Loading...
Loading...
Found 67 Skills
Perform quantitative analysis of returns, correlations, risk factors, and portfolio optimization. Statistical modeling with institutional-grade rigor.
RQAlpha 米筐开源事件驱动回测框架。支持A股和期货，模块化架构，可自由扩展；当用户需要使用 rqalpha 进行策略回测、模拟交易或Mod插件开发时使用。
Use when a user asks to build, optimize, backtest, rebalance, or analyze a stock portfolio with Mean-CVaR, efficient frontiers, scenario generation, or NVIDIA cuOpt.
Trade mean reversion setups in the style of Scarface Trades, the mean reversion specialist known for mathematical precision and statistical edge. Emphasizes standard deviation bands, RSI extremes, and calculated entries with defined risk. Use when trading overextended moves, fading extremes, or building systematic reversion strategies.
This skill should be used when the user asks to forecast aggregate sentiment and opinion dynamics over time—sentiment indices from text streams; temporal rollups; leading/lagging KPI links; time-series and sequence models (ARIMA, Prophet, state-space, ML); nowcasting; spikes, bots, and bias; walk-forward backtests; intervals and scenarios; volume/velocity/topic features; BI or brand dashboards. Triggers: sentiment forecasting, forecast sentiment, sentiment index, opinion trend forecast, social sentiment time series, brand sentiment trajectory, nowcast sentiment, sentiment leading indicator, aggregate polarity forecast, sentiment backtest, walk-forward sentiment, sentiment spike prediction. Not for per-text labeling (sentiment-analysis-engineer), demand forecasting without sentiment (predictive-logistics-developer, data-scientist), trade advice (methodology only), marketing copy (content-creator), macro without text sentiment (financial-analyst partial).
Backtrader 开源量化回测框架，支持多数据源、多策略、多周期回测与实盘交易，纯Python实现。当用户明确提及backtrader相关策略开发时使用。
Implements algorithmic trading strategies using quantitative models and financial APIs for automated trading.