考虑属性关联的两阶段获胜者确定模型

研究了多属性逆向拍卖的获胜者确定问题。考虑属性之间的两两关联，以定义在2-可加模糊测度上的Choquet积分表达拍卖人的偏好，其中模糊测度的值由拍卖人提供的偏好信息推测得出。由于一般情况下与偏好信息一致的模糊测度取值并不唯一，考虑所有一致的评分函数提出了两阶段获胜者确定方法。首先采用线性规划挑选出在任意评分函数下可能获胜的报价，再通过混合整数规划确定一个与所有一致的评分函数的评价结果最为接近的报价排序，以得分最高者为稳健获胜报价。仿真实验表明，大量的报价为不可能获胜报价，说明了在第一阶段进行筛选的必要性。与现有方法的比较表明了该方法的有效性，且在拍卖轮数较大、报价数目较多时，该方法在计算效率上更有优势。     

Beyond tail median and conditional tail expectation: Extreme risk estimation using tail Lp-optimization

The conditional tail expectation (CTE) is an indicator of tail behavior that takes into account both the frequency and magnitude of a tail event. However, the asymptotic normality of its empirical estimator requires that the underlying distribution possess a finite variance; this can be a strong restriction in actuarial and financial applications. A valuable alternative is the median shortfall (MS), although it only gives information about the frequency of a tail event. We construct a class of tail L^p-medians encompassing the MS and CTE. For p in (1,2), a tail L^p-median depends on both the frequency and magnitude of tail events, and its empirical estimator is, within the range of the data, asymptotically normal under a condition weaker than a finite variance. We extrapolate this estimator and another technique to extreme levels using the heavy-tailed framework. The estimators are showcased on a simulation study and on real fire insurance data.     

碳金融市场下基于模糊测度和Choquet积分的碳期权估值

基于投资者对投资财富和风险的偏好研究碳期权定价模型。运用λ-可加模糊测度表示投资者对碳期权价值模糊度量的差异性，借助Choquet期望积分构建投资者的期望收益效用函数；根据投资财富效用最大化推导无约束条件下碳期权的最优价；结合现实约束条件，构建投资财富效用最大化下的碳期权定价模型；通过数值计算分析效用函数、模糊参数和现实约束对碳期权定价的影响。研究结果表明:效用函数的选择会体现投资者对碳期权投资风险态度的变化，模糊测度参数的取值能够反映碳期权投资者个体的主观情绪和市场信息获取程度，现实约束会迫使碳期权投资者放弃部分投资隐含价值。     

Dynamics of the term structure of interest rates and monetary policy: is monetary policy effective during zero interest rate policy?

The monetary policy targets the short rates; however, during zero interest rate policy (ZIRP), the short end of the yield curve cannot serve as a policy instrument. Relying on the joint yields-macro latent factors model, this study empirically examines the effect of monetary policy stances on term structure and the possible feedback effect on the real sector using the Japanese experience of ZIRP. The analysis indicates that it is the entire term structure that transmits the policy shocks to the real economy rather than the yield spread only. The monetary policy signals pass through the yield curve level and slope factors to stimulate the economic activity. The curvature factor, besides reflecting the cyclical fluctuations of the economy, acts as a leading indicator for future inflation. In addition, policy influence tends to be low as the short end becomes segmented toward medium/long-term of the yield curve. Furthermore, volatility in bond markets is found to be asymmetrically affected by positive and negative shocks and long end tends to be less sensitive to stochastic shocks than the short maturities. The expectation hypothesis of the term structure does not hold during the ZIRP period.     

Symbolic correlation integral

This paper aims to introduce the concept of symbolic correlation integral SC that is extensively used in many scientific fields. The new correlation integral SC avoids the noisy parameter 𝜀 of the classical correlation integral, defined by Grassberger and Procaccia (1983 Grassberger, P., Procaccia, I. (1983). Measuring the strangeness of strange attractors. Physica D: Nonlinear Phenomena 9(1–2):189–208.[Crossref], [Web of Science ®] , [Google Scholar]) and extensively used for constructing correlation-integral-based statistics, as in the BDS test. Once the free parameter 𝜀 disappears, it is possible to construct a nonparametric powerful test for independence that can also be used as a diagnostic tool for model selection. The symbolic correlation integral is also extended to deal with multivariate models, and a test for causality is proposed as an example of the theoretical power of the new concept. With extensive Monte Carlo simulations, the paper shows the good size and power performance of symbolic correlation-integral-based tests.     

投资者情绪生成机理的研究

基于标准金融理论与行为金融理论相结合的思想，力图刻画投资者情绪的生成机理。以引起投资者情绪变化的货币环境、市场收益、市场波动、相关资产收益等因素为起点，引入市场投资价值、市场预期两个中间变量，建立了包含直接和间接影响两类路径的投资者情绪生成概念模型。使用中国股市2014年7月1日至2017年3月31日间的667组日度数据，在VAR建模的基础上开展实证研究。实证结果表明市场收益对投资者情绪具有直接的正向影响，市场波动和相关资产收益两因素基于市场预期中介变量间接负向作用于投资者情绪，而修正后引入的经济周期波动变量可以基于市场投资价值中介变量对投资者情绪产生正向影响，并进一步发现了市场收益、市场投资价值与投资者情绪之间存在正反馈强化过程。研究揭示出了投资者情绪生成的影响因素体系及其实现路径，将该领域研究深入到机理分析层面，并从一个侧面佐证了中国股市过度投机行为的存在。     

从偏见视角解读医患关系

偏见是个体以不正确或不充分的信息为依据,并对其他人形成先入为主的负性判断,泛化至群体中则会表现为人们对某群体产生片面或错误的认知。文章从消极刻板印象、期望差异与归因偏差这三个角度解释了医患群体产生偏见的心理机制,在此基础上讨论偏见对医患关系造成的消极影响,并结合社会现实提出减少医患双方偏见的方法。     

教育期望中的班级效应分析

班级是中国基础教育领域重要的组织设置。利用“中国教育追踪调查”（CEPS）数据，应用分层线性模型，本研究关注班级设置，包括班级组织结构和班级氛围，对初中生教育期望的影响。研究结果表明，在多个组织结构变量中，班主任的受教育程度和教龄对学生教育期望影响显著，但任课老师的资历影响不显著；在多个班级氛围变量中，学生的教育期望既受到班级客观学业水平的影响，亦受到师生之间互动关系的影响。此外，在控制了班级氛围变量后，师资配置对学生教育期望的影响不再显著。总之，在以往研究重点关注个体、家庭和学校影响的基础上，本研究将对教育期望的研究进一步拓展到学校内部的班级环境，并发现师生之间建立的紧密互动关系及良好的班级氛围对学生的教育期望发挥着最重要的影响。     

指令驱动市场中非知情交易者的最优交易策略

在非对称信息下,综合非知情交易者对资产价值的预期、私人估值及资产价值波动,构造指令驱动市场价格形成的动态模型,给出非知情交易者指令提交策略的解析解,并依此描述了非知情交易者对资产价值预期的动态更新过程.研究发现:私人估值和资产价值波动通过影响非知情交易者最优策略,使得市场进入不同均衡状态;在每个均衡状态下,非知情交易者根据资产价值的预期变化更新交易策略,进而引起知情交易者策略调整,特别地,使得知情交易者被挤出市场成为可能.进一步分析表明,私人估值、资产价值波动及知情交易者比例对市场流动性的影响依赖于每个均衡中限价指令执行风险的差异.