القائمة
Time-series market forecasting using the Kronos model with news-aware sentiment adjustment for OHLC price prediction
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Analyze financial text sentiment using FinBERT or LLM, returning a scored label (positive/negative/neutral) from -1.0 to 1.0
Search A-Share and HK stock tickers by name or code and retrieve OHLCV historical price data
Fetch real-time hot finance news and unified trend reports from multiple sources (财联社, WallStreetCN, Weibo, Zhihu, etc.) and Polymarket prediction data
Perform finance web searches across multiple engines (Jina, DuckDuckGo, Baidu) and local RAG document retrieval with smart search caching
Generate Draw.io XML diagrams to visualize finance logic flows, investment theses, and signal transmission chains
Plan, write, and assemble professional financial reports by clustering signals into themes, writing analysis sections, and compiling a final structured report
| name | AlphaEar Predictor |
| description | Time-series market forecasting using the Kronos model with news-aware sentiment adjustment for OHLC price prediction |
| category | financial-modeling/forecasting |
| tags | ["forecasting","time-series","kronos","quantitative"] |
This skill utilizes the Kronos model (via KronosPredictorUtility) to perform time-series forecasting and adjust predictions based on news sentiment.
Workflow:
scripts/kronos_predictor.py (via KronosPredictorUtility) to generate the technical/quantitative forecast.references/PROMPTS.md to subjectively adjust the numbers based on latest news/logic.Key Tools:
KronosPredictorUtility.get_base_forecast(df, lookback, pred_len, news_text): Returns List[KLinePoint].Example Usage (Python):
from scripts.utils.kronos_predictor import KronosPredictorUtility
from scripts.utils.database_manager import DatabaseManager
db = DatabaseManager()
predictor = KronosPredictorUtility()
# Forecast
forecast = predictor.predict("600519", horizon="7d")
print(forecast)
This skill requires the Kronos model and an embedding model.
Kronos Model:
exports/models directory exists in the project root.kronos_news_v1.pt) in exports/models/.Environment Variables:
EMBEDDING_MODEL: Path or name of the embedding model (default: sentence-transformers/all-MiniLM-L6-v2).KRONOS_MODEL_PATH: Optional path to override model loading.torchtransformerssentence-transformerspandasnumpyscikit-learn