变波动率多期复合实物期权定价模型及应用

当前复合期权理论与方法的研究主要集中于两个方面;其一是将简单两期复合期权理论推广至多期情形,其二是建立标的资产具有一般形式随机运动过程的复合期权定价模型及求解方法.本文提出了变波动率多期复合实物期权定价控制方程及相应的边界条件和终端条件,采用隐式差分格式获得了问题的数值解,并结合风险投资的实例展开了讨论.结果表明,与传统复合期权期权定价方法[1]相比较,本文给出的方法计算精度高,收敛速度快;常波动率多期复合期权定价模型明显高估了风险投资期初的执行阚值而低估了后期的执行阚值,且低估了风险投资的内在价值.     

近代的机械论与辩证论:一般系统论思想形成的逻辑环节

近代科学哲学思想对一般系统论的创立产生了重大影响。近代科学哲学思想可以分为两个时期:第一个时期是15世纪下半叶到18世纪末的形而上学整体观时期,这一时期完成了对自然界各门类深层规律的揭示,为人类的认识达到新的整体化阶段创造了条件;第二个时期是19世纪的辩证整体观时期,这一时期则揭示出世界就是普遍联系的辩证整体。这两个时期都是一般系统论思想得以形成的逻辑环节。     

资本回报率宏观核算法的进一步改进和再测算

已有研究对资本回报率的宏观核算方法进行了一系列改进,但在资本报酬处理和资本存量估计方面仍未达成共识,导致资本回报率测算结果存在较大差异。本文参照《OECD资本测算手册2009》,梳理分析了资本回报率的内涵及其宏观核算方法的演进脉络,探讨了资本回报率测算时的资本存量口径问题,提出了将"具有生产能力的资本存量"纳入核算方法中进行测算的设想,设计了将生产税净额中由资本创造部分进行剥离,以及针对个体经营业主混合收入和国有农场营业盈余进行调整的思路和改进方法。再测算结果显示:1978-2017年我国税后实际资本回报率在7.28%～13.05%之间,这一结果在走势上能有效刻画资本回报率的阶段变化特征,并印证了已有的相关统计数据。本文所做的工作,对于从宏观核算角度改进资本回报率的测算精度和完善我国的资本核算研究有积极的意义。     

PERCEIVED INFORMATION STRUCTURE: IMPLICATIONS FOR DECISION SUPPORT SYSTEM DESIGN

Top-level decision making in business organizations is characterized by high degrees of uncertainty, incomplete information, and conflicting objectives. To support top-level decision making effectively, decision support systems (DSSs) have been proposed. Information supplied by a DSS must be selective in that not all possible information sets may be feasibly or economically represented in the data base. This study suggests that discovery of perceptual complexity (dimensionality) of information items, and the subsequent categorization of decision makers having the same perceptions of those information items, is a first step in the ultimate design of an effective DSS. Through the use of multidimensional scaling in a field setting, this study shows the feasibility of creating relatively homogeneous groups of decision makers according to the content and number of dimensions associated with various information items. Further results of the research suggest that information can be tailored to classes of users, which has cost-benefit implications as well as the potential to improve the quality of the resultant decisions.     

On the scientific study of small samples: Challenges confronting quantitative and qualitative methodologies

Often phenomena that are important to understand and predict are very rare. Rare events can prove difficult to analyze systematically because they do not generate many sampling observations. In this article I examine how small sample sizes can be studied scientifically. The article begins with an explanation of the distinction between research and science. I then bring to the fore the importance of counterfactual comparisons and outline the nature of the methodological problems posed by the study of small samples. These problems include challenges related to using a single case, small sample sizes, selecting on the dependent variable, regression toward the mean, explaining a variable with a constant, and using the same data to both generate and test hypotheses. I provide potential resolutions to these problems which are: (a) employing matched controls; (b) shifting or widen the category of inquiry; (c) selecting variables based on variance in the independent variable; (d) including counterfactuals; (e) ensuring that both independent and dependent variables demonstrate variation; and (f) testing potential hypotheses against data sets that are fully independent of those used to generate the hypotheses. I conclude with a discussion of future directions for undertaking a more scientific approach to using small samples.     

Conceptualizing Effects of Office Information Systems: A Methodology and Application for the Study of Alpha,Beta, and Gamma Changes*

This article applies the concepts of alpha, beta, and gamma changes to test whether the implementation of a new office information system with networking capabilities changes the way organizational members conceptualize office work. The traditional approach (t-test) was used to measure alpha change and indicated little change in how effectively the respondents felt they performed eight generic office activities before implementation (T1) and nine months after implementation (T2). However, considerable change was detected between effectiveness reported at T1 and a retrospective assessment of T1 effectiveness reported at T2 (called “then” assessments). Strong change was also detected between “then” assessments and T2 effectiveness reported at T2, indicating beta change. Multiple hierarchical tests showed that most of the change was actually gamma change; the T2 and the “then” factor structures and covariances differed significantly. This study supports propositions that using computers to accomplish organizational work may be associated with different conceptualizations of work, which may create ambiguity and uncertainty if training and management policies do not respond appropriately. Finally, this study provides an expanded version of a prior solution to detecting alpha, beta, and gamma changes.     

A mixed methods evaluation of Multiple Mini Interviews for entry into the Bachelor of Midwifery

BackgroundMultiple-mini interviews (MMI) are increasingly used as part of the admission process into healthcare degrees. Evaluations have found MMIs to be a fair assessment tool in terms of reliability and validity and viewed positively by those involved in the MMI process. The use of MMIs in midwifery is novel and evaluation is lacking.AimTo evaluate the use of MMIs as part of the admission process for the Bachelor of Midwifery in one Australian university.MethodsA basic convergent mixed methods study design was utilised. Data included linked data sets, Likert scale responses to survey questions, focus groups and open-ended survey questions. Integration took place at the interpretation and reporting stage.FindingsParticipants viewed the MMI experience positively. The study confirmed the reliability of the MMIs as an assessment tool. Most variance in MMI scores was attributed to the candidate at 31.4 % with the interviewer and the interview station having less influence on the MMI score at 11 % and 6.4 % variance. Older applicants on average achieved higher MMI scores, and those who spoke a language other than English at home or were first in family to attend university had lower on average MMI scores. Being born overseas did not impact an applicant’s MMI score. The overall experience was seen as fair, offering further opportunity to gain entry into the Bachelor of Midwifery.ConclusionMMIs were viewed positively and findings support the use of MMIs as part of an admissions process for the Bachelor of Midwifery.     

Education TEAM-SIZE EFFECTS ON BUSINESS GAME PERFORMANCE AND DECISION-MAKING BEHAVIORS

The effects of various decision-making team sizes in a complex business game were studied. Firm size was associated with nonlinear performance results and decision curves resulting in differential learning outcomes, learning sources, attrition rates, and decisionmaking behaviors. A three-member format produced the highest learning levels while two-member firms experienced only marginally significant knowledge increases. Single-member firms experienced the most bankruptcies and dropouts. A contingency view of gaming effectiveness is suggested.     

Increasing the Effectiveness of Student Evaluation of Instructor Data through a Factor Score Comparative Report

Effective student evaluation of instructor instruments must provide norm, or comparative, data to aid interpretation. This note highlights an innovative factor score comparative report. Rather than merely reporting comparative data on individual questions items, the innovative report provides comparative percentile data on the six factors underlying our thirty-three item questionnaire. The faculty indicated overwhelming support for the new report. The note also briefly mentions three other activities that are essential for student evaluation of instructor data to improve teacher effectiveness. Our goal is to stimulate other colleges to adopt the innovative norming practice once they have validated their local evaluation instruments. College-wide improvement of teaching will occur through such do-it-yourself efforts and only decision science faculty are technically qualified to lead such efforts.     

Evaluating and Refining Expert Critiquing Systems: A Methodology*

Expert critiquing systems are a rapidly growing class of intelligent decision support systems that apply artificial intelligence techniques to criticize a user's proposed solution to a problem. Critic programs now exist in the medical, engineering, programming, knowledge acquisition, word processing, and other domains. Critic refinement is a nontrivial activity that, even when done well, consumes a sizable fraction of the complete effort to build and deploy a critiquing system. To ease that effort, it is important to adopt a rigorous approach that allows one to reproducibly measure the degree of success of the current critic version and to predict which refinements will improve the critic further. The current article presents one such approach with actual case studies that illustrate its usage and elaborate selected aspects of the refinement process.