dennisthiessen
099846513b
Two changes so the cross-sectional signal results can actually be trusted. (a) History depth — the binding constraint. Ingestion defaulted to 365 days, so long-lookback factors (12-month momentum, 52-week high) were only computable on a handful of weeks at the tail, and every IC reflected a single market regime. - New `settings.ohlcv_history_days` (default 1825 ≈ 5y); new tickers backfill this far instead of 1 year. - New manual "data_backfill" job (Admin → Jobs) re-fetches the full window for every ticker, ignoring incremental resume — run once to deepen existing 1-year histories. Idempotent (upsert); resumes after rate limits. (b) Factor-IC honesty. The IC was averaged over weekly rebalances whose 30-day forward windows overlap, inflating the t-stat ~sqrt(6)x. - IC now measured on NON-OVERLAPPING windows (weeks thinned to ~HORIZON apart). - Each signal carries a `reliable` flag (>= 12 independent windows); BacktestPanel greys out and de-stars thin signals so a lucky 9-week IC of 0.3 can't masquerade as an edge. 332 backend tests pass; frontend build clean. No migration (config + job + an added JSON field on the cached backtest report). Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
85 lines
3.0 KiB
Python
85 lines
3.0 KiB
Python
from pydantic_settings import BaseSettings, SettingsConfigDict
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class Settings(BaseSettings):
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model_config = SettingsConfigDict(env_file=".env", env_file_encoding="utf-8")
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# Database
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database_url: str = "postgresql+asyncpg://stock_backend:changeme@localhost:5432/stock_data_backend"
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# Auth
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jwt_secret: str = "change-this-to-a-random-secret"
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jwt_expiry_minutes: int = 60
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# OHLCV Provider — Alpaca Markets
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alpaca_api_key: str = ""
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alpaca_api_secret: str = ""
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# Sentiment Provider — Gemini with Search Grounding (legacy)
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gemini_api_key: str = ""
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gemini_model: str = "gemini-2.0-flash"
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# Sentiment Provider — OpenAI
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openai_api_key: str = ""
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openai_model: str = "gpt-4o-mini"
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openai_sentiment_batch_size: int = 5
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# Sentiment Provider — DeepSeek / xAI (OpenAI-compatible; optional env fallback)
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deepseek_api_key: str = ""
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xai_api_key: str = ""
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# Fundamentals Provider — Financial Modeling Prep
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fmp_api_key: str = ""
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# Fundamentals Provider — Finnhub (optional fallback)
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finnhub_api_key: str = ""
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# Fundamentals Provider — Alpha Vantage (optional fallback)
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alpha_vantage_api_key: str = ""
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# Alerts — Telegram (optional env fallback; can also be set in Admin)
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telegram_bot_token: str = ""
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telegram_chat_id: str = ""
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# Scheduled Jobs
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data_collector_frequency: str = "daily"
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sentiment_poll_interval_minutes: int = 30
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# Sentiment search-budget controls (Gemini grounding free tier = 5000/month).
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# Only fetch sentiment for relevant tickers (watchlist + open trades + top-N by
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# composite), skip ones refreshed within fresh_hours, and cap per run.
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sentiment_fresh_hours: int = 72
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sentiment_max_per_run: int = 25
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sentiment_top_composite: int = 30
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fundamental_fetch_frequency: str = "weekly" # quarterly-ish data; weekly conserves API quota
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rr_scan_frequency: str = "daily"
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alerts_frequency: str = "hourly"
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fundamental_rate_limit_retries: int = 3
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fundamental_rate_limit_backoff_seconds: int = 15
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# Pause between tickers in the bulk fundamentals job. Free tiers throttle
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# hard (Finnhub ~60 calls/min, ~3 calls/ticker → ~3s/ticker); without
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# spacing the job bursts straight into 429s. 0 disables.
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fundamental_request_spacing_seconds: float = 3.0
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# Scoring Defaults
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default_watchlist_auto_size: int = 10
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default_rr_threshold: float = 1.5
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# Outcome evaluation: trading days before an undecided setup expires
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outcome_evaluation_max_bars: int = 30
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# OHLCV history depth to fetch. New tickers backfill this far; the manual
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# "data_backfill" job re-fetches the full window for everyone. ~5 years so
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# long-lookback factors (12-month momentum, 52-week high) and multi-regime
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# backtests become computable. ~252 trading days/year.
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ohlcv_history_days: int = 1825
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# Database Pool
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db_pool_size: int = 5
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db_pool_timeout: int = 30
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# Logging
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log_level: str = "INFO"
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settings = Settings()
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