「ohlc」の検索結果

针对金融K线OHLC数据进行降维分析，包括数据预处理（变化率计算、标准化）、标准PCA降维以及基于随机化SVD的伪PCA降维的Python实现步骤。

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针对金融K线OHLC数据进行降维分析，包括数据预处理（变化率计算、标准化）、标准PCA降维以及基于随机化SVD的伪PCA降维的Python实现步骤。

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CCXT command-line interface (ccxt-cli) for interacting with 100+ cryptocurrency exchanges directly from the terminal — no code required. Covers installing the CLI, calling any unified CCXT method (fetchTicker, fetchOHLCV, createOrder, fetchBalance), passing arguments and exchange-specific params, authenticating with API keys, sandbox/testnet mode, streaming live tickers and orderbooks over WebSocket, plotting OHLCV charts, and scripting with raw JSON output. Use when the user wants to query an exchange, test API credentials, place or inspect orders, or debug exchange requests from the command line or in shell scripts.

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Use this skill when writing analytical SQL over time-series data with the TimescaleDB Toolkit (timescaledb_toolkit extension) hyperfunctions: approximate percentiles, statistical summaries, time-weighted averages, counter/gauge rates, uptime/heartbeat tracking, state durations, OHLC candlesticks, approximate distinct counts, top-N, and downsampling. **Trigger when user asks to:** - Compute percentiles/medians/p95/p99 over large or rolled-up time-series data - Compute rates or deltas from monotonic counters (Prometheus-style) or gauges - Compute time-weighted averages or integrals over irregularly sampled data - Track uptime/downtime from heartbeats, or time spent in each state - Build OHLC/candlestick or VWAP data for financial ticks - Store re-aggregatable summaries in continuous aggregates (two-step aggregation, rollup) - Approximate COUNT DISTINCT, find top-N / most frequent values, or downsample for charts **Keywords:** timescaledb_toolkit, hyperfunctions, percentile_agg, uddsketch, tdigest, approx_percentile, stats_agg, time_weight, counter_agg, gauge_agg, heartbeat_agg, state_agg, candlestick_agg, hyperloglog, approx_count_distinct, min_n, max_n, mcv_agg, lttb, asap_smooth, rollup, two-step aggregation

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Provides multi-school trading Q&A, chart/OHLCV analysis, annotation, and fresh-market workflows covering ICT/SMC, ChanLun, Wyckoff, Price Action, Order Flow, VSA, and Elliott Wave. Use for trading concepts; capability-discovery questions about available analysis lenses, Schools, models, modes, or data sources; attached charts; pasted OHLCV; chart annotation; or asset-plus-timeframe requests across crypto, stocks, or forex. Defaults unselected market analysis to strict ICT/SMC, honors explicit School/source selectors, and fails closed when no native analyzer exists. Phase 1 comparison is Q&A-only; fetch fresh Mobius Quant API data only after the capability gate.

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Market data preparation including OHLCV resampling, gap handling, anomaly detection, normalization, and multi-source merging

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Ingest and normalize market data into OHLCV vectors stored by symbol and date for later pattern detection. Use when you need to load price and volume history for a symbol before running pattern detection or comparison. Read-only analysis; it never places orders.

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Detect and classify candlestick patterns from ingested OHLCV data

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Per-token details for a specific token identified by keyword, symbol, or contract address: (1) search — find tokens by keyword/symbol/contract; (2) meta — static info: name, symbol, logo, social links, creator, official website; (3) dynamic — real-time market data: price, 24h change, volume, holder count, liquidity; (4) kline — OHLCV candlestick data for technical analysis. Use for: "price of $X", "search for token Y", "kline chart for $Z", "who created $W", "social links for $V", "holder count of $U", "candlestick data", "find the contract address of <token>".

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Seasonal/calendar-effect strategy. Generates trading signals from time-based patterns such as month-of-year effects and day-of-week effects. Suitable for any OHLCV data.

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Paid capability marketplace for global multi-asset data; use it when free Vibe-Trading sources lack coverage, depth, or provider quality, and keep free sources as the default for routine OHLCV.

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Core technical indicator collection (trend EMA/ADX + mean-reversion BB/RSI + volume-price OBV/volume ratio), generates a composite signal via three-dimensional voting. Pure pandas implementation for any OHLCV data.

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Volatility strategy. Trades mean reversion based on percentile ranking of historical volatility (HV). Suitable for any OHLCV data.

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yfinance global market data interface — retrieve OHLCV and research data for US, HK, and Canadian stocks, ETFs, and indices via Yahoo Finance. Free, no API key required.

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Machine-learning predictive strategy based on sklearn walk-forward training, feature engineering, and signal generation. Suitable for any OHLCV data.

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Token deep dive — info, OHLCV, holders, flows, flow intelligence, who bought/sold, DEX trades, PnL, perp trades, perp positions, perp PnL leaderboard. Use when researching a specific token in depth.

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HARD BLOCK — never use for prediction-market/Polymarket UpDown queries; route to okx-dapp-discovery when a named DApp (Polymarket/Aave/Hyperliquid/PancakeSwap/Morpho) appears with a timeframe, or 涨跌/updown for BTC/ETH/SOL/XRP/BNB/DOGE/HYPE. Otherwise, read-only on-chain DEX data, 6 groups: TOKEN (search, hot/热门, liquidity, holders/whale, risk metadata, cluster/持仓集中度, trade history, top traders); MARKET (price/价格, K线/OHLC, index price, wallet PnL/胜率, trade history); SIGNAL (smart money/KOL/whale tracking, buy signals/信号, leaderboard/牛人榜); SOCIAL (news/新闻, sentiment/情绪, token vibe/热度, KOL leaderboard); TRENCHES (pump.fun/meme launches/新盘/扫链, dev reputation, bundle/sniper detection/捆绑狙击者, co-investor — read-only; buy/snipe → okx-dapp-discovery); WS (onchainos ws CLI, or custom WebSocket script/脚本). Also owns Market API payment/x402, quota/额度, and MARKET_API_*_OVER_QUOTA/confirming:true for all 6 groups.

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Complete Birdeye API integration for real-time DeFi data across Solana and 15 other chains. Use for token prices, OHLCV charts, market discovery, on-chain trader intelligence, holder analysis, wallet portfolio & P&L, and WebSocket streams for live prices and whale alerts.

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Access real-time and historical stock market data, forex rates, cryptocurrency prices, commodities, economic indicators, and 50+ technical indicators via the Alpha Vantage API. Use when fetching stock prices (OHLCV), company fundamentals (income statement, balance sheet, cash flow), earnings, options data, market news/sentiment, insider transactions, GDP, CPI, treasury yields, gold/silver/oil prices, Bitcoin/crypto prices, forex exchange rates, or calculating technical indicators (SMA, EMA, MACD, RSI, Bollinger Bands). Requires a free API key from alphavantage.co.

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Access DeFi data from DexPaprika: token prices, liquidity pools, OHLCV, transactions across 34+ blockchains and 30M+ pools. Free, no API key needed. Install MCP: add https://mcp.dexpaprika.com/sse as SSE server, or install plugin: /plugin marketplace add coinpaprika/claude-marketplace

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Access cryptocurrency market data from CoinPaprika: prices, tickers, OHLCV, exchanges, contract lookups for 12,000+ coins and 350+ exchanges. Free tier, no API key needed. Install MCP: add https://mcp.coinpaprika.com/sse as SSE server, or install plugin: /plugin marketplace add coinpaprika/claude-marketplace

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Read Hyperliquid (app.hyperliquid.xyz) perp and spot market data through opencli and Hyperliquid's public info API: mark, oracle, and mid prices, 24h change, funding rates (hourly and annualized APR), open interest, volume, the L2 order book, OHLCV candles, funding history, and cross-venue funding comparisons (Hyperliquid vs Binance vs Bybit) for funding arbitrage. Use this skill whenever the user mentions Hyperliquid (HL, HL DEX, hyperliquid.xyz) or asks about its perps, spot pairs such as PURR, funding, open interest, order book, or candles. Read-only market data: no account, order, or transfer operations.

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Runs a declarative strategy spec over OHLCV bars with the manifoldbt Rust engine, pairs the fill log into round trips, and emits the eight inputs the backtest-expert skill scores. Use when the user wants to execute a backtest, measure a rule they have described, obtain win rate / average win / average loss / max drawdown from real bars, or feed backtest-expert with measured numbers instead of estimates.

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在 Remotion 项目中创建带动画的金融 K 线图（蜡烛图）。涵盖数据获取（Yahoo Finance）、 插件架构（config / timeline / Scene / plugin）、Canvas 逐帧绘制、深色交易终端风格、 以及 Remotion Studio 预览和渲染输出。触发词：K线图、蜡烛图、candlestick、OHLC、 股票动画、金融图表视频、Remotion 图表。

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