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。     

Anticipated Backward Stochastic Differential Equation with Reflection

In this article, we deal with anticipated backward stochastic differential equation with reflecting boundary. The existence and uniqueness of solution is obtained for equation with Lipschitz and non-Lipschitz generator.     

Accelerating inference for diffusions observed with measurement error and large sample sizes using approximate Bayesian computation

In recent years, dynamical modelling has been provided with a range of breakthrough methods to perform exact Bayesian inference. However, it is often computationally unfeasible to apply exact statistical methodologies in the context of large data sets and complex models. This paper considers a nonlinear stochastic differential equation model observed with correlated measurement errors and an application to protein folding modelling. An approximate Bayesian computation (ABC)-MCMC algorithm is suggested to allow inference for model parameters within reasonable time constraints. The ABC algorithm uses simulations of ‘subsamples’ from the assumed data-generating model as well as a so-called ‘early-rejection’ strategy to speed up computations in the ABC-MCMC sampler. Using a considerate amount of subsamples does not seem to degrade the quality of the inferential results for the considered applications. A simulation study is conducted to compare our strategy with exact Bayesian inference, the latter resulting two orders of magnitude slower than ABC-MCMC for the considered set-up. Finally, the ABC algorithm is applied to a large size protein data. The suggested methodology is fairly general and not limited to the exemplified model and data.     

Bayesian penalized B-spline estimation approach for epidemic models

Ordinary differential equations (ODEs) are normally used to model dynamic processes in applied sciences such as biology, engineering, physics, and many other areas. In these models, the parameters are usually unknown, and thus they are often specified artificially or empirically. Alternatively, a feasible method is to estimate the parameters based on observed data. In this study, we propose a Bayesian penalized B-spline approach to estimate the parameters and initial values for ODEs used in epidemiology. We evaluated the efficiency of the proposed method based on simulations using the Markov chain Monte Carlo algorithm for the Kermack–McKendrick model. The proposed approach is also illustrated based on a real application to the transmission dynamics of hepatitis C virus in mainland China.     

众数测算的一种新方法及其应用

针对传统众数估计值会因为组距的改变而不稳定,在已有的半极差(样本)众数估计方法上,提出多比例极差(样本)众数估计新方法。模拟研究显示,相对于半极差(样本)众数估计方法,该方法估计结果更稳定、准确。在实证分析中,基于2014、2015年国家一体化住户调查数据,使用新方法计算了新疆兵团居民人均可支配收入众数。结果表明,众数可以作为居民人均可支配收入平均数、中位数的有益补充,众数在政府统计中的推广及应用具有一定的可行性与必要性。     

A class of integral operators generated by random variables

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D. Rasch: Einführung in die muthematisehe Statlstik - II .Anweuduugen, VEB Deutscher Verlag der Wissenschaften, Berlin 1976.

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地下空间的软导向识别及主要设计策略

针对软导向设计具有改善用户在特定导向任务中的寻路效率和效果的假设,利用意向尺度法对包含软导向设计的空间和不包含软导向设计的空间进行对比调研。结果证明,软导向设计可以明显提升导识效率,并发现随着用户对空间熟悉程度的增加,一些地标性差异物可以成为用户稳定可靠的定位要素,从而对常规标识系统的依赖度逐渐下降。由此提出应通过色彩和光影变化、立体造型与显著空间标志物的设置、平面造型的图案规划与差异、材料和肌理以及装饰强度的对比等措施完成空间中的软导向设计。并认为软导向设计前期需要在充分调研的基础之上开展,在设计过程中不但要节制规范的使用软导向要素,还应与空间主题语境相呼应。     

Impatience versus Incentives

This paper studies the dynamics of long‐term contracts in repeated principal–agent relationships with an impatient agent. Despite the absence of exogenous uncertainty, Pareto‐optimal dynamic contracts generically oscillate between favoring the principal and favoring the agent.     

损失厌恶、后悔厌恶与沉没成本效应的关联性分析

以往研究认为沉没成本效应的产生与损失厌恶和后悔厌恶相关,但对其相互关系的探讨较少考虑货币性沉没成本和非货币性沉没成本的不同影响.文章选取证券监管者和证券市场投资者作为被试对象,通过有情境因素的调查问卷对损失厌恶、后悔厌恶与沉没成本效应之间的关联性进行验证.实证结果发现,与证券市场投资者相比,证券监管者的损失厌恶倾向要显著更低,而二者的后悔厌恶和沉没成本效应则无显著差异;证券监管者的数据结果表明,后悔厌恶与沉没成本效应之间存在显著的相关性,而损失厌恶与沉没成本效应之间不存在显著的相关性;相比之下,证券市场投资者的数据结果则表明,损失厌恶与沉没成本之间存在显著的相关性,而后悔厌恶与沉没成本之间则不存在显著的相关性.