Price bias and common practice in option pricing

Generally, the semiclosed-form option pricing formula for complex financial models depends on unobservable factors such as stochastic volatility and jump intensity. A popular practice is to use an estimate of these latent factors to compute the option price. However, in many situations this plug-and-play approximation does not yield the appropriate price. This article examines this bias and quantifies its impacts. We decompose the bias into terms that are related to the bias on the unobservable factors and to the precision of their point estimators. The approximated price is found to be highly biased when only the history of the stock price is used to recover the latent states. This bias is corrected when option prices are added to the sample used to recover the states' best estimate. We also show numerically that such a bias is propagated on calibrated parameters, leading to erroneous values. The Canadian Journal of Statistics 48: 8–35; 2020 © 2019 Statistical Society of Canada     

Reducing sample size needed for cox-proportional hazards model analysis using more efficient sampling method

Abstract

In general, survival data are time-to-event data, such as time to death, time to appearance of a tumor, or time to recurrence of a disease. Models for survival data have frequently been based on the proportional hazards model, proposed by Cox. The Cox model has intensive application in the field of social, medical, behavioral and public health sciences. In this paper we propose a more efficient sampling method of recruiting subjects for survival analysis. We propose using a Moving Extreme Ranked Set Sampling (MERSS) scheme with ranking based on an easy-to-evaluate baseline auxiliary variable known to be associated with survival time. This paper demonstrates that this approach provides a more powerful testing procedure as well as a more efficient estimate of hazard ratio than that based on simple random sampling (SRS). Theoretical derivation and simulation studies are provided. The Iowa 65+ Rural study data are used to illustrate the methods developed in this paper.     

A class of additive transformation models for recurrent gap times

Abstract

The gap time between recurrent events is often of primary interest in many fields such as medical studies, and in this article, we discuss regression analysis of the gap times arising from a general class of additive transformation models. For the problem, we propose two estimation procedures, the modified within-cluster resampling (MWCR) method and the weighted risk-set (WRS) method, and the proposed estimators are shown to be consistent and asymptotically follow the normal distribution. In particular, the estimators have closed forms and can be easily determined, and the methods have the advantage of leaving the correlation among gap times arbitrary. A simulation study is conducted for assessing the finite sample performance of the presented methods and suggests that they work well in practical situations. Also the methods are applied to a set of real data from a chronic granulomatous disease (CGD) clinical trial.     

The arithmetic of outcome editing in financial and social domains

Outcome editing refers to a set of mental rules that people apply when deciding whether to evaluate multiple outcomes jointly or separately, which subsequently affects choice. In a large-scale online survey (n = 2062) we investigate whether individuals use the same outcome editing rules for financial outcomes (e.g., a lottery win) and social outcomes (e.g., a party with friends). We also test the role of numeric ability in explaining outcome editing. Our results show that people’s preferences for combining or separating events depend on whether those events are in the financial or the social domain. Specifically, individuals were more likely to segregate social outcomes than monetary outcomes, except for when all outcomes were negative. Moreover, numeric ability was associated with preferences for outcome editing in the financial domain but not in the social domain. Our findings extend the understanding of the arithmetic operations underlying outcome editing and suggest that people rely more on calculations when making choices involving multiple financial outcomes and more on feelings when making choices involving social outcomes.     

论《侵权责任法》规定的医疗产品损害责任

《侵权责任法》规定的医疗产品损害责任，从性质上来说，既是医疗损害责任的一个特殊类型，也属于产品责任的范畴，适用无过错责任原则。其中第59条规制的适用范围包括有缺陷的药品、消毒药剂和医疗器械以及不合格的血液，但此适用范围应予以界定。在此界定内，导致患者损害的医疗机构、生产者所承担的赔偿责任才是《侵权责任法》第59条规定的医疗产品损害责任。     

医学生择业过程中的心理状况与职业生涯规划

随着大学毕业生人数的激增以及用人单位对于专业化程度要求的提高，就业形势变得日益严峻。同时，由于地区间经济发展的不平衡，人才往城市倾斜现象较为严重，由此出现城市与乡镇医院人才供求比例严重失衡。伴随社会问题出现的是医学生对于职业生涯规划的定位不准确而产生的各种心理问题，这些心理上的困境正严重地威胁着医学生职业前途。本文通过对医学生择业困境中的心理状态进行溯源与探讨，并结合我国目前医学生群体的就业状况，论述医学生择业过程中存在的心理问题，提出有针对性的解决方案与符合医学生群体特征的职业生涯规划，以期能为医学生群体带来一定的帮助。     

医学生医德教育的困境及对策

医德是保证社会医疗卫生事业健康发展的一个重要因素，而关于医德方面的教育也是医学教育中的重要组成部分之一。可以说，医德教育的好坏直接关系到社会医德风尚，但是从目前的形势上来看，在我国现行的医学生医德教育中实际上是存在着许多问题的，医德教育很多时候都是在困境中前行的。因此在本文中作者在对医德教育其重要意义进行了阐释的基础上就医学生医学教育中存在的诸多问题进行了剖析，并就这些问题提出了相应的解决方案和应对策略，旨在以此为提高医学生医德教育的质量提供一定的参照和指导。     

新环境下培育医学生社会责任感的探析

当前，医务人员不仅要具备精湛的医术，还要具有高尚的医德。社会责任感是医学生医德的重要体现，因此，本文主要论述了影响医学生社会责任感的因素和加强其社会责任感培育的途径。     

独立院校医学生人文素质教育分析与对策研究

人文素质教育对于医学生的培养不容忽视。由于我国现行医学生选拔和培养模式、独立院校校园文化薄弱和“三本”学生自身特点等因素影响，独立院校医学生人文素质教育有待加强。独立医学院校应从深化教学改革、提高师资力量、建设校园文化、增强临床教学等四方面入手，努力提高医学生人文素养，不仅有利于医学生的成长成才，也有利于缓和当前的医患矛盾，更有助于推动医疗卫生事业的和谐发展。     

新医改背景下医科大学生价值取向变化趋势及教育引导研究

新医改的价值目标是公益性，对于当前医科大学生价值取向的产生、形成具有重要导向作用。当前医科大学生价值取向出现了价值目标趋于功利化、迷失医学真正目的；医学技术至上、自身技术能力下滑；科研作风不够严谨，人文素质滑坡等趋势。因此，应从树立崇高职业理想，提升使命感和责任感；创新医德教育体系，强化思想政治教育育人功能；关注物质精神需求，提高从医幸福感等方面教育引导医科大学生树立正确价值取向。