Analytical approximations of local‐Heston volatility model and error analysis

This paper studies the expansion of an option price (with bounded Lipschitz payoff) in a stochastic volatility model including a local volatility component. The stochastic volatility is a square root process, which is widely used for modeling the behavior of the variance process (Heston model). The local volatility part is of general form, requiring only appropriate growth and boundedness assumptions. We rigorously establish tight error estimates of our expansions, using Malliavin calculus. The error analysis, which requires a careful treatment because of the lack of weak differentiability of the model, is interesting on its own. Moreover, in the particular case of call–put options, we also provide expansions of the Black–Scholes implied volatility that allow to obtain very simple formulas that are fast to compute compared to the Monte Carlo approach and maintain a very competitive accuracy.     

Examining artificial intelligence (AI) technologies in marketing via a global lens: Current trends and future research opportunities

Artificial intelligence (AI) has captured substantial interest from a wide array of marketing scholars in recent years. Our research contributes to this emerging domain by examining AI technologies in marketing via a global lens. Specifically, our lens focuses on three levels of analysis: country, company, and consumer. Our country-level analysis emphasizes the heterogeneity in economic inequality across countries due to the considerable economic resources necessary for AI adoption. Our company-level analysis focuses on glocalization because while the hardware that underlies these technologies may be global in nature, their application necessitates adaptation to local cultures. Our consumer-level analysis examines consumer ethics and privacy concerns, as AI technologies often collect, store and process a cornucopia of personal data across our globe. Through the prism of these three lenses, we focus on two important dimensions of AI technologies in marketing: (1) human–machine interaction and (2) automated analysis of text, audio, images, and video. We then explore the interaction between these two key dimensions of AI across our three-part global lens to develop a set of research questions for future marketing scholarship in this increasingly important domain.     

Drug testing and the law

This article examines judicial and administrative rulings and legislation involving or related to the issue of drug testing in the workplace. It discusses the rights of employees in the public and private sector: constitutional rights; federal, state, and local statutory rights; rights of unionized employees; and common law rights. It analyzes both the current state of the law and future directions the law may take, as courts and administrative agencies decide more cases and governmental bodies continue to pass drug testing legislation.     

基于建构主义的高职微积分教学方法探讨

微积分是高职院校一门非常重要的基础课程,是学生学习专业课程的基础和工具。传统的微积分教学基本上是传授型,重理论轻应用,忽视概念产生的实际背景和方法的实际应用,学生学起来感到困难,学了不知道如何用于解决实际问题。该从微积分的内容、教材的编写、教师的教学、学生的学习态度与方法四个方面分析了当前微积分教学中存在的问题,提出以建构主义学习理论为指导对微积分的教学进行改革,对从微积分发展史出发建构教学内容、以问题为中心组织教学、利用计算机进行微积分概念的辅助教学、注重数学建模能力的培养等教学方法进行了探讨。     

死者发表权与隐私权的冲突与保护

死者发表权的行使既要从公益出发、鼓励作品传播,又要以个性为落脚点保护作者合法权益。死者发表权的代行者出于个人利益往往会侵犯死者的隐私权。隐私权是人身权,是精神权利;发表权是著作权,有一定的物质利益,所以,发表权的行使应受到限制,在合理推定死者生前意图的基础上,最大限度地保护死者的隐私权。     

Optimal portfolio choice in the bond market

We consider the Merton problem of optimal portfolio choice when the traded instruments are the set of zero-coupon bonds. Working within a Markovian Heath–Jarrow–Morton model of the interest rate term structure driven by an infinite-dimensional Wiener process, we give sufficient conditions for the existence and uniqueness of an optimal trading strategy. When there is uniqueness, we provide a characterization of the optimal portfolio as a sum of mutual funds. Furthermore, we show that a Gauss–Markov random field model proposed by Kennedy [Math. Financ. 4, 247–258(1994)] can be treated in this framework, and explicitly calculate the optimal portfolio. We show that the optimal portfolio in this case can be identified with the discontinuities of a certain function of the market parameters.     

浅析大学物理微积分思想与矢量思想

本文探讨了微积分思想和矢量思想在大学物理教学中的应用,致力于总结出一个可靠的应用模式用于提高大学物理教学的质量。     

Beyond concern: socio-demographic and attitudinal influences on privacy and disclosure choices

ABSTRACT

The co-option of consumers as unwilling agents in their own surveillance has enabled significant abuses of consumer privacy. Previous studies have largely used privacy concern as a proxy for overall privacy attitudes. In this study, we implement a choice experiment in combination with measures adapted from Communication Privacy Management theory to enable a broader exploration of the influences of privacy attitudes by contextualising privacy as a negotiation about accessibility over contextual boundaries. Key findings suggest individuals’ social media disclosure decisions are influenced at least in part by their privacy attitudes, particularly with respect to information categories which may cue other personal information. Findings are also presented on consumers’ willingness to pay for privacy, with implications for alternative revenue streams not built on consumer surveillance.     

VALUATION OF BARRIER OPTIONS VIA A GENERAL SELF‐DUALITY

Classical put–call symmetry relates the price of puts and calls under a suitable dual market transform. One well‐known application is the semistatic hedging of path‐dependent barrier options with European options. This, however, in its classical form requires the price process to observe rather stringent and unrealistic symmetry properties. In this paper, we develop a general self‐duality theorem to develop valuation schemes for barrier options in stochastic volatility models with correlation.     

恶意软件隐私侵权问题研究

恶意软件是指在未明确提示用户或未经用户许可的情况下,在用户计算机或其他终端上安装运行,侵犯用户合法权益的软件。恶意软件侵犯网民关于网络生活不受非法侵入的隐私,剥夺网络用户对个人隐私的控制权,且侵权方式快捷,覆盖面极广,侵权后果严重。中国应通过单独立法、公益诉讼、行业自律等途径规范恶意软件的运行。