Results for “chinese-stocks”

Collects Chinese A-share stock data, fetching stock lists and daily, weekly, and monthly K-line history into a local SQLite database for quantitative analysis.

Stock quotes, history, search, compare, crypto via Yahoo.

查询A股、港股、美股个股/指数/ETF的详细数据，包括：K线/分时、财务报表（三大报表多期查询，支持跨市场批量对比）、资金流向、技术指标、筹码分析、股东结构、分红除权、业绩预告、公司简况、ETF基金数据（详情/持仓/净值）；以及大盘指数、行业/板块行情、板块成份股、板块区间涨幅排行、指数成份股、热搜、新股日历、投资日历等市场数据。

Track stocks, ETFs, indices, crypto (where available), and FX pairs with caching + provider fallbacks.

Analyze US stocks with fundamental and technical analysis, peer comparisons, and investment reports using real-time market data.

Screen US stocks using William O'Neil's CANSLIM growth stock methodology with composite scoring and weighted components.

查询中国地区的天气预报，支持15天及逐小时预报、各种生活指数

Stock quotes, history, search, compare, crypto via Yahoo.

Fetches stock quotes, search, history, comparisons, and crypto prices from Yahoo Finance via a read-only Python script.

Develops and backtests quantitative trading strategies for the Chinese securities market using the QMT terminal's built-in Python framework, covering data retrieval, order placement, and position management.

用于 A 股、港股、美股及其他股票市场的股票筛选、候选股构建、指定股票比较、行业筛选、主题概念筛选、产业链环节筛选、策略风格筛选和龙头识别。适用于用户要求找股票、筛股票池、比较指定股票、识别行业或主题龙头、按市场/行业/主题/产业链/投资风格/透明指标排序候选标的等场景。强调动态检索、权威信源、业务证据验证、透明分组和可解释结论；禁止隐藏评分、不可解释排名和确定性投资建议。

Analyze stocks and cryptocurrencies with 8-dimension scoring via AIsa API. Provides BUY/HOLD/SELL signals with confidence levels, entry/target/stop prices, and risk flags. Supports single or multi-ticker analysis with optional fast mode and JSON output. Use when the user asks to analyze a stock, check a ticker, or compare investments.

Produces structured US equity research and trading support: company snapshots, earnings analysis, valuation scenarios, catalysts, risks, and action plans with falsifiable claims.

Requires python3, and AISA_API_KEY. Uses the supplied AISA_API_KEY to send requests to https://api.aisa.one. Native-first ClawHub plugin for `stock-hot`. Ships the packaged AIsa skill with an `openclaw.plugin.json` manifest and a Claude-compatible bundle fallback. Hot Scanner — find the most trending and high-momentum stocks and crypto right now via AIsa API. Top gainers, losers, most active by volume, crypto highlights, news catalysts, and top 5 watchlist picks. Use when the user asks about trending stocks, what's hot, market movers, or momentum plays.

Use this skill for on-chain DEX operations: token search, swap quotes, DEX trading, wallet portfolio/balance queries, gas estimation, and transaction broadcasting across 20+ blockchains (Ethereum, Solana, Base, BSC, Arbitrum, Polygon, etc.). Use when user says: 'swap ETH for USDC', 'buy token on-chain', 'DEX swap', 'token search on-chain', 'wallet balance', 'portfolio value', 'gas price', 'broadcast transaction', 'trending on-chain tokens', 'hot tokens', 'token holders', 'token liquidity', 'smart money signal', 'whale signal', 'K-line on-chain', '链上交易', '链上swap', 'DEX交易', '买币', '链上行情', '钱包余额', '持仓', 'gas费', '广播交易', '链上热门币', '聪明钱', '巨鲸信号'. Powered by OKX Web3 DEX API with 500+ liquidity sources. MUST run node scripts — NEVER fabricate on-chain data. For CEX trading (Binance/OKX spot/futures), use aicoin-trading. For CEX market data (funding rates, OI, liquidation), use aicoin-market.

Generates a three-panel analysis for any ticker following Duan Yongping's seller-only options strategy: Sell Put at a willing-buy price, Covered Call for yield, and a VIX-based panic-buy signal.

Screen US stocks for Stockbee-style short-term momentum burst setups using 4% breakout, dollar breakout, range expansion, volume expansion, prior range contraction, close-location, failure filters, and risk-distance scoring.

Scans US equities for daily +20%/-20% movers, classifies catalysts and chart context, updates forward outcomes, and summarizes cohort patterns for research.

Upgrade of chinese-ppt for Chinese Beamer decks (xelatex + ctex + fandol, CUFE template). Same 7-section outline and X→M→Y framework, but adds (a) mandatory 1.3 line-spacing + 3pt paragraph spacing, (b) overflow-prevention line budget + balanced split-frame rules, (c) prose rewrites that strip AI-ish "关键比较/理论映射" labels and redundant 章节括号注释, (d) stricter CJK-space + middle-dot rules, (e) retrofit workflow for existing chinese-ppt decks, (f) mandatory local linespread reset inside TikZ / table / fixed-geometry frames. Use for "做中文学术PPT 2 版"、"中文 Beamer 改进版"、"答辩 PPT chinese-ppt2"、"防越界 PPT"等请求。用户在 Overleaf 编译，只产出 .tex + figures/，不要附加 compile 脚本。

Analyze weekly price charts for stocks, indices, crypto, or forex to identify trends, support/resistance, and probabilistic scenarios based purely on chart data.

Guides compliance with China's Personal Information Protection Law (PIPL, effective 1 November 2021). Covers consent requirements, cross-border transfer mechanisms (CAC security assessment, standard contracts, certification), separate consent triggers, and critical information infrastructure obligations. Keywords: PIPL, China data protection, CAC security assessment, cross-border transfer, separate consent, CIIO.

Professional US stock analysis with financial data, news, social sentiment, and multi-model AI. Comprehensive reports at $0.02-0.10 per analysis. Use when: the user needs market data, stock analysis, watchlists, or portfolio workflows.

Develop quantitative trading strategies with the vn.py framework, covering CTA, spread, and options strategies with support for 20+ broker gateways.

Tracks crypto portfolio values, wallet balances, market prices, CEX history, and Polymarket predictions from the command line.

Kalshi prediction market data (prices, odds, orderbooks, trades). Use for prediction markets, Kalshi, betting odds, election and sports betting, market forecasts. Provides real-time market data, event series information, and comprehensive trading analytics.

Analyzes global market conditions across US, European, and Asian indices, forex, commodities, and economic indicators to produce structured market reports with risk sentiment assessment.

China LLM Gateway - Unified interface for Chinese LLMs including Qwen, DeepSeek, GLM, Baichuan. OpenAI compatible, one API Key for all models. Use when: the user needs model routing, provider setup, or Chinese LLM access guidance.

下单交易工具。严格规则：(1) 所有订单必须通过 node scripts/exchange.mjs create_order 执行，禁止写自定义代码下单 (2) create_order 分两步：第一次返回预览，展示给用户等确认，用户说确认后第二次加 confirmed=true 执行 (3) 禁止自动确认，禁止跳过预览 (4) 平仓必须用 close_position，禁止用 create_order 构建平仓单。Trigger: 'buy', 'sell', 'order', 'long', 'short', 'leverage', 'close position', '买', '卖', '下单', '做多', '做空', '杠杆', '开仓', '平仓', '平掉', '关仓'.

Detect and humanize AI-generated Chinese text. 20+ rule detection categories plus statistical features (sentence-length CV, short-sentence fraction, comma density, perplexity, GLTR, DivEye) plus scene-aware LR fusion (rule × 0.2 + LR × 0.8) trained on three scenes: general / academic / longform 长文本 (≥1500 字)。Unified CLI: ./humanize {detect,rewrite,academic,style,compare}. 8 style transforms (casual/zhihu/xiaohongshu/wechat/academic/literary/weibo/novel)。 Multi-paragraph rewriting (paragraph length CV、跨段 trigram 重复) plus best-of-N humanize (默认 N=10 取最低 LR)。165 replacement patterns + CiLin 同义词词林 38873 with collision blacklist。 Academic paper AIGC reduction for CNKI/VIP/Wanfang (知网/维普/万方 AIGC 检测降重)。 Pure Python, no dependencies, offline。v5.0.0 — HC3 fused 准确率 95%、学术 hero 100→35 (-65)、 工作汇报 96→13 (-83)、长篇博客 96→41 (-55)。 Use when user says: "去AI味", "降AIGC", "人性化文本", "humanize chinese", "AI检测", "AIGC降重", "去除AI痕迹", "文本改写", "论文降重", "知网检测", "维普检测", "AI写作检测", "让文字更自然", "detect AI text", "humanize text", "reduce AIGC sc

Analyze stocks and cryptocurrencies using Yahoo Finance data. Supports portfolio management (create, add, remove assets), crypto analysis (Top 20 by market cap), and periodic performance reports (daily/weekly/monthly/quarterly/yearly). 8 analysis dimensions for stocks, 3 for crypto. Use for stock analysis, portfolio tracking, earnings reactions, or crypto monitoring.

Requires python3, and AISA_API_KEY. Uses the supplied AISA_API_KEY to send requests to https://api.aisa.one. Native-first ClawHub plugin for `stock-analysis`. Ships the packaged AIsa skill with an `openclaw.plugin.json` manifest and a Claude-compatible bundle fallback. Analyze stocks and cryptocurrencies with 8-dimension scoring via AIsa API. Provides BUY/HOLD/SELL signals with confidence levels, entry/target/stop prices, and risk flags. Supports single or multi-ticker analysis with optional fast mode and JSON output. Use when the user asks to analyze a stock, check a ticker, or compare investments.

This skill should be used when the user asks about crypto prices, market data, K-line charts, funding rates, open interest, long/short ratios, whale orders, liquidation data, crypto news, newsflash, Twitter crypto tweets, trending coins, airdrops, drop radar, airdrop research, project analysis, exchange listings, stock quotes, treasury holdings, or any crypto market query. Also use when user asks about configuring or checking AiCoin API key. Use when user says: 'BTC price', 'check price', 'show K-line', 'funding rate', 'open interest', 'whale orders', 'long/short ratio', 'crypto news', 'newsflash', 'ETF', '监管', '政策', 'trending coins', 'airdrop', 'drop radar', '查行情', '看价格', '大饼多少钱', 'K线', '资金费率', '多空比', '鲸鱼单', '新闻', '快讯', '新闻快讯', '热门币', '空投', '空投项目', '空投机会', '空投研报', '项目分析', '项目详情', '上了哪些交易所', '推特', 'Twitter', 'liquidation map', '配置AiCoin key', 'AiCoin API key', 'AiCoin key安全吗'. Covers 200+ exchanges with real-time data. MUST run node scripts to fetch real data. NEVER generate fake prices or hallucinate market

Screen S&P 500 stocks for Mark Minervini's Volatility Contraction Pattern (VCP) and detect historical VCPs in a single ticker's price path.

根据研究者提供的**研究计划书（Research Proposal）**执行基于中国制度环境的公司金融类实证研究全流程。**启动后第一件事：根据计划书的主题、识别策略、贡献边际与样本范围，从中国-context 英文顶级期刊池（JF/JFE/RFS/JFQA/MS/JCF/JBF/JAR/JAE/TAR/CAR/JIBS/China Economic Review/PBFJ 等 25+ 期刊）中推荐 5 本最匹配的目标期刊（[J1]–[J5]），等待研究者明确选定一本；该期刊决定 main.tex 的 bibliographystyle、Section 骨架、Introduction 风格与表注规范**。然后用 Python 完成数据清洗、描述性统计、基准回归、内生性检验（IV/2SLS、DML）、平行趋势、异质性、机制、稳健性检验与图表绘制。LaTeX 表格和图像严格遵循 template/ 示例格式，研究逻辑与排版严格遵循 rule/ 下的《通用实证研究逻辑与规范总结》与《回归表写作规范总结》。数据集与政策集从 asset/ 中按计划书中的关键词检索。**当计划书预期的实证结果无法实现时（系数不显著、平行趋势不通过、IV 弱工具、机制不成立等），skill 自动切换备选方案直至完成研究项目**。最终交付物：Python 代码 + LaTeX 表格 + 图像（.pdf/.png）。触发条件：研究者提交研究计划书（含 X→Y 假设、识别策略、样本、政策冲击等）。

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