A gradient boosting decision tree approach for insider trading identification: An empirical model evaluation of China stock market

Insider trading is a kind of criminal behavior in stock market by using nonpublic information. In recent years, it has become the major illegal activity in China’s stock market. In this study, a combination approach of GBDT (Gradient Boosting Decision Tree) and DE (Differential Evolution) is proposed to identify insider trading activities by using data of relevant indicators. First, insider trading samples occurred from year 2007 to 2017 and corresponding non-insider trading samples are collected. Next, the proposed method is trained by the GBDT, and initial parameters of the GBDT are optimized by the DE. Finally, out-of-samples are classified by the trained GBDT–DE model and its performances are evaluated. The experiment results show that our proposed method performed the best for insider trading identification under time window length of ninety days, indicating the relevant indicators under 90-days time window length are relatively more useful. Additionally, under all three time window lengths, relative importance result shows that several indicators are consistently crucial for insider trading identification. Furthermore, the proposed approach significantly outperforms other benchmark methods, demonstrating that it could be applied as an intelligent system to improve identification accuracy and efficiency for insider trading regulation in China stock market.     

A formal description of open distributed processing (ODP) trading based on guidelines for the definition of managed objects (GDMO)

New requirements of growing computer networks and information systems have an influence on extended client/server models with increased functionality. This forms the basis for service management in distributed systems which is realized by a service trading concept. This paper studies the requirements derived from the Open Distributed Processing (ODP) Reference Model in order to consider an open service market. Furthermore, it examines management possibilities for describing the service trading scenario. Because of similar architectures and properties ODP services, service offers, types, exporters and traders are mapped onto management components and modeled as managed objects. Therefore, the Guidelines for the Definition of Managed Objects (GDMO) are used. The final concept allows a precise and unambiguous study of the service trading scenario and provides means for exporting and importing of service offers in a distributed environment.     

MRC技术在全球油田开发中的应用

MRC技术被国际石油专家们确立为21世纪初最具发展潜力的8项钻井新技术之一,代表了21世纪石油技术的发展的方向。MRC除具有水平井的常规优势外,其成本比单个水平井低,是从1个主井眼中钻成2个或多个分支井眼,从而钻遇多个不同空间位置的产层、增大储层钻穿几率和有效面积、提供多种泄油模式以及控制底水锥进和延缓边水推进速度,进而提高单井油气产量。发达国家MRC的技术日渐成熟,已成为油气田开发的一种重要技术在世界范围内广泛应用,必将为全球油气资源的高水平、高效益开发和可持续发展作出积极贡献。     

G104-5P42分支水平井钻井液工艺技术

G104-5P42井是在高尚堡G104-5区块构造较高部位部署的一口重点开发井，也是冀东油田第一口鱼骨型水平分支井，钻探目的是开发高浅北区Ng12油层，挖掘高浅北区井间剩余油潜力。该井主井眼斜深为2388m，水平位移为736．42m，水平段长243m，第一分支斜深为2342m，水平段长120．25m，水平位移为682．14m，第二分支斜深为2421m，水平段长117m，水平位移为761．73m。三开选用无固相甲酸盐聚合醇钻井液，在钻进油气层前加入GN-YBJ-I保护剂。应用结果表明，无固相甲酸盐聚合醇钻井液具有好的防塌能力和润滑减阻效果，性能稳定、黏度、切力较低，有利于减少环空压力损耗；在油气层段密度控制在1．08g／cm^3以内，为近年来同区块密度使用最低井，减小了有害固相及滤液对储层的伤害密度，经测试该井获高产油流；该井全井平均机械钻速为15．09m／h，钻井周期比原设计提前15d。该体系的配制及维护成本较高，适宜在目的层井段使用，但可回收再利用。     

An evaluation of possible EU air transport emissions trading scheme allocation methods

The European Commission has been requested by member states to study the incorporation of air transport into their existing emissions trading scheme (ETS). Only CO₂ is to be included, at least initially.     

实时可视决策系统在渤海湾旅大油田开发中的应用

实时可视决策系统可以将接收到的现场数据实时传输到陆地，井眼轨迹和随钻测井资料可实时在三维地质油藏模型中显示，供钻完井和地质油藏专家综合分析、判断并及时下达指令指导现场施工。旅大油田运用实时可视决策系统成功钻成了6口水平井和4口水平分支井，实现了不钻领眼、井眼轨迹在最佳油层内成功着陆，并使水平井段尽可能沿着油层最佳位置钻进。例如在LD10—1-A25m水平分支井段的钻井过程中，利用实时可视决策系统，控制水平井眼轨迹在油层最佳位置钻进，获得了日产810M^3。的高产油气流。     

考虑排污权交易的有限理性企业博弈模型研究

在有限理性基础上建立寡头垄断博弈模型,将其引入到排污权市场中,同时考虑了生产成本、污染治理成本、排污权交易价格的影响,使该模型更符合实际。将不同理性层次,不同结构的非线性成本函数,不完全信息等因素引入到博弈模型中,对改进后的模型的演化过程进行分析,找出博弈均衡点,并分析其稳定性。由于具有有限理性的双寡头Cournot博弈模型会产生丰富的动力学行为,因此对其进行数据模拟后并对混沌现象进行分析。在此基础上,运用延迟反馈控制法对寡头垄断博弈模型的混沌控制进行了解析分析,结果表明选择合适的控制因子可使模型稳定在Nash均衡。     

考虑需求侧管理和碳交易的电-气互联网络分散式低碳经济调度

在能源互联网和低碳背景下,提出一种考虑需求侧管理(demand side management, DSM)和碳交易的电-气互联网络分散式低碳经济调度模型。首先,根据碳交易市场的实际情况建立阶梯型碳交易机制,并利用电转气(power to gas, P2G)的低碳特性,得到P2G参与碳交易市场的激励机制;其次,由现有DSM的机理与实现方式,在负荷侧考虑不同的DSM来最大化地协调网络的低碳性与经济性;然后,根据所建模型的非凸特性,对气网潮流进行二阶锥松弛且采用连续锥规划算法对松弛间隙进行检验,逐步缩小气潮流的仿真误差,保证松弛的严格性。为了满足不同决策主体的分散自治权与信息私密性,在上述基础上建立分散式优化模型并引入基于嵌套连续锥规划的同步交替方向乘子法(synchronous-alternating direction method of multipliers, S-ADMM)进行求解;最后,通过算例仿真对不同场景下网络的调度结果及不同的调度策略下的运行结果进行比较分析。结果表明,在阶梯型碳交易机制下,虽然总碳交易成本增加了0.02%,但碳排量、运行成本分别减少了4.53%和3.74%;DSM参与到所提模型中使碳排量、弃风量分别降低了9.87%和75.4%,进而有效地提升了电-气互联网络的低碳经济性。     

基于配额制的自备电厂参与新能源消纳日前交易模式

国内风电和光伏等新能源发电迅速发展,而部分地区本地消纳和电网外送能力均有限,当地自备电厂未充分发挥调峰作用,出现日趋严重的弃风弃光现象,因此难以完成配额制目标。为利用市场手段充分调动当地自备电厂参与新能源消纳,促进新能源配额制目标的完成,同时避免因强行完成指标导致的社会整体消纳成本升高的问题,提出了一种基于竞价摘牌的新能源日前交易模式。通过具有引导效应的市场化手段,调动具备自备电厂用户的主动消纳意愿,进而提升配额制目标完成度,并降低整体消纳成本。最后,以新疆地区算例为例,分析验证了所提交易模式在提升配额制目标完成度及在尽量降低社会整体消纳成本方面的价值,为新疆等类似地区电力市场建设提供了一种新的思路。     

基于区块链的分布式光伏就地消纳交易模式研究

目前配电网中分布式光伏发电渗透率越来越高,利用区块链技术的去中心化、难篡改等特点,有助于分布式发电就地或就近消纳,提高配电网运行的经济性。提出了一种基于区块链的光伏就地消纳交易模式,建立了光伏发电用户和分布式光伏聚合商的效益函数,运用Stackelberg博弈模型确定内部电价,通过边缘计算制定最优用电计划,设计了基于信誉值的就地消纳交易机制,对就地消纳程度低的用户进行惩罚,鼓励用户通过可时移负荷消纳光伏出力。配电网仿真结果表明,在采用区块链的交易模式下,配电网的就地消纳情况得到改善,用户的综合效益得到提升。