Effect of risk preference on the valuation of time charter contracts with extension options

ABSTRACT

The literature on valuation of time charter contracts and real options in shipping generally relies on the complete markets hypothesis and the risk-neutrality of agents. However, these assumptions fail completely in some shipping market segments. This study proposes a numerical approach—based on discounting the certainty equivalent payoff at the risk-free rate—which incorporates the agent’s risk preferences through an exponential utility function. The method comprises an iterative Monte Carlo nested simulation with the real probability measure. This method is applied to a case of Suezmax tankers. The stochastic evolution of the time charter rates is modelled as a geometric mean-reverting process. The case study supports the applicability of the proposed method and evidences that the effect of risk preference may be significant, mainly for more risk-averse agents. Although the method involves intensive computation, it has the benefits of theoretical ease and flexibility, which could encourage utilisation by practitioners.     

Airport–Airline interaction: some food for thought

Abstract

We provide an interpretive analysis of vertical relations between airports and carriers, while assessing the way in which deregulation of the airline market and the privatization of airports have created incentives for airport–airline interaction. In particular, if the vertical structure approach has become the standard approach in air transport research, we add to the literature by discussing three issues that we believe need further understanding. The three issues that we think should be the focus of future research on airport–airline interaction are (i) incomplete contracts and asymmetric information structure; (ii) upstream horizontal complementarities; and (iii) airports as two-sided platforms.     

基于 ECDIS 的雷达与 AIS 信息融合的算法与工程实现

为达到雷达与AIS（船舶自动识别系统）优缺点互补以提高航行安全性的目的,提出AIS目标信息与雷达目标信息融合算法。采用多因素模糊综合决策算法进行目标关联,并且基于ECDIS （电子海图显示系统）实现雷达与AIS目标信息融合。工程研究与实现最终验证了融合算法的可靠性及有效性。     

Orthogonal discriminant improved local tangent space alignment based feature fusion for face recognition

Improved local tangent space alignment (ILTSA) is a recent nonlinear dimensionality reduction method which can efficiently recover the geometrical structure of sparse or non-uniformly distributed data manifold. In this paper, based on combination of modified maximum margin criterion and ILTSA, a novel feature extraction method named orthogonal discriminant improved local tangent space alignment (ODILTSA) is proposed. ODILTSA can preserve local geometry structure and maximize the margin between different classes simultaneously. Based on ODILTSA, a novel face recognition method which combines augmented complex wavelet features and original image features is developed. Experimental results on Yale, AR and PIE face databases demonstrate the effectiveness of ODILTSA and the feature fusion method.     

基于语义Agent的网络安全数据采集模型

针对网络安全数据的多源异构特点,将语义网技术引入到基于Agent的数据采集模型中,设计了一种分布式采集、集中式管理的网络安全数据采集模型.该模型基于语义Agent对多源异构安全数据进行采集,并将其统一表示为具有语义的标准化数据,为其他系统提供更为全面、可靠、准确以及易于理解的数据,消除语义理解差异.     

多源图像融合技术研究

图像融合分为三个层次：像素级融合、特征级融合和决策级融合。论文主要介绍了像素级图像融合的常用算法,分析了各算法的特点,因单一算法存在缺陷,故提出图像二次融合模型来综合两种算法的优点,弥补缺陷,使融合图像达到良好的效果。     

产教融合背景下高职公共课教学调查与思考——以武汉软件工程职业学院为例

本研究旨在调查在产教融合背景下,高职公共课的教学现状,以便为教改进一步明晰方向。本研究以武汉软件工程职业学院部分学生为研究对象,通过问卷调查了《应用写作》等5门公共课的教学情况。基于数据,对学生学习动机、学生自我认识、教学方法、理想教师和理想教学等做出分析。本研究认为:应从提高师能,公共课程深度定位和深度开发,以行动导向法提升教学效能等三个方面入手进行高职公共课教改。     

基于交通综合信息平台的概率交通预报方法

以交通综合信息平台为数据支撑,考虑交通指数发布对交通预测的影响,应用模式匹配和概率统计方法构建了概率交通预报方法的流程框架,研究了概率交通预报的2项关键实现技术,包括3级交通数据融合方法和交通指数发布内容.算例结果表明:概率交通预报使主路径和替代路径的饱和度差值从40%降低到23%;由于概率交通预报方法在考虑交通指数发布对出行行为影响的基础上对交通预测结果进行了修正,所以提高了交通预报的可信度,使路网交通负荷趋于均衡.     

高速公路非接触式交通检测技术的应用研究

非接触式交通检测技术具有检测范围大,安装维护方便等优点,在高速公路动态交通数据采集中不断得到应用。本丈在分析各种非接触式检测技术特性和精度的基础上,通过现场实验,研究了非接触式检测技术的应用功能、基于微波一线圈的组合应用及其数据融合。实验结果表明,非接触式交通检测技术在高速公路动态数据检测中可以使用,但由于受检测精度、数据类型、范围与安装使用条件的影响,不宜单独使用;通过非接触式与接触式检测技术的组合应用,克服了接触式检测器难以维护的缺陷,并且多检测技术数据融合的检测精度比单一检测技术提高10％～15％。     

一种基于信息融合的跟随驾驶行为协同仿真模型

基于信息融合技术模拟驾驶人信息感知、分析决策和车辆控制的全过程,建立跟随驾驶协同仿真模型.模型以动态交通信息为输入,设计单个神经元仿真驾驶人对感知信息的筛选,采用模糊径向基高斯神经网络提取驾驶行为特征向量,应用模糊积分法模拟驾驶人对信息的分析和决策过程,输出为车辆控制状态.离线检验结果表明,该模型能较好地描述跟随车状态变化,具有较高的精度.