Sample selection in radiocarbon dating

Archaeologists working on the island of O'ahu, Hawai'i, use radiocarbon dating of samples of organic matter found trapped in fish-pond sediments to help them to learn about the chronology of the construction and use of the aquicultural systems created by the Polynesians. At one particular site, Loko Kuwili, 25 organic samples were obtained and funds were available to date an initial nine. However, on calibration to the calendar scale, the radiocarbon determinations provided date estimates that had very large variances. As a result, major issues of chronology remained unresolved and the archaeologists were faced with the prospect of another expensive programme of radiocarbon dating. This paper presents results of research that tackles the problems associated with selecting samples from those which are still available. Building on considerable recent research that utilizes Markov chain Monte Carlo methods to aid archaeologists in their radiocarbon calibration and interpretation, we adopt the standard Bayesian framework of risk functions, which allows us to assess the optimal samples to be sent for dating. Although rather computer intensive, our algorithms are simple to implement within the Bayesian radiocarbon framework that is already in place and produce results that are capable of direct interpretation by the archaeologists. By dating just three more samples from Loko Kuwili the expected variance on the date of greatest interest could be substantially reduced.     

A spanning heuristic for the unordered and ordered matching identification problem

The matching identification problem (MIP) is a combinatoric search problem related to the fields of learning from examples, boolean functions, and knowledge acquisition. The MIP involves identifying a single “goal” item from a large set of items. Because there is commonly a cost associated with evaluating each guess, the goal item should be identified in as few guesses as possible. As in most search problems, the items have a similar structure, which allows an evaluation of each guessed item. In other words, each guessed item elicits partial information about the goal item, i.e. how similar the guess is to the goal. With this information the goal is more quickly identified.The unordered MIP has been studied by Mehrez and Steinberg (ORSA J. Comput. 7 (1995) 211) in which they proposed two different types of algorithms. The purpose of the present paper is to suggest an improved Spanning Heuristic algorithm. Its improvement increases as the problem size increases. Further results and comparisons are derived for the unordered and ordered cases.This research shows that when the search space is very large, it is better to inquire from items that are known not to be the goal (they have been ruled out by previous guesses), for the purpose of acquiring more information about the goal. As the search space is narrowed, it is better to guess items that have not been ruled out.     

金融市场多标度分形现象及与风险管理的关系

已有研究通过对汇率、股票收益率、黄金价格等金融市场实证数据的分析,发现这些数据 具有多标度分形(multifractal) 特征. 通过对中国金融市场的代表数据之一———上海证券交易 所综合股价指数(SSECI) 的研究得出了相似的结论,并且初步提出了运用多标度分形理论所 提供的信息来进行金融风险管理的风险管理思路.     

TOT项目融资中国有资产转让定价的博弈分析

本文以TOT项目融资方式为对象,运用博弈的方法,从合理分配国有资产经营期内增值收入的角度出发,得出这样的结论,在国有资产转让过程中,政府与私营资本之间的谈判是一系列复杂的博弈过程,在博弈中政府的最优行为是对国有资产转让进行招标,同时给予某一招标企业一定的中标优先权,这样政府能够较现行的国有资产转让方式获得更多的收益.     

两阶段供应链中三种定价方式研究

本文考虑渠道一体化对品牌建设的作用,在一个制造商和两个零售商的两阶段供应链系统中,其中确定性的市场需求与产品的市场零售价格有关,通过分析以下三种定价方式下的最优定价和库存策略下供应链成员和系统的收益,1)商品市场零售价格由零售商各自决定,两零售商和制造商之间存在着竞争活动;2)商品市场零售价格由制造商统一制定;3)市场零售价格、转让价格和系统库存水平按渠道协调的最优原则确定,确定了同一产品品牌内部的市场竞争、定价控制权及转让价格对渠道性能及品牌自身造成的影响,并由此提出了分散决策系统中的一种激励机制.     

基于反向物流的商品定价和退货政策研究

综述了基于反向物流的商品定价和退货政策的最新研究成果。在此基础上,通过建立模型,对基于反向物流的商品定价策略和退货政策进行了进一步的研究,并求出了商品的最优价格和最优退货价格。基于模型,对管理提出了一些建议。最后指出了将来可能的研究方向。     

PC软件产品竞争性升级的定价研究

通过Hotelling模型对PC软件产品竞争性升级进行了研究,重点分析了网络外部性、转换成本、升级产品质量(或功能)的提高对升级定价及其竞争策略的影响.主要成果包括以下几个方面(1)在消费者静态预期的条件下,网络规模大的厂商总是偏好不兼容,网络规模小的厂商偏好全兼容.(2)分析了影响版本升级价格、竞争性价格和全价的相关因素.(3)解释了转换成本和实施竞争性升级的关系.(4)分析了厂商夺取竞争对手厂商客户的条件以及争夺新客户的竞争策略.对厂商的竞争性升级定价具有重要的理论指导意义.     

角式调节阀两相流模拟与结构改进

基于2003—2015年我国26个省、自治区的面板数据,重点考察了四万亿投资刺激计划背景下,各地区的财政货币政策对粮食价格波动的冲击效应及其差异。研究发现：中国粮食价格上涨除了受到生产成本因素驱动以外,还主要受到宽松的货币政策所引致的地方流动性过剩的影响,地方财政货币政策对粮食价格波动的冲击效应在四万亿投资实施前后存在明显的差异;四万亿刺激计划实施后,各地区积极的财政政策和宽松的货币政策才是新一轮粮食价格波动的主因,粮食类农产品因为自身的敏感和脆弱性,受到了财政货币政策引致的流动性泛滥所带来的最直接伤害;应注重财政货币政策的多重目标分解、梳理及协调配合,处理好“稳增长、控物价、调结构、惠民生、防风险”之间复杂多变的关系,寻求一个有效的“平衡点”。     

A股价格波动真的非平稳？ ——大数据背景下个股数据的全样本实证

传统研究对股票市场平稳性分析中大多采用市场指数抽样方式,分析方法和数据采样的差异一定程度上解析了现有研究结论中的不一致性。从市场指数构建原理入手可探究抽样分析的局限,作为系列个股的加权值,市场指数无法精确刻画市场所有个股的波动情况。实证时采用A股市场所有个股数据开展全样本分析,这更符合大数据分析理念,统计出个股分析结果继而对A股市场波动进行判定将更加系统和可靠。在不考虑结构突变的情形下,分别计算出ADF检验、KPSS检验和PP检验三种方法的结果;全样本分析结果表明A股市场年度股价数据更多地呈现出平稳性特点,而且,个股数据检验结果与市场指数检验结果存在显著差异。     

农产品价格波动中的金融化因素分析——以大豆、食糖为例

基于2007年1月至2016年12月的相关月度数据,以大豆和食糖为例,通过ARDL模型分别从长期和短期对影响国内农产品现货价格的金融化因素进行了系统测算。结果表明,通货膨胀因素、国内期货价格、货币供应量和国际现货价格是影响国内大豆现货价格的主要金融化因素;国内期货价格、通货膨胀因素和国际现货价格是影响国内食糖现货价格的主要金融化因素;汇率和能源价格对二者的影响均不明显。最后,从改善宏观经济环境、规范期货市场发展、健全农产品进口风险防控体系、关注品种间差异等方面提出了应对农产品金融化的对策建议。