997 to 1999. The relevance of a hedge‐analysis is stressed further in this paper. As benchmarks, the Black–Scholes model with historical and implied volatility estimates are used. Comparisons reveal that the neural network models outperform the benchmarks both in pricing and hedging performances. A moving block bootstrap is used to test the statistical significance of the results. Although the neural networks are superior, the results are sometimes insignificant at the 5% level. Copyright © 2003 John Wiley & Sons, Ltd.     

对西方数学直观的评析

本文从数学方法论的角度,具体论述和评析了西方数学直观随数学发展的不同阶段所表现出的特点和演变方式。     

具有(F(V×V),R,→,■)模糊逻辑模型的稳定性结构

本文利用多边矩阵理论定义的正交性及对称性,给出了一种具有两种因果关系的模糊稳定性逻辑分析模型,这种稳定的逻辑分析模型结构清晰、简单,并且可用于解决许多复杂问题.     

Pragmatism in Economic Methodology: The Duhem-Quine Thesis Revisited

Contemporary developments in economicmethodology have produced a vibrant agenda ofcompeting positions. These include, amongothers, constructivism, critical realism andrhetoric, with each contributing to the Realistvs. Pragmatism debate in the philosophies of thesocial sciences. A major development in theneo-pragmatist contribution to economicmethodology has been Quine's pragmatic assaulton the dogmas of empiricism, which are nowclearly acknowledged within contemporaryeconomic methodology. This assault isencapsulated in the celebrated Duhem-Quinethesis, which according to a number ofcontemporary leading philosophers of economics,poses a particularly serious methodologicalproblem for economics. This problem, asreflected in Hausman's analysis, consists ofthe inability of economics to learn fromexperience, thereby subverting the capacity totest economic theories. In this paper wedispute this position. Our argument is basedon a combination of Quine's holism with VanFraassen's constructive empiricism, especiallythe latter's analysis of empirical adequacy andhis pragmatic approach to explanation. Theresulting reorientation of economic methodologyrestores the capacity of economics to learnfrom experience and reinstates the imperativeof developing alternatives to orthodoxtheorizing in economics.     

导弹发射决策专家系统推理机研究与实现

介绍了一种基于灵活、通用的知识表达方法的推理机。它将面向对象方法和问题求解的黑板模型有机结合 ,自带各种控制信息和适宜的不确定性推理算法 ,将知识库分层和模块化 ,极大地提高了推理效率。推理机根据监控信息 ,推理计算出导弹允许发射的合格置信度 ,已应用于导弹发射决策专家系统设计中。     

论中美关系中的美国国会因素

由于宪法机制上的含糊性,美国历史上存在对外政策上的“府会”之争。冷战结束以来,国会实现了一种在对外政策上的“复兴”。伴随这一历史背景,国会在美国对华决策机制中所起的作用越来越大。从历史线索整理当代中美关系发展史上国会在不同时期对中美关系的影响,可以概括出美国国会在中美关系中的主要地位作用,进而得出影响美国国会对华政策的关键性原因:国会内部微观因素和外部制约因素。在此基础上,可以预测美国国会对中美关系进一步发挥影响的可能趋势,进而提出中国政府做国会工作的几点对策。     

具有自学习功能的电力负荷模糊推理预测

考虑到电力负荷预测问题中存在的不确定性,采用模糊推理预测方法进行负荷预测的研究。该方法利用电力最高负荷和国内生产总值的历史数据建立模糊推理规则,从而进一步建立最高负荷跟国内生产总值之间的模糊蕴涵关系,通过模糊推理得到了负荷预测结果。为了使模型能够象专家一样不断地总结新的经验并调整原有的经验,模型克服了其它模型中知识的凝固性,具有自学习功能。利用某些区的实际数据进行分析计算,得到了满足的结果。     

高校健身健美专家系统的设计和实现

为研究高校健身健美专家系统的设计和实现方法，探索有效的专家系统建造模型，采用．net编程技术，结合模糊技术、神经网络和面向对象等新技术的出现进行系统分析，构建了知识库及两套推理机，使用了自学习机制，提高了专家系统的运行效率。     

烧结法生产氧化铝生料浆的配料专家系统设计

基于烧结法生产氧化铝生料浆的配料机理和长期积累的专家经验知识,建立了生料浆质量预测模型,开发了适应于生料浆配料生产特点的专家优化配料系统.根据实际生产和配料机理,提出了产生式规则的知识表示形式,结合规则集分类原理,设计了生料浆配料的专家知识库.通过规则集之间的有知识搜索、规则集内部的前向推理、规则前提和结论之间的哈希算法的有机结合来实现推理机制,从而实现专家系统的优化配比计算.实际结果表明:该专家系统优化配比计算速度快、效率高,既提高了生料浆质量,又稳定了生产.     

关联理论与英语阅读浅析

关联理论是Sperber和Wilson提出的认知语用理论，且被广泛应用于各个领域。阅读就是作者示意和读者推理的交际过程，在英语阅读过程中，读者凭借认知语境中的词语信息、逻辑信息和百科信息等做出语境假设，从作者以文字方式明示的信息中寻找最佳关联，从而理解作者意图，达到阅读的目的，提高阅读的效果。