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Generate trading signals using technical indicators and on-chain metrics. Use when receiving trading signals and alerts. Trigger with phrases like "get trading signals", "check indicators", or "analyze signals".
Audit LLM token cost estimates against actual API usage. Activate on 'cost verification', 'token estimate accuracy', 'API cost audit', 'estimation variance'. NOT for pricing lookups, budget
Build robust backtesting systems for trading strategies with proper handling of look-ahead bias, survivorship bias, and transaction costs. Use when developing trading algorithms, validating strategies, or building backtesting infrastructure.
Run a historical backtest using npx neural-trader with Rust/NAPI engine (8-19x faster) and walk-forward validation; Ed25519-sign the result for paper→live tamper evidence (ADR-126 Phase 4)
Regulator-grade feature attribution for any LSTM/Transformer signal — single-entry PageRank ranks the top-K features that drove the prediction (ADR-126 Phase 6, ADR-123 single-entry PR)
Mean-variance portfolio optimization via Conjugate Gradient — 40-60× faster than the legacy Neumann path (ADR-126 Phase 3, ADR-123 Wedge 8)
Build robust backtesting systems for trading strategies with proper handling of look-ahead bias, survivorship bias, and transaction costs. Use when developing trading algorithms, validating strategies, or building backtesting infrastructure.
Oracle Database with PL/SQL, RAC, and enterprise features. Use for enterprise systems.
使用mplfinance生成黑色背景的专业K线图，支持白灰涨跌配色、数据自动处理及预测信号叠加。
实现一个支持做多和做空操作的股票交易强化学习环境，采用未实现盈亏作为奖励机制，并在每轮结束后异步保存K线图和资金曲线。
Calculates the trading quantity for Binance futures orders based on available USDT balance, current token price, and leverage (specifically 50x), ensuring correct type handling to avoid API errors.
Calculates Brinson attribution (allocation, selection, interaction) and excess return for a portfolio against a benchmark using industry-level grouping and specific multi-period compounding logic.
Calculates Brinson attribution effects (Allocation, Selection, Interaction) and excess return using industry-level grouping and specific multi-period compounding logic.
Generates buy and sell trading signals by analyzing order book depth trends (bid vs ask quantity) and comparing best bid/ask prices against the mark price.
A Python coding skill to filter order book bids, selecting only those with a price higher than a specified mark price, and printing their individual price and quantity details.
Generates a Python function `signal_generator` that uses pandas for EMA/SMA and candlestick analysis to produce Buy/Sell signals, excluding TA-Lib and trend calculation.
Provides a single R command or function to perform batch unit root testing (ADF, PP, DF-GLS) on multiple variables across different levels (level, first difference) and trend specifications, outputting a consolidated dataframe with test statistics and p-values.
Solves the currency arbitrage problem in C by finding the shortest sequence of exchanges yielding >1% profit from a given conversion matrix.
AKShare financial data aggregator (18k+ stars). Free, no API key. Covers A-shares, US, HK, futures, macro, forex. Primary fallback for tushare and yfinance.
CCXT unified crypto exchange library (100+ exchanges). Free public market data. Fallback when OKX is unavailable.
Hyperliquid market data, account history, trade review.
Test backtest crypto trading strategies against historical data with performance metrics. Use when validating trading strategies with historical data. Trigger with phrases like "backtest strategy", "test trading signals", or "validate approach".
Execute review crypto wallet security including private key management and transaction signing. Use when auditing wallet security practices. Trigger with phrases like "audit wallet", "check security", or "verify signatures".
Real-time data streaming via WebSocket for spot and futures.
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