CnOpenData 股票日行情表

时间区间

截至2023.10


字段展示

股票日行情表-英文字段股票日行情表表-中文字段
ID自增ID
SECURITY_ID证券内部ID
TICKER_SYMBOL证券代码
EXCHANGE_CD交易市场代码
TRADE_DATE交易日
PRE_CLOSE_PRICE昨收盘
ACT_PRE_CLOSE_PRICE实际昨收盘
OPEN_PRICE今开盘
HIGHEST_PRICE最高价
LOWEST_PRICE最低价
CLOSE_PRICE今收盘
TURNOVER_VOL成交量
TURNOVER_VALUE成交金额
DEAL_AMOUNT成交笔数
PE市盈率TTM
PE1动态市盈率
PB流通市值
NEG_MARKET_VALUE总市值
MARKET_VALUE涨跌幅
CHG_PCT日换手率
TURNOVER_RATE市净率
UPDATE_TIME更新时间

样本数据

IDSECURITY_IDTICKER_SYMBOLEXCHANGE_CDTRADE_DATEPRE_CLOSE_PRICEACT_PRE_CLOSE_PRICEOPEN_PRICEHIGHEST_PRICELOWEST_PRICECLOSE_PRICETURNOVER_VOLTURNOVER_VALUEDEAL_AMOUNTPEPE1PBNEG_MARKET_VALUEMARKET_VALUECHG_PCTTURNOVER_RATEUPDATE_TIME
自增ID证券内部ID证券代码交易市场代码交易日昨收盘实际昨收盘今开盘最高价最低价今收盘成交量成交金额成交笔数市盈率TTM动态市盈率流通市值总市值涨跌幅日换手率市净率更新时间
15726798240000600XSHE2023-10-095.7005.7005.7005.7905.6805.7601432015682400596.0202143441.890761.22251.04806278647104.000010319768064.00000.01050.01312023-10-09 15:05:03.120
15726799241000601XSHE2023-10-094.2204.2204.2004.2904.1904.240697396429630067.64013189-27.361954.67510.99864578610216.00004581538784.00000.00470.00652023-10-09 15:05:03.120
15726800243000603XSHE2023-10-0914.41014.41014.25014.67013.86014.49011226199159606154.1201344531.033781.74313.28028531852553.00009997655157.00000.00560.01912023-10-09 15:05:03.120
15726801244000605XSHE2023-10-096.1406.1406.1706.1805.9005.930676514040535405.60012027175.521887.03510.98862002227141.00002091265498.0000-0.03420.02002023-10-09 15:05:03.123
15726802246000607XSHE2023-10-094.7404.7404.7404.7404.5004.5901499556968742787.500863446.964541.39352.87414061772702.00004671235656.0000-0.03160.01692023-10-09 15:05:03.123
15726803247000608XSHE2023-10-092.8902.8902.8702.9102.7602.7801222660034265933.00014479-5.5893-47.23190.78662084758974.00002084758974.0000-0.03810.01632023-10-09 15:05:03.123
15726804248000609XSHE2023-10-095.4505.4505.4505.4505.2105.2701527320080479525.00014714-5.6494-15.87653.01661539311665.00001577129185.0000-0.03300.05232023-10-09 15:05:03.123
15726805249000610XSHE2023-10-0916.19016.19015.81015.82015.00015.06017531950264824364.20024806-21.0746-35.47125.93663546387534.00003565423374.0000-0.06980.07452023-10-09 15:05:03.123
15726806251000612XSHE2023-10-095.1405.1405.1505.1805.1105.140488860025137089.0009506117.815323.22641.14606123899314.00006127904916.00000.00000.00412023-10-09 15:05:03.123
15726807254000615XSHE2023-10-094.2804.2804.2604.4904.2304.4902210470297210462.8806936-2.2154-41.5841-16.91223420348198.00003425778853.00000.04910.02902023-10-09 15:05:03.123
15726808256000617XSHE2023-10-096.6206.6206.6106.6106.4306.50056583231367184764.0102715715.479510.51640.831382173514150.000082173514150.0000-0.01810.00452023-10-09 15:05:03.123
15726809258000619XSHE2023-10-096.3906.3906.3906.4106.0906.130722320044489174.00013970-25.3760-398.04770.99782206800000.00002206800000.0000-0.04070.02012023-10-09 15:05:03.123
15726810259000620XSHE2023-10-091.6401.6401.6301.6401.5801.5901886250030267023.8002607-0.8274-1.2341-1.83313015632478.00003015737736.0000-0.03050.00992023-10-09 15:05:03.123
15726811260000622XSHE2023-10-094.5204.5204.7404.7404.4904.61068282377314364110.43032244-270.2028-530.680310.18521960291860.00001960291860.00000.01990.16062023-10-09 15:05:03.123
15726812261000623XSHE2023-10-0917.26017.26017.16017.24016.88017.16011444476195226754.710228078.49619.38640.741719893778476.000019958885232.0000-0.00580.00992023-10-09 15:05:03.123
15726813262000625XSHE2023-10-0913.44013.44014.00014.09013.60013.9302344626593260476788.17018589714.40269.02762.0335106538491297.0000138176169390.00000.03650.03072023-10-09 15:05:03.123
15726814263200625XSHE2023-10-093.6103.6103.6103.6603.6103.650356235912987371.51015863.77382.36550.53285991894020.000036205528950.00000.01110.00222023-10-09 15:05:03.123
15726815264000626XSHE2023-10-097.1207.1207.1007.1106.8806.900436200030330832.000814166.91602356.42211.15643463657860.00003511689450.0000-0.03090.00872023-10-09 15:05:03.123
15726816265000627XSHE2023-10-093.1203.1203.1203.1203.0503.0903012691492693989.98021083-170.5994-40.73320.730114067237978.000015266544228.0000-0.00960.00662023-10-09 15:05:03.123
15726817266000628XSHE2023-10-0916.33016.3300.0000.0000.00016.33000.000025.651130.82493.13913136568420.00005752732400.00000.00000.00002023-10-09 15:05:03.123
15726818267000629XSHE2023-10-093.6803.6803.6803.6803.5803.60043668861157848551.9401747038.281027.74322.855630922547760.000033462119520.0000-0.02170.00512023-10-09 15:05:03.123
15726819268000630XSHE2023-10-093.1903.1903.1903.2303.1403.220103386548330077908.7004458214.743514.27421.548933894950362.000040787772200.00000.00940.00982023-10-09 15:05:03.127
15726820269000631XSHE2023-10-092.7902.7902.8002.8102.7502.750813314222514631.500975150.003759.93891.17506587017525.00006587017525.0000-0.01430.00342023-10-09 15:05:03.127
15726821270000632XSHE2023-10-094.2204.2204.2204.2904.1804.2101190870050257045.00014164119.636784.21161.35611959677536.00001959837516.0000-0.00240.02562023-10-09 15:05:03.127
15726822271000633XSHE2023-10-097.6107.6107.5507.7107.3707.68022984479173415702.900157601262.2237518.857016.74382957594112.00002957616384.00000.00920.05972023-10-09 15:05:03.127
15726823272000635XSHE2023-10-098.5908.5908.7608.7608.4808.500211303118047743.5007088-3.9884-4.33491.31042576244600.00002583735650.0000-0.01050.00702023-10-09 15:05:03.127
15726824273000636XSHE2023-10-0914.69014.69014.63014.86014.54014.7806814001100208699.64015030388.4103100.51201.428315939888582.000017100655096.00000.00610.00632023-10-09 15:05:03.127
15726825274000637XSHE2023-10-094.1604.1604.2004.3504.0804.3101804060776058187.6806822-11.4839-21.73182.70601586141633.00002240662974.00000.03610.04902023-10-09 15:05:03.127
15726826275000638XSHE2023-10-096.2206.2206.2306.3306.0506.060766540046839216.0008786769.9601-101.454010.85221871174076.00001878694536.0000-0.02570.02482023-10-09 15:05:03.127
15726827276000639XSHE2023-10-094.2104.2104.2104.2104.1304.160502159620919705.2409426-6.8534-43.79961.34604490415488.00004490420896.0000-0.01190.00472023-10-09 15:05:03.127
15726828277000650XSHE2023-10-097.1507.1507.1307.1406.9807.04034755097244963101.2902956215.618313.82081.69429449925760.00009855565632.0000-0.01540.02592023-10-09 15:05:03.127
15726829278000651XSHE2023-10-0936.30036.30036.20036.77035.84036.60024756794901912870.600388858.01568.13171.9573204672280080.0000206109448620.00000.00830.00442023-10-09 15:05:03.127
15726797239000599XSHE2023-10-094.3704.3704.3804.4804.3704.430990130043808535.00014727-8.3393-13.77071.65283618094851.00003618241927.00000.01370.01212023-10-09 15:05:03.120
15726796238000598XSHE2023-10-095.3605.3605.3505.3805.3105.310915130048758842.000135809.74809.35861.036215763140153.000015853357053.0000-0.00930.00312023-10-09 15:05:03.120
15726795237000597XSHE2023-10-095.2505.2505.2505.2805.1905.240769952940255865.9201236620.180027.85981.62107199918772.00007515817412.0000-0.00190.00562023-10-09 15:05:03.120
15726794236200596XSHE2023-10-09131.000131.000131.000131.830128.880128.88016955922012808.770122617.015312.25523.455615465600000.000068125968000.0000-0.01620.00142023-10-09 15:05:03.120
15726793235000596XSHE2023-10-09271.800271.800271.850274.690267.040272.2301282081346963351.800813635.941125.88637.2992111233178000.0000143900778000.00000.00160.00312023-10-09 15:05:03.120
15726792234000595XSHE2023-10-095.3705.3705.3705.3905.3405.390591570231796544.7402812-65.1546-99.29519.66056134993403.00006137357996.00000.00370.00522023-10-09 15:05:03.120
15726791232000593XSHE2023-10-097.2807.2807.3007.4607.2507.310969853770899517.1001709840.736737.89352.33302620315553.00002621592610.00000.00410.02712023-10-09 15:05:03.120
15726790231000592XSHE2023-10-092.4702.4702.4702.4802.4302.45055269926135466443.11016638-21.5028226.16101.99024689145405.00004732863205.0000-0.00810.02892023-10-09 15:05:03.120

数据更新频率

年度更新,特殊需求另行联系

内容概要:本文围绕EKF SLAM(扩展卡尔曼滤波同步定位与地图构建)的性能展开多项对比实验研究,重点分析在稀疏与稠密landmark环境下、预测与更新步骤同时进行与非同时进行的情况下的系统性能差异,并进一步探讨EKF SLAM在有色噪声干扰下的鲁棒性表现。实验考虑了不确定性因素的影响,旨在评估不同条件下算法的定位精度与地图构建质量,为实际应用中EKF SLAM的优化提供依据。文档还提及多智能体系统在遭受DoS攻击下的弹性控制研究,但核心内容聚焦于SLAM算法的性能测试与分析。; 适合人群:具备一定机器人学、状态估计或自动驾驶基础知识的科研人员及工程技术人员,尤其是从事SLAM算法研究或应用开发的硕士、博士研究生和相关领域研发人员。; 使用场景及目标:①用于比较EKF SLAM在不同landmark密度下的性能表现;②分析预测与更新机制同步与否对滤波器稳定性与精度的影响;③评估系统在有色噪声等非理想观测条件下的适应能力,提升实际部署中的可靠性。; 阅读建议:建议结合MATLAB仿真代码进行实验复现,重点关注状态协方差传播、观测更新频率与噪声模型设置等关键环节,深入理解EKF SLAM在复杂环境下的行为特性。稀疏 landmark 与稠密 landmark 下 EKF SLAM 性能对比实验,预测更新同时进行与非同时进行对比 EKF SLAM 性能对比实验,EKF SLAM 在有色噪声下性能实验
内容概要:本文围绕“基于主从博弈的售电商多元零售套餐设计与多级市场购电策略”展开,结合Matlab代码实现,提出了一种适用于电力市场化环境下的售电商优化决策模型。该模型采用主从博弈(Stackelberg Game)理论构建售电商与用户之间的互动关系,售电商作为领导者制定电价套餐策略,用户作为跟随者响应电价并调整用电行为。同时,模型综合考虑售电商在多级电力市场(如前市场、实时市场)中的【顶级EI复现】基于主从博弈的售电商多元零售套餐设计与多级市场购电策略(Matlab代码实现)购电组合优化,兼顾成本最小化与收益最大化,并引入不确定性因素(如负荷波动、可再生能源出力变化)进行鲁棒或随机优化处理。文中提供了完整的Matlab仿真代码,涵盖博弈建模、优化求解(可能结合YALMIP+CPLEX/Gurobi等工具)、结果可视化等环节,具有较强的可复现性和工程应用价值。; 适合人群:具备一定电力系统基础知识、博弈论初步认知和Matlab编程能力的研究生、科研人员及电力市场从业人员,尤其适合从事电力市场运营、需求响应、售电策略研究的相关人员。; 使用场景及目标:① 掌握主从博弈在电力市场中的建模方法;② 学习售电商如何设计差异化零售套餐以引导用户用电行为;③ 实现多级市场购电成本与风险的协同优化;④ 借助Matlab代码快速复现顶级EI期刊论文成果,支撑科研项目或实际系统开发。; 阅读建议:建议读者结合提供的网盘资源下载完整代码与案例数据,按照文档目录顺序逐步学习,重点关注博弈模型的数学表达与Matlab实现逻辑,同时尝试对目标函数或约束条件进行扩展改进,以深化理解并提升科研创新能力。
内容概要:本文介绍了基于粒子群优化算法(PSO)的p-Hub选址优化问基于粒子群优化算法的p-Hub选址优化(Matlab代码实现)题的Matlab代码实现,旨在解决物流与交通网络中枢纽节点的最优选址问题。通过构建数学模型,结合粒子群算法的全局寻优能力,优化枢纽位置及分配策略,提升网络传输效率并降低运营成本。文中详细阐述了算法的设计思路、实现步骤以及关键参数设置,并提供了完整的Matlab仿真代码,便于读者复现和进一步改进。该方法适用于复杂的组合优化问题,尤其在大规模网络选址中展现出良好的收敛性和实用性。; 适合人群:具备一定Matlab编程基础,从事物流优化、智能算法研究或交通运输系统设计的研究生、科研人员及工程技术人员;熟悉优化算法基本原理并对实际应用场景感兴趣的从业者。; 使用场景及目标:①应用于物流中心、航空枢纽、快递分拣中心等p-Hub选址问题;②帮助理解粒子群算法在离散优化问题中的编码与迭代机制;③为复杂网络优化提供可扩展的算法框架,支持进一步融合约束条件或改进算法性能。; 阅读建议:建议读者结合文中提供的Matlab代码逐段调试运行,理解算法流程与模型构建逻辑,重点关注粒子编码方式、适应度函数设计及约束处理策略。可尝试替换数据集或引入其他智能算法进行对比实验,以深化对优化效果和算法差异的理解。
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