A generalized algorithm for duration and convexity of option embedded bonds

This article derives a generalized algorithm for duration and convexity of option embedded bonds that provides a convenient way of estimating the dollar value of 1 basis point change in yield known as DV01, an important metric in the bond market. As delta approaches 1, duration of callable bonds approaches zero once the bond is called. However, when the delta is zero, the short call is worthless and duration of callable will be equal to that of a straight bond. On the other hand, the convexity of a callable bond follows the same behaviour when the delta is 1 as shown in Dunetz and Mahoney (1988) as well as in Mehran and Homaifar’s (1993) derivations. However, in the case when delta is zero, the convexity of a callable bond approaches zero as well, which is in stark contrast to the non-zero convexity derived in Dunetz and Mahoney’s paper. Our generalized algorithm shows that duration and convexity nearly symmetrically underestimate (overestimate) the actual price change by 11/10 basis points for ± 100 basis points change in yield. Furthermore, our algorithm reduces to that of MH for convertible bonds assuming the convertible bond is not callable.     

一种基于Edline线特征的车道线识别算法

为了提升车道线检测的准确性和实时性,改良车道偏离预警系统的性能,提出了一种新的车道线识别算法。首先应用投影法对采集到的图像设立感兴趣区域,以此来减少图像中存在的干扰信息;其次应用一种改进后的自适应高斯滤波算法对采集所得图像进行平滑处理,减少图像中不必要的细节;最后采用边缘绘制算法进行边缘检测,在此基础上,提出一种线段检测算法——Edline算法提取边缘线,对检测到的直线段进行筛选和聚类。利用引用计数法对车道线进行跟踪和预测。结果表明,新算法的平均处理时间为17.1 ms,准确率为96.19%,将其应用在车道偏离预警系统中可以有效地提高预警效率,提升预警的准确性和响应速度。研究结果丰富了车道线识别理论,可为车道偏离预警系统的应用及基础研究提供参考。     

使用粒子群算法解决期权定价模型参数校准问题——以heston模型为例

期权定价模型的参数校准问题是一个常见的难题,以heston 模型为例,定价时需要估计6 个参数,参数估计问题实质上是高维非线性规划问题,由于估参函数的性质不好,一般的估参方法常常失效。使用粒子群（PSO）智能算法可以改善该模型的参数校准问题,因为粒子群算法具有内在随机性,因此参数估计中的局部极小值问题可以被较好地解决。使用2017 年12 月20 日的香港恒生指数期权作为估计样本,并对2017 年12 月25 日的期权进行样本外预测,数值结果表明使用heston 模型对期权进行定价并配合粒子群算法估计参数具有良好的定价效果。     

基于TLS的主动全向声呐浮标目标定位与跟踪

采用最小二乘(LS)拟和法进行主动全向浮标目标定位时容易受测量误差的影响,为此提出一种基于总体最小二乘法(TLS)的定位算法,首先对主动全向浮标的定位方程和测速方程进行变换形成线性的量测方程,然后利用潜艇测距误差和浮标定位误差的随机性,基于总体最小二乘法对量测方程进行递归解算,解算过程根据潜艇运动的物理限制,取运动模型的状态预测值作为递归过程的初值,最终实现了测量误差平滑化和航迹的整体优化。仿真结果显示算法较之最小二乘法具有更好的抑制噪声能力和机动目标跟踪能力。     

基于改进Dijkstra算法的最短路算法

Dijkstra算法是求解最短路径问题的经典算法。在现如今的城市交通网络中,经常需要寻求两个地点之间的最短距离,减少运输时间。本文将Dijkstra算法与C语言相结合,对Dijkstra算法进行改进,根据实际网络图的情况,建立了相应的数学模型,运用C语言编程,在给定的网络图中,实现了只需确定起始点和终点,就可以直接输出最短路径和最短距离的功能。在有多个相同最短路径的情况下,会将多个最短路径一起输出,在搜索到终点时,立即跳出,结束循环。在一般情况下,无需对所有点进行迭代,提高了效率。这种方法可以应用到现在的物流运输中,以此来节约时间,降低成本。     

基于成本优化的制造业生产物流装配线排序问题分析

为了降低制造业的生产成本，提高收益，在分析生产物流配线闲置和超载成本的基础上，采用粒子群算法对其进行优化，并利用模糊自适应改进惯性权值，通过实证研究表明该方法实用，可操作性强，可以有效降低制造业生产物流成本，具有广泛的应用价值。     

Numerical Maximisation of Likelihood: A Neglected Alternative to EM?

There is by now a long tradition of using the EM algorithm to find maximum‐likelihood estimates (MLEs) when the data are incomplete in any of a wide range of ways, even when the observed‐data likelihood can easily be evaluated and numerical maximisation of that likelihood is available as a conceptually simple route to the MLEs. It is rare in the literature to see numerical maximisation employed if EM is possible. But with excellent general‐purpose numerical optimisers now available free, there is no longer any reason, as a matter of course, to avoid direct numerical maximisation of likelihood. In this tutorial, I present seven examples of models in which numerical maximisation of likelihood appears to have some advantages over the use of EM as a route to MLEs. The mathematical and coding effort is minimal, as there is no need to derive and code the E and M steps, only a likelihood evaluator. In all the examples, the unconstrained optimiser nlm available in R is used, and transformations are used to impose constraints on parameters. I suggest therefore that the following question be asked of proposed new applications of EM: Can the MLEs be found more simply and directly by using a general‐purpose numerical optimiser?     

基于星载极化SAR数据的农作物分类识别进展评述

［目的］农作物播种面积信息不仅可为农情监测和作物估产提供重要的数据保障，还是国家制定粮食政策和经济计划的重要依据。快速、准确地获取农作物播种面积信息能为农业生产管理提供决策支持。极化SAR不受云雨天气的影响，在农作物遥感监测方面具有巨大的应用潜力，有效利用极化SAR数据进行农作物识别研究对促进雷达技术在国家农业遥感监测和农业供给侧结构性改革中发挥更大作用具有重要意义。［方法］以星载极化SAR技术的发展过程为论述主线，从单、双极化SAR数据，单、双极化SAR数据结合光学影像，全极化SAR数据三个发展阶段，对极化SAR数据在农作物分类识别中的研究与应用进行总结，并对比分析不同的识别特征、融合算法以及分类算法的优缺点。［结果］以往研究存在以下不足：当前研究多以识别水稻为主，对于难以识别的旱地作物研究较少；目前对旱地作物识别精度不高，平均识别精度不足85%；缺乏对不同作物散射机制及其随时相变化的研究，导致分类算法机理性不足，普适性较差。［结论］在今后的研究中，旱地作物散射机制的定量确定，如何利用散射机制及其变化来提高旱地作物遥感识别精度和普适性；目前分类算法大都是基于光学影像设计，如何利用SAR特殊的成像方式优化设计适用于极化SAR数据的分类算法，得到更高的分类精度；如何更好的跟光学遥感等多源数据（光学数据、GIS数据等）结合来提高精度，将成为未来极化SAR农作物识别中三个亟需重点解决的问题。     

The endo–exo problem in high frequency financial price fluctuations and rejecting criticality

The endo–exo problem lies at the heart of statistical identification in many fields of science, and is often plagued by spurious strong-and-long memory due to improper treatment of trends, shocks and shifts in the data. A class of models that has shown to be useful in discerning exogenous and endogenous activity is the Hawkes process. This class of point processes has enjoyed great recent popularity and rapid development within the quantitative finance literature, with particular focus on the study of market microstructure and high frequency price fluctuations. We show that there are important lessons from older fields like time series and econometrics that should also be applied in financial point process modelling. In particular, we emphasize the importance of appropriately treating trends and shocks for the identification of the strength and length of memory in the system. We exploit the powerful Expectation Maximization algorithm and objective statistical criteria (BIC) to select the flexibility of the deterministic background intensity. With these methods, we strongly reject the hypothesis that the considered financial markets are critical at univariate and bivariate microstructural levels.     

基于改进粒子群算法的无人机航迹规划

针对当前基本粒子群算法无人机航迹规划在后期收敛速度比较慢、效率不高、易陷入局部最优等问题,提出一种改进粒子群算法。首先,在迭代前期和后期分段设置惯性权值的调整,实现粒子惯性和寻优行为的平衡;其次,设置一个定值与相邻2次适应度函数最优值比较策略,防止陷入局部最优;最后,引入遗传算法的交叉、变异机制,得出更优的结果。并通过仿真验证了改进粒子群算法在三维空间航迹规划的有效性和可行性。结果表明,与其他航迹规划算法相比,新算法具有路径长度更短、耗时更少、路径更平滑等优点,加快了收敛速度,提高了航迹规划效率和稳定性。因此,改进算法的航迹规划可得到满足约束关系的最优航迹,对实现自主飞行有重要的参考价值。