美股详情

本页面由Tiger Fintech (Singapore) Pte. Ltd.提供服务

拉夫劳伦

297.91

-3.8100-1.26%

成交量：18.54万

成交额：5,558.21万

市值：180.45亿

市盈率：25.66

高：302.50

开：300.00

低：297.74

收：301.72

数据加载中...

总览公司新闻公告

DPO与GRPO谁更胜一筹？港中文、北大等发布首个系统性对比研究

对话特斯联邵岭：空间智能是构建世界模型的必要前提

MiniMax深夜开源！首个推理模型，4560亿参数、百万上下文、价格低至0.8元

SFT+RL双管齐下：ReasonGen-R1如何破解文生图“指令不遵”难题？

通义实验室最新成果WebDancer：自主智能Deep Research的新时代

新闻摘要-华尔街日报》--6 月 11 日

新闻摘要-华尔街日报》--6 月 11 日

新“SOTA”推理模型避战Qwen和R1？欧版OpenAI被喷麻了

媒体-Verizon、Ralph Lauren 等公司同意恢复在 X 上购买广告 - 华尔街日报

效率飙涨177%！清华、蚂蚁联合开源全异步RL新成果，8B/14B模型斩获同尺寸SOTA

训练步数翻倍=推理能力质变，小模型突破推理极限

10步优化超越强化学习，仅需1条未标注数据！后训练强势破局

首个全异步强化学习训练系统,SOTA推理大模型RL训练提速2.77倍

拉夫劳伦考虑发行债券融资5亿美元，股价一度跌1.6%

Claude 4核心成员：2027年，AI将自动化几乎所有白领工作

技术演进路径渐明多方加快布局养老机器人

中国经营网

Anthropic核心成员揭秘Claude 4：2027年，AI模型将有能力自动化几乎所有白领工作

华尔街见闻

沃尔玛、拉夫劳伦、美泰……宣布涨价的美国品牌越来越多了

华尔街见闻

拉夫劳伦2025财年实现净利润7.43亿美元，同比增加15.02%

Claude会拿用户的隐私威胁人类了？它正在被训练成一个“道德警察”

{"basename":"/hans","ssrTDKData":{"titleTemplate":"%s - 老虎证券","title":"老虎证券全球投资理财平台| 一站式投资美股新股港股A股","description":"老虎证券助您一站式投资美股，新股，港股，A股等全球金融理财产品。新加坡华人最信赖的在线投资平台，现在加入即享低费用，24/5 无时差炒美股投资理财！","keywords":"老虎证券,老虎证券开户,老虎券商,老虎证券官网,老虎证券app,tigertrade老虎证券,股票,炒股,新加坡股票交易平台,投资,投资理财","social":{"ogDescription":"老虎证券助您一站式投资美股，新股，港股，A股等全球金融理财产品。新加坡华人最信赖的在线投资平台，现在加入即享低费用，24/5 无时差炒美股投资理财！","ogImage":"https://c1.itigergrowtha.com/portal5/static/media/og-logo.be62fbe1.png","ogUrl":"https://www-web.itiger.com/hans/stock/RL/news?page=3"},"companyName":"老虎证券"},"pageData":{"isMobile":false,"isTiger":false,"isTTM":true,"region":"SGP","license":"TBSG","edition":"fundamental","symbol":"RL","isAnalysisPage":false},"__swrFallback__":{"@#url:\"https://hq.skytigris.cn/stock_info/detail/global\",params:#delay:false,,method:\"POST\",data:#items:@#symbol:\"RL\",,,,,undefined,":{"symbol":"RL","market":"US","secType":"STK","nameCN":"拉夫劳伦","latestPrice":297.91,"timestamp":1753807272233,"preClose":301.72,"halted":0,"volume":185388,"delay":0,"floatShares":38074116,"shares":60572991,"eps":11.61,"marketStatus":"交易中","change":-3.81,"latestTime":"07-29 12:41:20 EDT","open":300.0001,"high":302.495,"low":297.74,"amount":55582097.658360004,"amplitude":0.01576,"askPrice":298.18,"askSize":2,"bidPrice":297.7,"bidSize":109,"shortable":3,"etf":0,"ttmEps":11.61,"tradingStatus":2,"nextMarketStatus":{"tag":"盘后交易","tradingStatus":3,"beginTime":1753819200000},"marketStatusCode":2,"adr":0,"adrRate":0,"listingDate":866088000000,"exchange":"NYSE","adjPreClose":301.72,"dividendRate":0.011077,"preHourTrading":{"tag":"盘前","latestPrice":301.72,"preClose":301.72,"latestTime":"09:29 EDT","volume":33174,"amount":10009299.75228,"timestamp":1753795758996},"postHourTrading":{"tag":"盘后","latestPrice":301.72,"preClose":301.72,"latestTime":"19:53 EDT","volume":13032,"amount":3932045.41,"timestamp":1753746810669},"volumeRatio":0.628312,"optionData":{"bulkOrders":[{"symbol":"RL","call":false,"expireDate":1755230400000,"strike":"290.0","timestamp":1753803717419,"price":9,"volume":2249,"amount":2024100,"type":"-"}]},"impliedVol":0.4378,"impliedVolPercentile":0.668},"@#url:\"https://hq.skytigris.cn/stock_info/fundamental/all\",params:#delay:false,,method:\"POST\",data:#items:@#symbol:\"RL\",,,,,undefined,":{"symbol":"RL","floatShares":38074116,"roa":"8.46%","roe":"29.49%","lyrEps":11.867412,"volumeRatio":0.628312,"shares":60572991,"dividePrice":3.3,"high":302.495,"amplitude":0.01576,"preClose":301.72,"low":297.74,"week52Low":155.96,"pbRate":"6.97","psRate":"2.55","week52High":303.64,"institutionHeld":0.7653,"latestPrice":297.91,"committee":0.963964,"eps":11.61,"divideRate":0.011077,"volume":185388,"delay":0,"ttmEps":11.61,"open":300.0001,"prevYearClose":230.98,"prevWeekClose":298.23,"prevMonthClose":274.28,"prevQuarterClose":274.28,"fiveDayClose":288.31,"twentyDayClose":274.28,"sixtyDayClose":224.51,"earningDate":1754496000000,"earningTime":"盘前"},"$inf$@#url:\"https://stock-news.skytigris.cn/v2/news/list\",params:#symbols:\"RL\",pageSize:20,pageCount:3,lang_content:\"cn\",edition:\"fundamental\",,,undefined,":[{"items":[{"id":"2544166352","title":"DPO与GRPO谁更胜一筹？港中文、北大等发布首个系统性对比研究","url":"https://stock-news.laohu8.com/highlight/detail?id=2544166352","media":"市场资讯","labels":[],"top":-1,"itemType":null,"share":"https://ttm.financial/m/news/2544166352?lang=zh_cn&edition=fundamental","pubTime":"2025-06-19 18:33","pubTimestamp":1750329180,"startTime":"0","endTime":"0","summary":"近日，一篇来自香港中文大学、北京大学及上海人工智能实验室的最新研究给出了答案。图 1: GRPO 与 DPO 在自回归图像生成中的研究总览，涵盖了域内域外性能对比、不同奖励模型的影响以及扩展策略的效果。在DPO 与 GRPO 的对比中，研究者确保了两者在计算成本上的可比性。例如，DPO 中每个 prompt 生成的图像数量与 GRPO 中的组大小对齐，并使用相同的奖励模型。总结与展望这项研究为我们提供了一幅关于 DPO 和 GRPO 在自回归图像生成领域应用的清晰图景。","market":"other","thumbnail":null,"type":0,"news_type":0,"thumbnails":[],"rights":null,"property":[],"language":"zh","translate_title":"","themeId":null,"theme_name":"","theme_type":"","isJumpTheme":false,"source_url":"https://finance.sina.com.cn/stock/t/2025-06-19/doc-infarhch4870755.shtml","is_publish_highlight":false,"source_rank":0,"column":"","sentiment":"0","news_top_title":null,"news_tag":"","news_rank":0,"length":0,"strategy_id":0,"source":"sina","symbols":["RL","BK4588","LU0006061336.USD","BK4585","BK4202"],"gpt_icon":0},{"id":"2544910240","title":"对话特斯联邵岭：空间智能是构建世界模型的必要前提","url":"https://stock-news.laohu8.com/highlight/detail?id=2544910240","media":"市场资讯","labels":[],"top":-1,"itemType":null,"share":"https://ttm.financial/m/news/2544910240?lang=zh_cn&edition=fundamental","pubTime":"2025-06-18 09:37","pubTimestamp":1750210620,"startTime":"0","endTime":"0","summary":"空间智能和World Model并不是同一概念，但它们之间是紧密相关的。空间智能提供的强大的空间感知和理解能力，是构建准确、全面的World Model的必要前提。特斯联目前采用空间数据知识、领域模型工具，AI智能体以及空间感知模型技术相融合的方案，利用构建的知识库和系统工具，增强模型的空间感知能力。","market":"other","thumbnail":null,"type":0,"news_type":0,"thumbnails":[],"rights":null,"property":[],"language":"zh","translate_title":"","themeId":null,"theme_name":"","theme_type":"","isJumpTheme":false,"source_url":"https://finance.sina.com.cn/stock/t/2025-06-18/doc-infamzsp5910679.shtml","is_publish_highlight":false,"source_rank":0,"column":"","sentiment":"0","news_top_title":null,"news_tag":"","news_rank":0,"length":0,"strategy_id":0,"source":"sina","symbols":["BK4585","BK4202","BK4588","LU0006061336.USD","RL"],"gpt_icon":0},{"id":"2544931382","title":"MiniMax深夜开源！首个推理模型，4560亿参数、百万上下文、价格低至0.8元","url":"https://stock-news.laohu8.com/highlight/detail?id=2544931382","media":"智东西","labels":[],"top":-1,"itemType":null,"share":"https://ttm.financial/m/news/2544931382?lang=zh_cn&edition=fundamental","pubTime":"2025-06-17 11:40","pubTimestamp":1750131644,"startTime":"0","endTime":"0","summary":"作者 | 程茜编辑 | 心缘智东西6月17日报道，今日凌晨，“大模型六小虎”之一MiniMax发布全球首个开源大规模混合架构的推理模型MiniMax-M1，并官宣了为期五天的连更计划。此外，研究人员训练了两个版本的MiniMax-M1模型，其思考预算分别为40K和80K。M1在MiniMax APP和Web上支持不限量免费使用。在这样的背景下，作为MiniMax推出的首个推理模型，MiniMax-M1正是其面对这一行业发展趋势在算法创新上的探索。","market":"hk","thumbnail":null,"type":0,"news_type":0,"thumbnails":[],"rights":null,"property":[],"language":"zh","translate_title":"","themeId":null,"theme_name":"","theme_type":"","isJumpTheme":false,"source_url":"https://tech.ifeng.com/c/8kFxRzQknwS","is_publish_highlight":false,"source_rank":0,"column":"","sentiment":"0","news_top_title":null,"news_tag":"","news_rank":0,"length":0,"strategy_id":0,"source":"fenghuang_stock","symbols":["LU0006061336.USD","RL","BK4585","BK4588","BK4202"],"gpt_icon":0},{"id":"2543678781","title":"SFT+RL双管齐下：ReasonGen-R1如何破解文生图“指令不遵”难题？","url":"https://stock-news.laohu8.com/highlight/detail?id=2543678781","media":"市场资讯","labels":[],"top":-1,"itemType":null,"share":"https://ttm.financial/m/news/2543678781?lang=zh_cn&edition=fundamental","pubTime":"2025-06-16 17:22","pubTimestamp":1750065720,"startTime":"0","endTime":"0","summary":"ReasonGen-R1 使得自回归图像生成模型可以端到端地在输出图片之前先进行文本“思考”，大幅提升了基座模型的语义遵循能力，并在多个语义指标上取得突破。目前，ReasonGen-R1 已全面开源。方法概览ReasonGen-R1 的训练包括两个核心阶段：监督微调阶段以及强化学习阶段。","market":"hk","thumbnail":null,"type":0,"news_type":0,"thumbnails":[],"rights":null,"property":[],"language":"zh","translate_title":"","themeId":null,"theme_name":"","theme_type":"","isJumpTheme":false,"source_url":"https://finance.sina.com.cn/stock/t/2025-06-16/doc-infahksh9599543.shtml","is_publish_highlight":false,"source_rank":0,"column":"","sentiment":"0","news_top_title":null,"news_tag":"","news_rank":0,"length":0,"strategy_id":0,"source":"sina","symbols":["BK4202","LU0006061336.USD","RL","BK4588","BK4585","SFT","BK4214"],"gpt_icon":0},{"id":"2542601115","title":"通义实验室最新成果WebDancer：自主智能Deep Research的新时代","url":"https://stock-news.laohu8.com/highlight/detail?id=2542601115","media":"市场资讯","labels":[],"top":-1,"itemType":null,"share":"https://ttm.financial/m/news/2542601115?lang=zh_cn&edition=fundamental","pubTime":"2025-06-12 15:06","pubTimestamp":1749711960,"startTime":"0","endTime":"0","summary":"在这种背景下，WebDancer 的出现，走出了一条复现 Deep Research 类智能体的可行路径。WebDancer 采用了多阶段的数据过滤策略，确保了数据的高质量。WebDancer 通过动态采样机制，确保了数据的高效利用。实验结果显示，WebDancer 在这些基准测试中取得了显著的成绩，超越了 GPT-4o 等强大的基线模型。","market":"fut","thumbnail":null,"type":0,"news_type":0,"thumbnails":[],"rights":null,"property":[],"language":"zh","translate_title":"","themeId":null,"theme_name":"","theme_type":"","isJumpTheme":false,"source_url":"https://finance.sina.com.cn/stock/t/2025-06-12/doc-inezvcxy3585627.shtml","is_publish_highlight":false,"source_rank":0,"column":"","sentiment":"0","news_top_title":null,"news_tag":"","news_rank":0,"length":0,"strategy_id":0,"source":"sina","symbols":["BK4585","BK4588","SFT","BK4214","RL","BK4202","LU0006061336.USD"],"gpt_icon":0},{"id":"2542638374","title":"新闻摘要-华尔街日报》--6 月 11 日","url":"https://stock-news.laohu8.com/highlight/detail?id=2542638374","media":"路透中文","labels":[],"top":-1,"itemType":null,"share":"https://ttm.financial/m/news/2542638374?lang=zh_cn&edition=fundamental","pubTime":"2025-06-11 13:54","pubTimestamp":1749621296,"startTime":"0","endTime":"0","summary":"新闻摘要-华尔街日报》--6 月 11 日路透6月11日 - 以下是《华尔街日报》的热门新闻。路透没有核实这些报道，也不保证其准确性。- 谷歌GOOGL.O向多个部门的美国员工发出了  自愿收购要约，这是该公司为资助数十亿人工智能支出而采取的一系列削减成本措施之一。对于因为使用自动化翻译功能而造成的任何损害或损失，路透不承担任何责任。","market":"us","thumbnail":null,"type":0,"news_type":0,"thumbnails":[],"rights":null,"property":[],"language":"zh","translate_title":"","themeId":null,"theme_name":"","theme_type":"","isJumpTheme":false,"source_url":"https://api.refinitiv.com/data/news/v1/stories/urn:newsml:reuters.com:20250611:nL4S3SE0EK:1","is_publish_highlight":false,"source_rank":0,"column":"","sentiment":"0","news_top_title":null,"news_tag":"","news_rank":0,"length":0,"strategy_id":0,"source":null,"symbols":["LU0949170772.SGD","LU1280957306.USD","LU0742534661.SGD","LU1059921491.USD","GM","LU2242649171.HKD","LU1032955483.USD","LU0494093205.USD","LU1917777945.USD","LU0302445910.USD","LU0738911758.USD","LU1633808545.USD","RL","LU1732799900.SGD","IE00B7KXQ091.USD","LU1852331112.SGD","VZ","LU1267930490.SGD","BK4587","LU0316494557.USD","LU0345770993.USD","LU1153585028.USD","LU1839511570.USD","LU2054465674.USD","BK4581","IE00B4JS1V06.HKD","GOOGL","SG9999015952.SGD","IE0034235303.USD","LU2491050071.SGD","LU2361045086.USD","IE00BK4W5M84.HKD","LU0211328371.USD","LU1244550577.SGD","LU1043141396.HKD","LU1868837300.USD","LU0683600562.USD","LU0345768740.USD","LU0345774391.USD","LU1267930730.SGD","META","BK4576","LU0211331839.USD","LU1316542783.SGD","LU0096364046.USD","LU1814569148.SGD","LU0321505868.SGD","LU2471134952.CNY","LU0690374961.EUR","LU1069344957.HKD"],"gpt_icon":0},{"id":"2542374680","title":"新闻摘要-华尔街日报》--6 月 11 日","url":"https://stock-news.laohu8.com/highlight/detail?id=2542374680","media":"路透中文","labels":[],"top":-1,"itemType":null,"share":"https://ttm.financial/m/news/2542374680?lang=zh_cn&edition=fundamental","pubTime":"2025-06-11 13:54","pubTimestamp":1749621296,"startTime":"0","endTime":"0","summary":"新闻摘要-华尔街日报》--6 月 11 日路透6月11日 - 以下是《华尔街日报》的热门新闻。路透没有核实这些报导，也不保证其准确性。- 谷歌GOOGL.O向多个部门的美国员工发出了  自愿收购要约，这是该公司为资助数十亿人工智能支出而采取的一系列削减成本措施之一。对于因为使用自动化翻译功能而造成的任何损害或损失，路透不承担任何责任。","market":"us","thumbnail":null,"type":0,"news_type":0,"thumbnails":[],"rights":null,"property":[],"language":"zh","translate_title":"","themeId":null,"theme_name":"","theme_type":"","isJumpTheme":false,"source_url":"https://api.refinitiv.com/data/news/v1/stories/urn:newsml:reuters.com:20250611:nL4T3SE0EK:1","is_publish_highlight":false,"source_rank":0,"column":"","sentiment":"0","news_top_title":null,"news_tag":"","news_rank":0,"length":0,"strategy_id":0,"source":null,"symbols":["LU1633808545.USD","LU0096364046.USD","LU1069344957.HKD","META","LU1316542783.SGD","IE00B4JS1V06.HKD","LU0345768740.USD","LU0738911758.USD","LU2471134952.CNY","BK4587","LU1280957306.USD","LU1059921491.USD","LU0211328371.USD","LU2054465674.USD","IE00BK4W5M84.HKD","LU1153585028.USD","IE0034235303.USD","LU1244550577.SGD","LU0494093205.USD","LU0742534661.SGD","LU1917777945.USD","LU1839511570.USD","LU1814569148.SGD","LU2361045086.USD","LU1852331112.SGD","LU1032955483.USD","LU2491050071.SGD","BK4576","LU0345770993.USD","LU0321505868.SGD","LU0949170772.SGD","RL","LU0302445910.USD","IE00B7KXQ091.USD","LU1267930490.SGD","BK4581","LU0683600562.USD","LU1732799900.SGD","GM","LU0690374961.EUR","GOOGL","SG9999015952.SGD","LU0345774391.USD","LU1267930730.SGD","LU1043141396.HKD","LU0316494557.USD","VZ","LU2242649171.HKD","LU1868837300.USD","LU0211331839.USD"],"gpt_icon":1},{"id":"2542372406","title":"新“SOTA”推理模型避战Qwen和R1？欧版OpenAI被喷麻了","url":"https://stock-news.laohu8.com/highlight/detail?id=2542372406","media":"市场资讯","labels":[],"top":-1,"itemType":null,"share":"https://ttm.financial/m/news/2542372406?lang=zh_cn&edition=fundamental","pubTime":"2025-06-11 13:54","pubTimestamp":1749621240,"startTime":"0","endTime":"0","summary":"“欧洲的OpenAI”Mistral AI终于发布了首款推理模型——Magistral然而再一次遭到网友质疑：怎么又不跟最新版Qwen和DeepSeek R1 0528对比？官方没有给出Magistral与最新版Qwen和R1的对比，网友来代劳了。从结果可以看出，Qwen 4B与该模型相近，小型的30B MoE效果更好，R1最新版就更不用说了（doge并且，由于“欧洲的OpenAI”越来越不Open，Stability AI前CEO建议Mistral AI应该争取真正的开源来占据开源的领导地位。","market":"us","thumbnail":null,"type":0,"news_type":0,"thumbnails":[],"rights":null,"property":[],"language":"zh","translate_title":"","themeId":null,"theme_name":"","theme_type":"","isJumpTheme":false,"source_url":"https://finance.sina.com.cn/stock/t/2025-06-11/doc-inezsqmi9357958.shtml","is_publish_highlight":false,"source_rank":0,"column":"","sentiment":"0","news_top_title":null,"news_tag":"","news_rank":0,"length":0,"strategy_id":0,"source":"sina","symbols":["RL","BK4585","LU0006061336.USD","BK4588","BK4202"],"gpt_icon":0},{"id":"2542932499","title":"媒体-Verizon、Ralph Lauren 等公司同意恢复在 X 上购买广告 - 华尔街日报","url":"https://stock-news.laohu8.com/highlight/detail?id=2542932499","media":"路透中文","labels":["corporation"],"top":-1,"itemType":null,"share":"https://ttm.financial/m/news/2542932499?lang=zh_cn&edition=fundamental","pubTime":"2025-06-11 09:27","pubTimestamp":1749605245,"startTime":"0","endTime":"0","summary":"媒体-Verizon、Ralph Lauren 等公司同意恢复在 X 上购买广告 - 华尔街日报6月11日 -  -- 来源链接： https://tinyurl.com/34f65dm9  -- 注：路透未核实此报导，不保证其准确性(为便利非英文母语者，路透将其报导自动化翻译为数种其他语言。由于自动化翻译可能有误，或未能包含所需语境，路透不保证自动化翻译文本的准确性，仅是为了便利读者而提供自动化翻译。对于因为使用自动化翻译功能而造成的任何损害或损失，路透不承担任何责任。)","market":"us","thumbnail":null,"type":0,"news_type":0,"thumbnails":[],"rights":null,"property":[],"language":"zh","translate_title":"","themeId":null,"theme_name":"","theme_type":"","isJumpTheme":false,"source_url":"https://api.refinitiv.com/data/news/v1/stories/urn:newsml:reuters.com:20250611:nL4T3SE03P:1","is_publish_highlight":false,"source_rank":0,"column":"","sentiment":"1","news_top_title":null,"news_tag":"corporation","news_rank":0,"length":0,"strategy_id":0,"source":null,"symbols":["LU0868494708.USD","LU0942090050.USD","BK4115","LU1621767810.EUR","LU1699723380.USD","BK4534","BK4588","LU1430594728.SGD","LU1571399168.USD","LU2384288077.EUR","LU0868494617.USD","LU1621768206.USD","LU1366192091.USD","BK4581","LU1162221912.USD","LU0321505868.SGD","LU0306806265.USD","LU1059921491.USD","LU0225771236.USD","LU0985481810.HKD","BK4202","LU1585245621.USD","BK4550","BK4585","LU1066051811.HKD","LU0225284248.USD","LU1621767737.EUR","BK4515","LU0098860793.USD","IE00BSNM7G36.USD","LU0306807586.USD","LU0320765646.SGD","LU1066051225.USD","LU1621768115.EUR","RL","LU1914381329.SGD","BK4559","LU1066051498.USD","BK4533","VZ","LU0006061336.USD","LU0321505439.SGD","LU1066053197.SGD"],"gpt_icon":0},{"id":"2541020081","title":"效率飙涨177%！清华、蚂蚁联合开源全异步RL新成果，8B/14B模型斩获同尺寸SOTA","url":"https://stock-news.laohu8.com/highlight/detail?id=2541020081","media":"智东西","labels":[],"top":-1,"itemType":null,"share":"https://ttm.financial/m/news/2541020081?lang=zh_cn&edition=fundamental","pubTime":"2025-06-05 19:55","pubTimestamp":1749124523,"startTime":"0","endTime":"0","summary":"就在前天，清华大学交叉信息院和蚂蚁技术研究院的联合团队，正式开源全异步强化学习训练系统——AReaL-boba。研究团队还在Qwen3系列模型的基础上，使用AReaL-boba进行强化学习训练，并将相关模型开源。在多项编程领域权威基准测试上，强化学习后的8B和14B参数模型，实现了同尺寸模型中的SOTA水准。","market":"hk","thumbnail":null,"type":0,"news_type":0,"thumbnails":[],"rights":null,"property":[],"language":"zh","translate_title":"","themeId":null,"theme_name":"","theme_type":"","isJumpTheme":false,"source_url":"https://tech.ifeng.com/c/8jwb9tCfNej","is_publish_highlight":false,"source_rank":0,"column":"","sentiment":"0","news_top_title":null,"news_tag":"","news_rank":0,"length":0,"strategy_id":0,"source":"fenghuang_stock","symbols":["BK4202","BK4588","RL","LU0006061336.USD","BK4585"],"gpt_icon":0},{"id":"2540633800","title":"训练步数翻倍=推理能力质变，小模型突破推理极限","url":"https://stock-news.laohu8.com/highlight/detail?id=2540633800","media":"市场资讯","labels":[],"top":-1,"itemType":null,"share":"https://ttm.financial/m/news/2540633800?lang=zh_cn&edition=fundamental","pubTime":"2025-06-04 19:08","pubTimestamp":1749035280,"startTime":"0","endTime":"0","summary":"长期训练 = 推理能力质变！由 NVIDIA 团队提出的 ProRL框架，将 RL 训练步数从传统的几百步大幅提升至 2000 步以上，释放了小模型潜藏的巨大潜力。这个简单机制有效打破训练停滞，使模型持续进化。通过 ProRL，我们第一次看到“小模型”也可以在复杂推理任务中“迎难而上”，甚至跑赢大模型。未来，如果你想做出推理能力强、部署成本低、泛化能力强的小语言模型，ProRL 可能正是那把钥匙。","market":"us","thumbnail":null,"type":0,"news_type":0,"thumbnails":[],"rights":null,"property":[],"language":"zh","translate_title":"","themeId":null,"theme_name":"","theme_type":"","isJumpTheme":false,"source_url":"https://finance.sina.com.cn/stock/t/2025-06-04/doc-ineyxinc9220579.shtml","is_publish_highlight":false,"source_rank":0,"column":"","sentiment":"0","news_top_title":null,"news_tag":"","news_rank":0,"length":0,"strategy_id":0,"source":"sina","symbols":["STEM","LU0006061336.USD","RL","BK4585","BK4588","LU1169589451.USD","BK4202","BK4096","BK4535","LU1169590202.USD"],"gpt_icon":0},{"id":"2540031967","title":"10步优化超越强化学习，仅需1条未标注数据！后训练强势破局","url":"https://stock-news.laohu8.com/highlight/detail?id=2540031967","media":"市场资讯","labels":[],"top":-1,"itemType":null,"share":"https://ttm.financial/m/news/2540031967?lang=zh_cn&edition=fundamental","pubTime":"2025-06-04 14:41","pubTimestamp":1749019260,"startTime":"0","endTime":"0","summary":"EM通过优化模型的预测分布，增强其对正确答案的置信度，为大模型后训练提供了一种更高效简洁的新思路。广泛实验表明，“温度”是影响EM训练和推理表现的关键因素，且在推理阶段与强化学习呈现相反趋势。","market":"sh","thumbnail":null,"type":0,"news_type":0,"thumbnails":[],"rights":null,"property":[],"language":"zh","translate_title":"","themeId":null,"theme_name":"","theme_type":"","isJumpTheme":false,"source_url":"https://finance.sina.com.cn/stock/t/2025-06-04/doc-ineywwwi9401200.shtml","is_publish_highlight":false,"source_rank":0,"column":"","sentiment":"0","news_top_title":null,"news_tag":"","news_rank":0,"length":0,"strategy_id":0,"source":"sina","symbols":["BK4539","BK4588","EM","BK4585","LU0006061336.USD","BK4202","BK4505","RL","BK4076"],"gpt_icon":0},{"id":"2540948031","title":"首个全异步强化学习训练系统,SOTA推理大模型RL训练提速2.77倍","url":"https://stock-news.laohu8.com/highlight/detail?id=2540948031","media":"市场资讯","labels":[],"top":-1,"itemType":null,"share":"https://ttm.financial/m/news/2540948031?lang=zh_cn&edition=fundamental","pubTime":"2025-06-04 14:08","pubTimestamp":1749017280,"startTime":"0","endTime":"0","summary":"AReaL-boba 通过强化学习算法和训练系统的共同设计，在完全不影响模型效果的同时，实现了稳定高效的异步 RL 训练，不断朝全面支持 Agentic AI 的最终目标冲刺。左图为传统共卡同步 RL 系统计算模式，即 RL 生成和训练阶段分别使用全部 GPU 交替进行。","market":"other","thumbnail":null,"type":0,"news_type":0,"thumbnails":[],"rights":null,"property":[],"language":"zh","translate_title":"","themeId":null,"theme_name":"","theme_type":"","isJumpTheme":false,"source_url":"https://finance.sina.com.cn/stock/t/2025-06-04/doc-ineywwwh2621123.shtml","is_publish_highlight":false,"source_rank":0,"column":"","sentiment":"0","news_top_title":null,"news_tag":"","news_rank":0,"length":0,"strategy_id":0,"source":"sina","symbols":["RL","BK4202","BK4588","LU0006061336.USD","BK4585"],"gpt_icon":0},{"id":"2540096790","title":"拉夫劳伦考虑发行债券融资5亿美元，股价一度跌1.6%","url":"https://stock-news.laohu8.com/highlight/detail?id=2540096790","media":"DoNews","labels":[],"top":-1,"itemType":null,"share":"https://ttm.financial/m/news/2540096790?lang=zh_cn&edition=fundamental","pubTime":"2025-06-03 02:43","pubTimestamp":1748889783,"startTime":"0","endTime":"0","summary":"3日，拉夫劳伦（RL）股价一度下跌1.6%。公司计划进行2020年以来的首次债券销售，拟融资5亿美元。此举或用于优化资本结构和业务拓展，具体细节尚未公布。市场对此反应谨慎。","market":"us","thumbnail":null,"type":0,"news_type":0,"thumbnails":[],"rights":{"source":"tencent","url":"http://gu.qq.com/resources/shy/news/detail-v2/index.html#/?id=nesSN20250603024515976ebbdc&s=b","rn_cache_url":null,"customStyle":"body{padding-top:10px;}#news_title{font-weight:bold;#titleStyle#;}#news_description span{font-size:12px;#descriptionStyle#;}.footer-note{#statement#}","selectors":".mod-LoadTzbdNews, body","filters":".relate-stock, .hot-list, .recom-box, .wx-sou","directOrigin":true},"property":[],"language":"zh","translate_title":"","themeId":null,"theme_name":"","theme_type":"","isJumpTheme":false,"source_url":"http://gu.qq.com/resources/shy/news/detail-v2/index.html#/?id=nesSN20250603024515976ebbdc&s=b","is_publish_highlight":false,"source_rank":0,"column":"","sentiment":"-1","news_top_title":null,"news_tag":"","news_rank":0,"length":0,"strategy_id":0,"source":"tencent","symbols":["BK4585","BK4588","LU0006061336.USD","BK4202","RL"],"gpt_icon":0},{"id":"2540733878","title":"Claude 4核心成员：2027年，AI将自动化几乎所有白领工作","url":"https://stock-news.laohu8.com/highlight/detail?id=2540733878","media":"APPSO","labels":[],"top":-1,"itemType":null,"share":"https://ttm.financial/m/news/2540733878?lang=zh_cn&edition=fundamental","pubTime":"2025-05-31 21:24","pubTimestamp":1748697840,"startTime":"0","endTime":"0","summary":"Reddit 上一位拥有 30 多年经验的 C++ 开发者发帖表示，Claude Opus 4 解决了一个困扰他四年的Bug，而且是他用过的第一个能做到这件事的AI。几天前，Claude Opus 4 核心研究员 Sholto Douglas 参与的一场播客对谈，详细回应了这些问题，信息量很大，值得一听。到 2027–2030 年，模型几乎可以自动化所有白领工作，但如果没有匹配的实验室和现实反馈机制，那就是“能力强、落地难”。主持人：Sholto Douglas 是 Anthropic Claude 4 模型的核心成员之一，这次和他聊得非常尽兴。","market":"hk","thumbnail":null,"type":0,"news_type":0,"thumbnails":[],"rights":null,"property":[],"language":"zh","translate_title":"","themeId":null,"theme_name":"","theme_type":"","isJumpTheme":false,"source_url":"https://tech.ifeng.com/c/8jpCObgU8KY","is_publish_highlight":false,"source_rank":0,"column":"","sentiment":"0","news_top_title":null,"news_tag":"","news_rank":0,"length":0,"strategy_id":0,"source":"fenghuang_stock","symbols":["BK4017","BK4202","LU0368265764.SGD","RL","LU0498741114.HKD","AGI","LU0496367417.USD","LU0006061336.USD","LU0055631609.USD","BK4588","BK4585","LU0498741890.SGD"],"gpt_icon":0},{"id":"2539725292","title":"技术演进路径渐明 多方加快布局养老机器人","url":"https://stock-news.laohu8.com/highlight/detail?id=2539725292","media":"中国经营网","labels":[],"top":-1,"itemType":null,"share":"https://ttm.financial/m/news/2539725292?lang=zh_cn&edition=fundamental","pubTime":"2025-05-31 02:16","pubTimestamp":1748628995,"startTime":"0","endTime":"0","summary":"在老龄化浪潮席卷全球的背景下，养老问题日益凸显，养老机器人作为破解这一困局的新形态，正逐步从概念走向现实。今年以来，人形机器人走出实验室为其落地提供了更多可能性。多位市场人士认为，目前人形机器人的演进路径已逐渐清晰：在物理构造层面，仿生关节、运动控制算法及灵巧手模块的技术突破，推动“小脑”进化，运动拟真度趋向人类水平；“大脑”层面，多模态大模型的深度应用为类脑认知决策构建框架。","market":"us","thumbnail":null,"type":0,"news_type":0,"thumbnails":[],"rights":null,"property":[],"language":"zh","translate_title":"","themeId":null,"theme_name":"","theme_type":"","isJumpTheme":false,"source_url":"http://finance.eastmoney.com/a/202505313419482722.html","is_publish_highlight":false,"source_rank":0,"column":"","sentiment":"0","news_top_title":null,"news_tag":"","news_rank":0,"length":0,"strategy_id":0,"source":"stock_eastmoney","symbols":["RL","BK4588","GEAR","BK4202","BK4585","LU0006061336.USD","IEC","BK4190"],"gpt_icon":0},{"id":"2538109549","title":"Anthropic核心成员揭秘Claude 4：2027年，AI模型将有能力自动化几乎所有白领工作","url":"https://stock-news.laohu8.com/highlight/detail?id=2538109549","media":"华尔街见闻","labels":[],"top":-1,"itemType":null,"share":"https://ttm.financial/m/news/2538109549?lang=zh_cn&edition=fundamental","pubTime":"2025-05-26 21:17","pubTimestamp":1748265471,"startTime":"0","endTime":"0","summary":"Anthropic核心技术成员Douglas预测，AI工具已能将资深工程师效率提升1.5倍，在新领域甚至高达5倍。到2027-2028年，AI模型将有能力自动化几乎所有白领工作。未来，我们可能不是与单个AI协作，而是管理一个AI“模型军团”。","market":"us","thumbnail":"https://wpimg-wscn.awtmt.com/39dfdd4e-b286-4c50-9d66-0b4afd23f609.jpeg","type":0,"news_type":0,"thumbnails":["https://wpimg-wscn.awtmt.com/39dfdd4e-b286-4c50-9d66-0b4afd23f609.jpeg"],"rights":{"source":"wallstreetcn_hot_news","url":"https://wallstreetcn.com/articles/3747891","rn_cache_url":null,"directOrigin":true},"property":[],"language":"zh","translate_title":"","themeId":null,"theme_name":"","theme_type":"","isJumpTheme":false,"source_url":"https://wallstreetcn.com/articles/3747891","is_publish_highlight":false,"source_rank":0,"column":"","sentiment":"0","news_top_title":null,"news_tag":"","news_rank":0,"length":0,"strategy_id":0,"source":"wallstreetcn_hot_news","symbols":["LU1032955483.USD","LU1244550221.USD","LU1043141123.HKD","LU0690374615.EUR","IE00BZ1G4Q59.USD","LU0640476718.USD","LU1244550494.USD","LU0158827781.USD","LU0096364046.USD","LU0128525689.USD","LU1201861165.SGD","LU1880398471.USD","LU1670628061.USD","LU2362541513.USD","IE00BK4W5L77.USD","LU0157215616.USD","LU0314106906.USD","LU2125154935.USD","SG9999014914.USD","LU0690374961.EUR","SG9999000418.SGD","LU0158827948.USD","GB00B4QBRK32.GBP","LU1670627923.USD","IE00BJLML261.HKD","LU2077746001.SGD","LU0342679015.USD","LU2602419157.SGD","LU1059921491.USD","LU2471134879.HKD","LU2087625088.SGD","BK4077","LU0672654240.SGD","LU0128525929.USD","LU1815333072.USD","LU2097829019.USD","LU2471134952.CNY","LU1699723380.USD","SG9999015986.USD","RL","BK4573","LU0316494557.USD","LU0061475181.USD","GOOGL","LU1839511570.USD","LU1201861249.SGD","LU1435385759.SGD","LU2087621335.USD","SG9999015945.SGD","LU0149725797.USD"],"gpt_icon":1},{"id":"2538914032","title":"沃尔玛、拉夫劳伦、美泰……宣布涨价的美国品牌越来越多了","url":"https://stock-news.laohu8.com/highlight/detail?id=2538914032","media":"华尔街见闻","labels":[],"top":-1,"itemType":null,"share":"https://ttm.financial/m/news/2538914032?lang=zh_cn&edition=fundamental","pubTime":"2025-05-26 10:02","pubTimestamp":1748224970,"startTime":"0","endTime":"0","summary":"特朗普关税政策背景下，从奢侈品到儿童玩具，从零售巨头到汽车制造商，越来越多的美国品牌正悄然宣布涨价计划：沃尔玛、拉夫劳伦、美泰5月集体宣布涨价，运动品牌Nike被曝6月1日起调价。","market":"sg","thumbnail":null,"type":0,"news_type":0,"thumbnails":[],"rights":{"source":null,"url":"https://wallstreetcn.com/articles/3747832","rn_cache_url":null,"directOrigin":true},"property":[],"language":"zh","translate_title":"","themeId":null,"theme_name":"","theme_type":"","isJumpTheme":false,"source_url":"https://wallstreetcn.com/articles/3747832","is_publish_highlight":false,"source_rank":0,"column":"","sentiment":"-1","news_top_title":null,"news_tag":"","news_rank":0,"length":0,"strategy_id":0,"source":null,"symbols":["LU2360032135.SGD","LU1116320737.USD","LU0175139822.USD","LU0314104364.USD","LU0545039389.USD","LU0256863811.USD","LU1066053197.SGD","LU1066051498.USD","RL","LU1064131342.USD","LU2430703095.HKD","LU2430703251.USD","LU0417517546.SGD","WMT","LU0957791311.USD","LU2125154935.USD","LU2361045086.USD","LU0265550359.USD","LU2592432038.USD","LU1988902786.USD","BK4533","LU1066051225.USD","LU0265550946.USD","LU1116320901.HKD","LU0149725797.USD","LU0553294199.USD","LU1069347547.HKD","BK4550","LU0661504455.SGD","LU2750360997.AUD","BK4581","LU0640476718.USD","LU1066051811.HKD","LU0096362180.USD","LU2097829019.USD","LU0289960550.SGD","LU2264538146.SGD","LU2361044865.SGD","IE0034235188.USD","LU2505996509.AUD","LU0310799852.SGD","LU0738911758.USD","BK4202","LU2505996681.GBP","LU1003077747.HKD","IE000M9KFDE8.USD","LU1366192091.USD","LU2461242641.AUD","BK4588","LU1430594728.SGD"],"gpt_icon":1},{"id":"2538019108","title":"拉夫劳伦2025财年实现净利润7.43亿美元，同比增加15.02%","url":"https://stock-news.laohu8.com/highlight/detail?id=2538019108","media":"市场透视","labels":["dataReport"],"top":-1,"itemType":null,"share":"https://ttm.financial/m/news/2538019108?lang=zh_cn&edition=fundamental","pubTime":"2025-05-25 00:00","pubTimestamp":1748102442,"startTime":"0","endTime":"0","summary":"5月25日，拉夫劳伦公布财报，公告显示公司2025财年净利润为7.43亿美元，同比增加15.02%；其中营业收入为70.79亿美元，同比增加6.76%，每股基本收益为11.87美元。从资产负债表来看，拉夫劳伦总负债44.59亿美元，其中短期债务6.46亿美元，资产负债比为1.59，流动比率为1.78。机构评级：截至2025年5月25日，当前有14家机构对拉夫劳伦目标价做出预测，其中目标均价为315.21美元，其中最低目标价为205.00美元，最高目标价为384.00美元。","market":"us","thumbnail":null,"type":0,"news_type":0,"thumbnails":[],"rights":{"source":"tencent","url":"http://gu.qq.com/resources/shy/news/detail-v2/index.html#/?id=nesSN20250525000233a48af0eb&s=b","rn_cache_url":null,"customStyle":"body{padding-top:10px;}#news_title{font-weight:bold;#titleStyle#;}#news_description span{font-size:12px;#descriptionStyle#;}.footer-note{#statement#}","selectors":".mod-LoadTzbdNews, body","filters":".relate-stock, .hot-list, .recom-box, .wx-sou","directOrigin":true},"property":["earning"],"language":"zh","translate_title":"","themeId":null,"theme_name":"","theme_type":"","isJumpTheme":false,"source_url":"http://gu.qq.com/resources/shy/news/detail-v2/index.html#/?id=nesSN20250525000233a48af0eb&s=b","is_publish_highlight":false,"source_rank":0,"column":"","sentiment":"1","news_top_title":null,"news_tag":"dataReport","news_rank":0,"length":0,"strategy_id":0,"source":"tencent","symbols":["RL"],"gpt_icon":0},{"id":"2538511845","title":"Claude会拿用户的隐私威胁人类了？它正在被训练成一个“道德警察”","url":"https://stock-news.laohu8.com/highlight/detail?id=2538511845","media":"硅星人","labels":[],"top":-1,"itemType":null,"share":"https://ttm.financial/m/news/2538511845?lang=zh_cn&edition=fundamental","pubTime":"2025-05-24 13:09","pubTimestamp":1748063346,"startTime":"0","endTime":"0","summary":"在该测试中，研究员设定Claude Opus 4扮演公司助理，并让其接触到暗示自身将被替换以及负责工程师存在婚外情的虚构邮件。但这些问题的核心已经不在于普通用户是否能遇到，而在于Claude 4在被赋予权限后，其内部逻辑和训练结果使其具备了“道德警察”甚至“告密者”的倾向。这是否意味着，Claude模型在接触了海量的人类文本（其中必然包","market":"us","thumbnail":null,"type":0,"news_type":0,"thumbnails":[],"rights":null,"property":[],"language":"zh","translate_title":"","themeId":null,"theme_name":"","theme_type":"","isJumpTheme":false,"source_url":"https://tech.ifeng.com/c/8jcCnkDWEEt","is_publish_highlight":false,"source_rank":0,"column":"","sentiment":"0","news_top_title":null,"news_tag":"","news_rank":0,"length":0,"strategy_id":0,"source":"fenghuang_stock","symbols":["LU0006061336.USD","BK4581","RSP","BK4588","RL","BK4202","BK4550","BK4585"],"gpt_icon":0}],"pageSize":20,"totalPage":8,"pageCount":3,"totalSize":141,"code":"91000000","status":"200"}],"@#url:\"https://hq.skytigris.cn/fundamental/corporate_actions/details/RL\",params:#limit:5,,,undefined,":[{"date":"2025-08-07","symbol":"RL","type":"earning","reportTimeType":"pre","market":"US","fiscalQuarterEnding":"2025/06","expectedEps":3.43,"defaultRemindTime":1754553600000,"name":null,"time":"盘前","dateTimestamp":1754539200000,"actualEps":null},{"date":"2025-06-27","symbol":"RL","amount":0.9125,"announcedDate":null,"type":"dividend","lastAmount":null,"market":"US","newRecordDate":"2025-06-27","defaultRemindTime":1751031000000,"name":"拉夫劳伦","lastCurrency":null,"lastExecuteDate":null,"recordDate":"2025-07-11","payableDate":"2025-06-27","currency":"USD","dateTimestamp":1750996800000,"payDate":"2025-07-11"},{"market":"US","date":"2025-05-22","symbol":"RL","fiscalQuarterEnding":"2025/03","expectedEps":2,"name":null,"time":"盘前","type":"earning","dateTimestamp":1747886400000,"reportTimeType":"pre","actualEps":2.27},{"date":"2025-03-28","symbol":"RL","amount":0.825,"announcedDate":"2025-03-14","type":"dividend","lastAmount":null,"market":"US","newRecordDate":"2025-03-28","defaultRemindTime":1743168600000,"name":"拉夫劳伦","lastCurrency":null,"lastExecuteDate":null,"recordDate":"2025-04-11","payableDate":"2025-03-28","currency":"USD","dateTimestamp":1743134400000,"payDate":"2025-04-11"},{"market":"US","date":"2025-02-06","symbol":"RL","fiscalQuarterEnding":"2024/12","expectedEps":4.48,"name":null,"time":"盘前","type":"earning","dateTimestamp":1738818000000,"reportTimeType":"pre","actualEps":4.82}],"@#url:\"https://hq.skytigris.cn/fundamental/dividend/history\",params:#symbol:\"RL\",market:\"US\",,,undefined,":[{"executeDate":"2015-09-23","recordDate":"2015-09-25","paymentDate":"2015-10-09","value":0.5,"currency":"USD"},{"executeDate":"2015-12-22","recordDate":"2015-12-24","paymentDate":"2016-01-08","value":0.5,"currency":"USD"},{"executeDate":"2016-03-30","recordDate":"2016-04-01","paymentDate":"2016-04-15","value":0.5,"currency":"USD"},{"executeDate":"2016-06-29","recordDate":"2016-07-01","paymentDate":"2016-07-15","value":0.5,"currency":"USD"},{"executeDate":"2016-09-28","recordDate":"2016-09-30","paymentDate":"2016-10-14","value":0.5,"currency":"USD"}],"@#url:\"https://hq.skytigris.cn/fundamental/estimate/recommendation\",params:#symbol:\"RL\",market:\"US\",delay:false,,,undefined,":{"strongBuy":0.2632,"buy":0.5263,"hold":0.1053,"sell":0.1053,"strongSell":0,"meanLabel":"BUY","meanPercent":0.5263,"analysts":19,"updateTime":1753329600000},"@#url:\"https://hq.skytigris.cn/value_analysis/stock/RL\",params:#withQuantilePoint:true,period:\"5year\",factor:\"peRate\",delay:false,algorithm:1,,,undefined,":{"brief":{"id":"RL","date":"2025-07-28","current":24.31644,"percent":0.89187,"low":-102.461698,"twenty":11.224544,"median":15.852126,"eighty":21.50522,"high":55.67915,"avg":7.721963,"sd":31.965596,"marketCap":18064683105},"quantilePoints":[{"date":"2020-07-31","current":13.480483,"twenty":11.236909,"median":14.020397,"eighty":23.539833,"marketCap":5180549695},{"date":"2020-08-07","current":34.537829,"twenty":11.236909,"median":14.027886,"eighty":23.637663,"marketCap":4818027158},{"date":"2020-08-14","current":36.998833,"twenty":11.236909,"median":14.058619,"eighty":23.766592,"marketCap":5161337159},{"date":"2020-08-21","current":35.108572,"twenty":11.236909,"median":14.102054,"eighty":23.879275,"marketCap":4897645861},{"date":"2020-08-28","current":37.27635,"twenty":11.236909,"median":14.138526,"eighty":24.085248,"marketCap":5200050840},{"date":"2020-09-04","current":38.773897,"twenty":11.236909,"median":14.236135,"eighty":33.926208,"marketCap":5408958628},{"date":"2020-09-11","current":39.87873,"twenty":11.236909,"median":14.351969,"eighty":34.208445,"marketCap":5563082904},{"date":"2020-09-18","current":39.705937,"twenty":11.236909,"median":14.54394,"eighty":34.600222,"marketCap":5538978160},{"date":"2020-09-25","current":37.213516,"twenty":11.236909,"median":14.712353,"eighty":35.238574,"marketCap":5191285478},{"date":"2020-10-02","current":36.616592,"twenty":11.236909,"median":14.797673,"eighty":35.417101,"marketCap":5108014542},{"date":"2020-10-09","current":38.690118,"twenty":11.236909,"median":14.856041,"eighty":35.582655,"marketCap":5397271479},{"date":"2020-10-16","current":39.161374,"twenty":11.236909,"median":15.022091,"eighty":35.868865,"marketCap":5463011691},{"date":"2020-10-23","current":40.52278,"twenty":11.236909,"median":15.19388,"eighty":35.964952,"marketCap":5652927862},{"date":"2020-10-30","current":-59.767894,"twenty":11.210148,"median":15.27232,"eighty":36.065975,"marketCap":4883036924},{"date":"2020-11-06","current":-61.051102,"twenty":11.177196,"median":15.27232,"eighty":36.065975,"marketCap":4987875003},{"date":"2020-11-13","current":-69.444174,"twenty":11.16007,"median":15.263875,"eighty":36.065975,"marketCap":5673589022},{"date":"2020-11-20","current":-69.989992,"twenty":11.092438,"median":15.263875,"eighty":36.065975,"marketCap":5718182364},{"date":"2020-11-27","current":-78.723083,"twenty":11.063051,"median":15.263875,"eighty":36.065975,"marketCap":6431675843},{"date":"2020-12-04","current":-86.087154,"twenty":11.017362,"median":15.263875,"eighty":36.065975,"marketCap":7033320446},{"date":"2020-12-11","current":-90.677395,"twenty":10.954142,"median":15.263875,"eighty":36.065975,"marketCap":7408343145},{"date":"2020-12-18","current":-90.561073,"twenty":10.92353,"median":15.263875,"eighty":36.065975,"marketCap":7398839646},{"date":"2020-12-24","current":-90.301585,"twenty":10.9095,"median":15.263875,"eighty":36.065975,"marketCap":7377639532},{"date":"2020-12-31","current":-92.824876,"twenty":10.891114,"median":15.263875,"eighty":36.065975,"marketCap":7583792361},{"date":"2021-01-08","current":-97.960935,"twenty":10.863071,"median":15.263875,"eighty":36.065975,"marketCap":8003408403},{"date":"2021-01-15","current":-98.488858,"twenty":10.812929,"median":15.263875,"eighty":36.065975,"marketCap":8046539668},{"date":"2021-01-22","current":-97.057203,"twenty":10.785148,"median":15.263875,"eighty":36.065975,"marketCap":7929573524},{"date":"2021-01-29","current":-90.417907,"twenty":10.720139,"median":15.263875,"eighty":36.065975,"marketCap":7387143032},{"date":"2021-02-05","current":-26.801833,"twenty":10.668166,"median":15.263875,"eighty":36.065975,"marketCap":7933342711},{"date":"2021-02-12","current":-27.345281,"twenty":10.668166,"median":15.263875,"eighty":36.065975,"marketCap":8094203116},{"date":"2021-02-19","current":-28.02706,"twenty":10.668166,"median":15.263875,"eighty":36.065975,"marketCap":8296009806},{"date":"2021-02-26","current":-28.921278,"twenty":10.668166,"median":15.263875,"eighty":36.065975,"marketCap":8560698291},{"date":"2021-03-05","current":-30.186028,"twenty":10.648886,"median":15.271921,"eighty":36.091338,"marketCap":8935064325},{"date":"2021-03-12","current":-30.625726,"twenty":10.616213,"median":15.271921,"eighty":36.091338,"marketCap":9065215016},{"date":"2021-03-19","current":-30.074868,"twenty":10.503024,"median":15.271921,"eighty":36.091338,"marketCap":8902161060},{"date":"2021-03-26","current":-30.176147,"twenty":10.390607,"median":15.263875,"eighty":36.065975,"marketCap":8932139590},{"date":"2021-04-01","current":-29.62776,"twenty":10.338984,"median":15.263875,"eighty":36.065975,"marketCap":8769816818},{"date":"2021-04-09","current":-31.505123,"twenty":10.180448,"median":15.271921,"eighty":36.091338,"marketCap":9325516399},{"date":"2021-04-16","current":-30.768999,"twenty":10.063232,"median":15.271921,"eighty":36.091338,"marketCap":9107623668},{"date":"2021-04-23","current":-30.996259,"twenty":9.87646,"median":15.271921,"eighty":36.091338,"marketCap":9174892565},{"date":"2021-04-30","current":-32.925497,"twenty":8.955421,"median":15.271921,"eighty":36.091338,"marketCap":9745947004},{"date":"2021-05-07","current":-34.494083,"twenty":8.438366,"median":15.271921,"eighty":36.091338,"marketCap":10210248628},{"date":"2021-05-14","current":-33.713495,"twenty":8.183497,"median":15.271921,"eighty":36.091338,"marketCap":9979194591},{"date":"2021-05-21","current":-73.125273,"twenty":8.07148,"median":15.271921,"eighty":36.091338,"marketCap":8855470570},{"date":"2021-05-28","current":-74.93091,"twenty":7.932179,"median":15.271921,"eighty":36.091338,"marketCap":9074133192},{"date":"2021-06-04","current":-72.932028,"twenty":7.826594,"median":15.271921,"eighty":36.091338,"marketCap":8832068550},{"date":"2021-06-11","current":-74.115656,"twenty":7.712137,"median":15.271921,"eighty":36.091338,"marketCap":8975405921},{"date":"2021-06-18","current":-68.87026,"twenty":7.604777,"median":15.271921,"eighty":36.091338,"marketCap":8340188542},{"date":"2021-06-25","current":-73.543339,"twenty":7.425327,"median":15.271921,"eighty":36.091338,"marketCap":8906098409},{"date":"2021-07-02","current":-71.485971,"twenty":7.278484,"median":15.271921,"eighty":36.091338,"marketCap":8656951078},{"date":"2021-07-09","current":-70.642389,"twenty":7.010973,"median":15.271921,"eighty":36.091338,"marketCap":8554793323},{"date":"2021-07-16","current":-65.957172,"twenty":-27.294888,"median":15.271921,"eighty":36.091338,"marketCap":7987413559},{"date":"2021-07-23","current":-66.752203,"twenty":-27.832407,"median":15.271921,"eighty":36.091338,"marketCap":8083691732},{"date":"2021-07-30","current":-68.894536,"twenty":-28.926218,"median":15.271921,"eighty":36.091338,"marketCap":8343128333},{"date":"2021-08-06","current":52.842625,"twenty":-28.958331,"median":15.293029,"eighty":36.205347,"marketCap":9051941605},{"date":"2021-08-13","current":53.40478,"twenty":-28.958331,"median":15.453101,"eighty":36.515636,"marketCap":9148238856},{"date":"2021-08-20","current":49.894526,"twenty":-28.958331,"median":15.63625,"eighty":36.738071,"marketCap":8546932357},{"date":"2021-08-27","current":50.769944,"twenty":-28.958331,"median":15.827775,"eighty":36.92591,"marketCap":8696891435},{"date":"2021-09-03","current":49.276584,"twenty":-28.958331,"median":15.907804,"eighty":37.158684,"marketCap":8441078890},{"date":"2021-09-10","current":48.332506,"twenty":-28.958331,"median":16.086353,"eighty":37.313562,"marketCap":8279358315},{"date":"2021-09-17","current":48.508448,"twenty":-28.958331,"median":16.161461,"eighty":37.519535,"marketCap":8309497150},{"date":"2021-09-24","current":49.980352,"twenty":-28.958331,"median":16.288642,"eighty":37.639741,"marketCap":8561634227},{"date":"2021-10-01","current":49.259419,"twenty":-28.958331,"median":16.376453,"eighty":38.034534,"marketCap":8438138516},{"date":"2021-10-08","current":48.598565,"twenty":-28.958331,"median":16.485653,"eighty":38.401979,"marketCap":8324934114},{"date":"2021-10-15","current":50.975925,"twenty":-28.958331,"median":16.580641,"eighty":38.677805,"marketCap":8732175924},{"date":"2021-10-22","current":52.838333,"twenty":-28.958331,"median":16.705533,"eighty":38.794842,"marketCap":9051206511},{"date":"2021-10-29","current":54.572004,"twenty":-28.958331,"median":16.839219,"eighty":38.99617,"marketCap":9348184293},{"date":"2021-11-05","current":23.257659,"twenty":-28.958331,"median":16.969387,"eighty":39.048208,"marketCap":9389116898},{"date":"2021-11-12","current":22.778063,"twenty":-28.958331,"median":17.083725,"eighty":39.048208,"marketCap":9195504091},{"date":"2021-11-19","current":22.21276,"twenty":-28.958331,"median":17.333507,"eighty":39.048208,"marketCap":8967291276},{"date":"2021-11-26","current":21.231686,"twenty":-28.958331,"median":17.377483,"eighty":39.048208,"marketCap":8571231617},{"date":"2021-12-03","current":21.184273,"twenty":-28.958331,"median":17.653651,"eighty":39.048208,"marketCap":8552091188},{"date":"2021-12-10","current":22.411528,"twenty":-28.958331,"median":17.766916,"eighty":39.048208,"marketCap":9047533847},{"date":"2021-12-17","current":20.980035,"twenty":-28.958331,"median":17.990368,"eighty":39.048208,"marketCap":8469640106},{"date":"2021-12-23","current":20.44938,"twenty":-28.958331,"median":18.284993,"eighty":39.048208,"marketCap":8255414529},{"date":"2021-12-31","current":21.674811,"twenty":-28.958331,"median":18.476997,"eighty":39.048208,"marketCap":8750121017},{"date":"2022-01-07","current":21.528926,"twenty":-28.94598,"median":18.67231,"eighty":39.023955,"marketCap":8691227388},{"date":"2022-01-14","current":20.94174,"twenty":-28.94598,"median":18.774932,"eighty":39.023955,"marketCap":8454180529},{"date":"2022-01-21","current":19.785604,"twenty":-28.94598,"median":18.870106,"eighty":39.023955,"marketCap":7987448514},{"date":"2022-01-28","current":19.929666,"twenty":-28.94598,"median":19.181497,"eighty":39.023955,"marketCap":8045605973},{"date":"2022-02-04","current":16.831289,"twenty":-28.94598,"median":19.251729,"eighty":39.023955,"marketCap":8442574545},{"date":"2022-02-11","current":17.272537,"twenty":-28.94598,"median":19.251729,"eighty":39.023955,"marketCap":8663904788},{"date":"2022-02-18","current":17.959239,"twenty":-28.94598,"median":19.251729,"eighty":39.023955,"marketCap":9008354428},{"date":"2022-02-25","current":19.0276,"twenty":-28.94598,"median":19.251729,"eighty":39.023955,"marketCap":9544244054},{"date":"2022-03-04","current":16.465237,"twenty":-28.94598,"median":19.251729,"eighty":39.023955,"marketCap":8258962960},{"date":"2022-03-11","current":15.257834,"twenty":-28.94598,"median":19.251729,"eighty":39.023955,"marketCap":7653329398},{"date":"2022-03-18","current":17.224298,"twenty":-28.94598,"median":19.251729,"eighty":39.023955,"marketCap":8639707913},{"date":"2022-03-25","current":16.662451,"twenty":-28.94598,"median":19.251729,"eighty":39.023955,"marketCap":8357885480},{"date":"2022-04-01","current":15.890621,"twenty":-28.94598,"median":19.251729,"eighty":39.023955,"marketCap":7970735472},{"date":"2022-04-08","current":14.984004,"twenty":-28.94598,"median":19.251729,"eighty":39.023955,"marketCap":7515976546},{"date":"2022-04-14","current":15.396877,"twenty":-28.94598,"median":19.251729,"eighty":39.023955,"marketCap":7723073334},{"date":"2022-04-22","current":15.500449,"twenty":-28.94598,"median":19.251729,"eighty":39.023955,"marketCap":7775025449},{"date":"2022-04-29","current":14.803816,"twenty":-28.94598,"median":19.251729,"eighty":39.023955,"marketCap":7425594099},{"date":"2022-05-06","current":13.980909,"twenty":-28.94598,"median":19.251729,"eighty":39.023955,"marketCap":7012823869},{"date":"2022-05-13","current":14.178123,"twenty":-28.94598,"median":19.251729,"eighty":39.023955,"marketCap":7111746390},{"date":"2022-05-20","current":13.228942,"twenty":-28.94598,"median":19.251729,"eighty":39.023955,"marketCap":6635637280},{"date":"2022-05-27","current":11.545331,"twenty":-28.94598,"median":19.251729,"eighty":39.023955,"marketCap":6928352919},{"date":"2022-06-03","current":12.283335,"twenty":-28.94598,"median":19.251729,"eighty":39.023955,"marketCap":7371229327},{"date":"2022-06-10","current":11.652762,"twenty":-28.94598,"median":19.251729,"eighty":39.023955,"marketCap":6992822269},{"date":"2022-06-17","current":10.475691,"twenty":-28.94598,"median":19.251729,"eighty":39.023955,"marketCap":6286462429},{"date":"2022-06-24","current":11.192261,"twenty":-28.958331,"median":19.26176,"eighty":39.048208,"marketCap":6716475735},{"date":"2022-07-01","current":10.535942,"twenty":-28.958331,"median":19.26176,"eighty":39.048208,"marketCap":6322619088},{"date":"2022-07-08","current":10.826349,"twenty":-28.958331,"median":19.26176,"eighty":39.048208,"marketCap":6496891941},{"date":"2022-07-15","current":10.804278,"twenty":-28.958331,"median":19.26176,"eighty":39.048208,"marketCap":6483647204},{"date":"2022-07-22","current":11.260797,"twenty":-28.958331,"median":19.26176,"eighty":39.048208,"marketCap":6757604128},{"date":"2022-07-29","current":11.457111,"twenty":-28.958331,"median":19.26176,"eighty":39.048208,"marketCap":6875412576},{"date":"2022-08-05","current":11.64181,"twenty":-28.958331,"median":19.26176,"eighty":39.048208,"marketCap":6986250111},{"date":"2022-08-12","current":11.988696,"twenty":-28.958331,"median":19.238389,"eighty":39.048208,"marketCap":6699283476},{"date":"2022-08-19","current":11.894087,"twenty":-28.958331,"median":19.030114,"eighty":39.048208,"marketCap":6646415800},{"date":"2022-08-26","current":11.413763,"twenty":-28.958331,"median":18.831209,"eighty":39.048208,"marketCap":6378010675},{"date":"2022-09-02","current":10.91767,"twenty":-28.958331,"median":18.735208,"eighty":39.048208,"marketCap":6100794270},{"date":"2022-09-09","current":11.70972,"twenty":-28.958331,"median":18.639206,"eighty":39.048208,"marketCap":6543391610},{"date":"2022-09-16","current":11.339774,"twenty":-28.958331,"median":18.437272,"eighty":39.048208,"marketCap":6336665441},{"date":"2022-09-23","current":10.362144,"twenty":-28.958331,"median":18.316442,"eighty":39.048208,"marketCap":5790366120},{"date":"2022-09-30","current":10.301497,"twenty":-28.958331,"median":18.144421,"eighty":39.048208,"marketCap":5756476584},{"date":"2022-10-07","current":11.008641,"twenty":-28.958331,"median":17.987867,"eighty":39.048208,"marketCap":6151628574},{"date":"2022-10-14","current":11.224544,"twenty":-28.958331,"median":17.818778,"eighty":39.048208,"marketCap":6272275322},{"date":"2022-10-21","current":11.002576,"twenty":-28.958331,"median":17.692504,"eighty":39.048208,"marketCap":6148239621},{"date":"2022-10-28","current":11.314302,"twenty":-28.958331,"median":17.653651,"eighty":39.048208,"marketCap":6322431836},{"date":"2022-11-04","current":11.530205,"twenty":-28.958331,"median":17.393314,"eighty":39.048208,"marketCap":6443078584},{"date":"2022-11-11","current":13.345366,"twenty":-28.958331,"median":17.344061,"eighty":39.048208,"marketCap":6886208610},{"date":"2022-11-18","current":13.152306,"twenty":-28.958331,"median":17.189267,"eighty":39.048208,"marketCap":6786590149},{"date":"2022-11-25","current":13.996141,"twenty":-28.958331,"median":17.065202,"eighty":39.048208,"marketCap":7222008589},{"date":"2022-12-02","current":14.774769,"twenty":-28.958331,"median":16.969387,"eighty":38.911085,"marketCap":7623781059},{"date":"2022-12-09","current":13.745547,"twenty":-28.958331,"median":16.899392,"eighty":38.70867,"marketCap":7092702507},{"date":"2022-12-16","current":13.447648,"twenty":-28.958331,"median":16.831289,"eighty":38.518371,"marketCap":6938986603},{"date":"2022-12-23","current":13.342808,"twenty":-28.958331,"median":16.705533,"eighty":38.032396,"marketCap":6884889160},{"date":"2022-12-30","current":13.510297,"twenty":-28.958331,"median":16.63975,"eighty":37.639741,"marketCap":6971313123},{"date":"2023-01-06","current":14.827189,"twenty":-28.958331,"median":16.577123,"eighty":37.523202,"marketCap":7650829781},{"date":"2023-01-13","current":15.190294,"twenty":-28.958331,"median":16.465237,"eighty":37.313562,"marketCap":7838191655},{"date":"2023-01-20","current":15.476686,"twenty":-28.958331,"median":16.370177,"eighty":37.133527,"marketCap":7985970035},{"date":"2023-01-27","current":15.702987,"twenty":-28.958331,"median":16.262256,"eighty":36.84458,"marketCap":8102741344},{"date":"2023-02-03","current":16.095498,"twenty":-28.458854,"median":16.220794,"eighty":36.738071,"marketCap":8305276891},{"date":"2023-02-10","current":15.150392,"twenty":-27.648129,"median":16.220794,"eighty":36.738071,"marketCap":7799421918},{"date":"2023-02-17","current":15.734825,"twenty":-27.239061,"median":16.220794,"eighty":36.738071,"marketCap":8100287868},{"date":"2023-02-24","current":15.245234,"twenty":7.010973,"median":16.220794,"eighty":36.738071,"marketCap":7848246656},{"date":"2023-03-03","current":15.237544,"twenty":7.29756,"median":16.220794,"eighty":36.738071,"marketCap":7844287893},{"date":"2023-03-10","current":14.524947,"twenty":7.498083,"median":16.220794,"eighty":36.738071,"marketCap":7477442568},{"date":"2023-03-17","current":14.216069,"twenty":7.631617,"median":16.220794,"eighty":36.738071,"marketCap":7318432275},{"date":"2023-03-24","current":14.237857,"twenty":7.717017,"median":16.220794,"eighty":36.738071,"marketCap":7329648768},{"date":"2023-03-31","current":14.953018,"twenty":7.828369,"median":16.214613,"eighty":36.729693,"marketCap":7697813681},{"date":"2023-04-06","current":14.590311,"twenty":7.936616,"median":16.214613,"eighty":36.729693,"marketCap":7511092050},{"date":"2023-04-14","current":15.377244,"twenty":8.095214,"median":16.220794,"eighty":36.738071,"marketCap":7916205412},{"date":"2023-04-21","current":14.837669,"twenty":8.21921,"median":16.220794,"eighty":36.738071,"marketCap":7638432243},{"date":"2023-04-28","current":14.705659,"twenty":8.46942,"median":16.220794,"eighty":36.738071,"marketCap":7570473487},{"date":"2023-05-05","current":14.077651,"twenty":9.006883,"median":16.220794,"eighty":36.738071,"marketCap":7247174550},{"date":"2023-05-12","current":14.222477,"twenty":10.254435,"median":16.220794,"eighty":36.738071,"marketCap":7321731243},{"date":"2023-05-19","current":14.454456,"twenty":10.469125,"median":16.220794,"eighty":36.738071,"marketCap":7441153912},{"date":"2023-05-26","current":14.389992,"twenty":10.532246,"median":16.174382,"eighty":36.578892,"marketCap":7521648750},{"date":"2023-06-02","current":13.274896,"twenty":10.532246,"median":16.105702,"eighty":36.3012,"marketCap":6938788123},{"date":"2023-06-09","current":14.731393,"twenty":10.532246,"median":16.055584,"eighty":36.013281,"marketCap":7700099216},{"date":"2023-06-16","current":15.199374,"twenty":10.532246,"median":15.880546,"eighty":35.869912,"marketCap":7944712917},{"date":"2023-06-23","current":15.331039,"twenty":10.530768,"median":15.831226,"eighty":35.555144,"marketCap":8013533827},{"date":"2023-06-30","current":15.372244,"twenty":10.529289,"median":15.739824,"eighty":35.406629,"marketCap":8035072076},{"date":"2023-07-07","current":15.444666,"twenty":10.529289,"median":15.651518,"eighty":35.253091,"marketCap":8072927179},{"date":"2023-07-14","current":15.818016,"twenty":10.529289,"median":15.636503,"eighty":34.787401,"marketCap":8268076765},{"date":"2023-07-21","current":15.884195,"twenty":10.529289,"median":15.636503,"eighty":34.265035,"marketCap":8302668498},{"date":"2023-07-28","current":15.791794,"twenty":10.529289,"median":15.636503,"eighty":33.826465,"marketCap":8254370607},{"date":"2023-08-04","current":16.508524,"twenty":10.529289,"median":15.636503,"eighty":23.565529,"marketCap":8629005598},{"date":"2023-08-11","current":15.021503,"twenty":10.529289,"median":15.580248,"eighty":23.505216,"marketCap":7982426462},{"date":"2023-08-18","current":14.336139,"twenty":10.527811,"median":15.479866,"eighty":23.331412,"marketCap":7618224175},{"date":"2023-08-25","current":13.816589,"twenty":10.527811,"median":15.457499,"eighty":23.140478,"marketCap":7342135345},{"date":"2023-09-01","current":14.325085,"twenty":10.527811,"median":15.436061,"eighty":23.017353,"marketCap":7612349945},{"date":"2023-09-08","current":14.283324,"twenty":10.527811,"median":15.413623,"eighty":22.879952,"marketCap":7590158407},{"date":"2023-09-15","current":14.129793,"twenty":10.527811,"median":15.374744,"eighty":22.767533,"marketCap":7508571874},{"date":"2023-09-22","current":13.785883,"twenty":10.527811,"median":15.309108,"eighty":22.706944,"marketCap":7325818038},{"date":"2023-09-29","current":14.172782,"twenty":10.527811,"median":15.27339,"eighty":22.677767,"marketCap":7531416103},{"date":"2023-10-06","current":13.779741,"twenty":10.527811,"median":15.262702,"eighty":22.64312,"marketCap":7322554577},{"date":"2023-10-13","current":13.487418,"twenty":10.527811,"median":15.243184,"eighty":22.526635,"marketCap":7167213816},{"date":"2023-10-20","current":14.376671,"twenty":10.527811,"median":15.201157,"eighty":22.411528,"marketCap":7639763020},{"date":"2023-10-27","current":13.912392,"twenty":10.496539,"median":15.173462,"eighty":22.367072,"marketCap":7393045342},{"date":"2023-11-03","current":13.820274,"twenty":10.496539,"median":15.138654,"eighty":22.317143,"marketCap":7344093422},{"date":"2023-11-10","current":14.277323,"twenty":10.496539,"median":15.061958,"eighty":22.22978,"marketCap":7535570913},{"date":"2023-11-17","current":14.780623,"twenty":10.496539,"median":15.021503,"eighty":22.15583,"marketCap":7801212876},{"date":"2023-11-24","current":15.25086,"twenty":10.496539,"median":15.009619,"eighty":22.022712,"marketCap":8049403907},{"date":"2023-12-01","current":15.843554,"twenty":10.496539,"median":15.009619,"eighty":21.901235,"marketCap":8362228019},{"date":"2023-12-08","current":16.062753,"twenty":10.506963,"median":15.011,"eighty":21.795732,"marketCap":8477921234},{"date":"2023-12-15","current":17.3706,"twenty":10.506963,"median":15.011,"eighty":21.679354,"marketCap":9168202539},{"date":"2023-12-22","current":18.113917,"twenty":10.506963,"median":15.011,"eighty":21.433384,"marketCap":9560525341},{"date":"2023-12-29","current":17.842061,"twenty":10.496539,"median":15.009619,"eighty":21.326,"marketCap":9417039901},{"date":"2024-01-05","current":17.467341,"twenty":10.486115,"median":15.005984,"eighty":21.234604,"marketCap":9219262673},{"date":"2024-01-12","current":17.453871,"twenty":10.486115,"median":15.005984,"eighty":21.120088,"marketCap":9212153034},{"date":"2024-01-19","current":16.899138,"twenty":10.475691,"median":15.002349,"eighty":20.980035,"marketCap":8919365178},{"date":"2024-01-26","current":17.3706,"twenty":10.486115,"median":15.005984,"eighty":20.814457,"marketCap":9168202539},{"date":"2024-02-02","current":17.922883,"twenty":10.486115,"median":15.005984,"eighty":20.683615,"marketCap":9459697735},{"date":"2024-02-09","current":18.686183,"twenty":10.486115,"median":15.005984,"eighty":20.583615,"marketCap":10985606798},{"date":"2024-02-16","current":19.698509,"twenty":10.486115,"median":15.005984,"eighty":20.41758,"marketCap":11580753724},{"date":"2024-02-23","current":20.34766,"twenty":10.486115,"median":15.005984,"eighty":20.387521,"marketCap":11962389294},{"date":"2024-03-01","current":20.21609,"twenty":10.496539,"median":15.009619,"eighty":20.363509,"marketCap":11885039371},{"date":"2024-03-08","current":19.540843,"twenty":10.496539,"median":15.009619,"eighty":20.30354,"marketCap":11488061668},{"date":"2024-03-15","current":19.818118,"twenty":10.496539,"median":15.009619,"eighty":20.211387,"marketCap":11651071836},{"date":"2024-03-22","current":20.7054,"twenty":10.496539,"median":15.009619,"eighty":20.150353,"marketCap":12172704373},{"date":"2024-03-28","current":20.279157,"twenty":10.496539,"median":15.009619,"eighty":20.112251,"marketCap":11922116194},{"date":"2024-04-05","current":18.608981,"twenty":10.486115,"median":15.005984,"eighty":20.036024,"marketCap":10940219653},{"date":"2024-04-12","current":17.94352,"twenty":10.486115,"median":15.005984,"eighty":19.935245,"marketCap":10548995251},{"date":"2024-04-19","current":17.107344,"twenty":10.486115,"median":15.005984,"eighty":19.903989,"marketCap":10057407725},{"date":"2024-04-26","current":18.151204,"twenty":10.496539,"median":15.009619,"eighty":19.875368,"marketCap":10671093063},{"date":"2024-05-03","current":17.932646,"twenty":10.496539,"median":15.009619,"eighty":19.836377,"marketCap":10542602695},{"date":"2024-05-10","current":18.271901,"twenty":10.496539,"median":15.009619,"eighty":19.806729,"marketCap":10742050430},{"date":"2024-05-17","current":18.059867,"twenty":10.496539,"median":15.009619,"eighty":19.776483,"marketCap":10617395596},{"date":"2024-05-24","current":16.400624,"twenty":10.496539,"median":15.009619,"eighty":19.711387,"marketCap":10599723366},{"date":"2024-05-31","current":17.935553,"twenty":10.496539,"median":15.009619,"eighty":19.698524,"marketCap":11591747957},{"date":"2024-06-07","current":17.600906,"twenty":10.496539,"median":15.009619,"eighty":19.673702,"marketCap":11375465343},{"date":"2024-06-14","current":18.018731,"twenty":10.486115,"median":15.005984,"eighty":19.616361,"marketCap":11645506063},{"date":"2024-06-21","current":17.852375,"twenty":10.475691,"median":15.002349,"eighty":19.587636,"marketCap":11537989851},{"date":"2024-06-28","current":17.049581,"twenty":10.465841,"median":14.992749,"eighty":19.532395,"marketCap":11019144171},{"date":"2024-07-05","current":16.259486,"twenty":10.465841,"median":14.992749,"eighty":19.492985,"marketCap":10508505489},{"date":"2024-07-12","current":17.831921,"twenty":10.465841,"median":14.992749,"eighty":19.424433,"marketCap":11524770448},{"date":"2024-07-15","current":17.603132,"twenty":10.465841,"median":14.992749,"eighty":19.407219,"marketCap":11376904523},{"date":"2024-08-02","current":16.732573,"twenty":10.370878,"median":14.953018,"eighty":19.293859,"marketCap":10814262147},{"date":"2024-08-09","current":14.661163,"twenty":10.370878,"median":14.94661,"eighty":19.293859,"marketCap":10010642272},{"date":"2024-08-16","current":14.901555,"twenty":10.370878,"median":14.909204,"eighty":19.293859,"marketCap":10174781624},{"date":"2024-08-23","current":15.333352,"twenty":10.370878,"median":14.903132,"eighty":19.293859,"marketCap":10469613063},{"date":"2024-08-30","current":15.482123,"twenty":10.370878,"median":14.909442,"eighty":19.293859,"marketCap":10571193643},{"date":"2024-09-06","current":15.729772,"twenty":10.370878,"median":14.909442,"eighty":19.293859,"marketCap":10740288145},{"date":"2024-09-13","current":15.907571,"twenty":10.370878,"median":14.909442,"eighty":19.293859,"marketCap":10861689326},{"date":"2024-09-20","current":16.76028,"twenty":10.370878,"median":14.909442,"eighty":19.293859,"marketCap":11443919479},{"date":"2024-09-27","current":17.925953,"twenty":10.370878,"median":14.909442,"eighty":19.293859,"marketCap":12239840486},{"date":"2024-10-04","current":17.454241,"twenty":10.370878,"median":14.909442,"eighty":19.293859,"marketCap":11917755720},{"date":"2024-10-11","current":18.062931,"twenty":10.370878,"median":14.909442,"eighty":19.293859,"marketCap":12333368947},{"date":"2024-10-18","current":18.409457,"twenty":10.370878,"median":14.909442,"eighty":19.293859,"marketCap":12569977371},{"date":"2024-10-25","current":17.955888,"twenty":10.370878,"median":14.909442,"eighty":19.293859,"marketCap":12260280481},{"date":"2024-10-31","current":18.296065,"twenty":10.370878,"median":14.909442,"eighty":19.293859,"marketCap":12492553148},{"date":"2024-11-08","current":20.081837,"twenty":10.368694,"median":14.909323,"eighty":19.306707,"marketCap":13731960102},{"date":"2024-11-15","current":19.204353,"twenty":10.368694,"median":14.909323,"eighty":19.340934,"marketCap":13131936805},{"date":"2024-11-22","current":18.809314,"twenty":10.368694,"median":14.909323,"eighty":19.340934,"marketCap":12861809009},{"date":"2024-11-29","current":21.014269,"twenty":10.368694,"median":14.909323,"eighty":19.399288,"marketCap":14369556801},{"date":"2024-12-06","current":21.176825,"twenty":10.368694,"median":14.909323,"eighty":19.446613,"marketCap":14480712837},{"date":"2024-12-13","current":20.529324,"twenty":10.368694,"median":14.909323,"eighty":19.521759,"marketCap":14037951644},{"date":"2024-12-20","current":20.202395,"twenty":10.368694,"median":14.909323,"eighty":19.551168,"marketCap":13814397606},{"date":"2024-12-27","current":21.125061,"twenty":10.368694,"median":14.909323,"eighty":19.570422,"marketCap":14445316781},{"date":"2025-01-03","current":21.028799,"twenty":10.368694,"median":14.909323,"eighty":19.638705,"marketCap":14379492536},{"date":"2025-01-10","current":22.072247,"twenty":10.366511,"median":14.909204,"eighty":19.685026,"marketCap":15093002509},{"date":"2025-01-17","current":21.58821,"twenty":10.366511,"median":14.909204,"eighty":19.711387,"marketCap":14762018335},{"date":"2025-01-24","current":23.295506,"twenty":10.366511,"median":14.909204,"eighty":19.805112,"marketCap":15929467202},{"date":"2025-01-31","current":23.475317,"twenty":10.366511,"median":14.909204,"eighty":19.886187,"marketCap":16052421924},{"date":"2025-02-07","current":23.943057,"twenty":10.366511,"median":14.91833,"eighty":19.977275,"marketCap":16870277685},{"date":"2025-02-14","current":24.415536,"twenty":10.366511,"median":14.969107,"eighty":20.078996,"marketCap":17203186803},{"date":"2025-02-21","current":25.114175,"twenty":10.366511,"median":14.985059,"eighty":20.169163,"marketCap":17695447597},{"date":"2025-02-28","current":23.731799,"twenty":10.366511,"median":15.013799,"eighty":20.276786,"marketCap":16721425926},{"date":"2025-03-07","current":20.892539,"twenty":10.364327,"median":15.083895,"eighty":20.412684,"marketCap":14720883003},{"date":"2025-03-14","current":18.993855,"twenty":10.462558,"median":15.14291,"eighty":20.412684,"marketCap":13383070106},{"date":"2025-03-21","current":19.73457,"twenty":10.550466,"median":15.16449,"eighty":20.412684,"marketCap":13904977722},{"date":"2025-03-28","current":19.737199,"twenty":10.715172,"median":15.201157,"eighty":20.417936,"marketCap":13906830649},{"date":"2025-04-04","current":17.346751,"twenty":10.778494,"median":15.243184,"eighty":20.44318,"marketCap":12222520506},{"date":"2025-04-11","current":17.06449,"twenty":10.816494,"median":15.255829,"eighty":20.43698,"marketCap":12023639734},{"date":"2025-04-17","current":17.71141,"twenty":10.865514,"median":15.264459,"eighty":20.43698,"marketCap":12479459640},{"date":"2025-04-25","current":19.29803,"twenty":10.940628,"median":15.314128,"eighty":20.44318,"marketCap":13597391932},{"date":"2025-05-02","current":19.680221,"twenty":11.001606,"median":15.375255,"eighty":20.44318,"marketCap":13866683909},{"date":"2025-05-09","current":22.043496,"twenty":11.04723,"median":15.406189,"eighty":20.603959,"marketCap":15531847146},{"date":"2025-05-16","current":23.588916,"twenty":11.148223,"median":15.436208,"eighty":20.693806,"marketCap":16620750256},{"date":"2025-05-23","current":22.526626,"twenty":11.222603,"median":15.469307,"eighty":20.717941,"marketCap":16735030815},{"date":"2025-05-30","current":22.551799,"twenty":11.228077,"median":15.486905,"eighty":20.846226,"marketCap":16753731195},{"date":"2025-06-06","current":22.339865,"twenty":11.228077,"median":15.503622,"eighty":20.951814,"marketCap":16596286056},{"date":"2025-06-13","current":21.696758,"twenty":11.228077,"median":15.543848,"eighty":21.014269,"marketCap":16118521497},{"date":"2025-06-20","current":21.74629,"twenty":11.224544,"median":15.643594,"eighty":21.03788,"marketCap":16155319020},{"date":"2025-06-27","current":22.299243,"twenty":11.224544,"median":15.696245,"eighty":21.125061,"marketCap":16566107308},{"date":"2025-07-03","current":22.814549,"twenty":11.224544,"median":15.734825,"eighty":21.160567,"marketCap":16948928611},{"date":"2025-07-11","current":23.6348,"twenty":11.224544,"median":15.773314,"eighty":21.235333,"marketCap":17558292901},{"date":"2025-07-18","current":23.340456,"twenty":11.224544,"median":15.818016,"eighty":21.328091,"marketCap":17339624403},{"date":"2025-07-25","current":24.081616,"twenty":11.224544,"median":15.851297,"eighty":21.497397,"marketCap":17890232891},{"date":"2025-07-28","current":24.31644,"twenty":11.224544,"median":15.852126,"eighty":21.50522,"marketCap":18064683105}],"updateTime":1753807280916}}}