dennisthiessen
ef523474ad
The 5-year backtest confirmed the EV gate adds negative value (high threshold = worst expectancy) and that 12-1 month momentum is the one price signal with a plausible, right-signed cross-sectional IC (~0.05). So "qualified" now means: clears the R:R + confidence floors AND the ticker ranks in the top `min_momentum_percentile` of the universe by 12-1 momentum that week. - qualification.py: drop expected_value_r / the EV gate; add a momentum-percentile gate (duck-typed `momentum_percentile`, only enforced when attached + threshold set, else defers to floors). Mirrored in frontend qualification.ts. - activation config/schema: min_expected_value -> min_momentum_percentile (default 80 = top quintile). ActivationSettings, DashboardPage (ranks/【shows】 momentum instead of EV), and the BacktestPanel sweep follow. - backtest: rank each ISO week's universe by 12-1 momentum, assign a percentile, and qualify the top slice; the sweep now sweeps the percentile cutoff. Also offload the backtest's per-ticker compute to a worker thread so the heavy ~5y run no longer blocks the API event loop (the "backend offline" flicker). Production setups don't carry momentum_percentile yet — wiring the scanner to attach it (a universe momentum-rank step) is the next step; until then the live gate defers to floors while the backtest measures the momentum selection. 330 backend tests pass; frontend build clean. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
102 lines
3.7 KiB
Python
102 lines
3.7 KiB
Python
"""Admin request/response schemas."""
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from typing import Literal
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from pydantic import BaseModel, Field
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class UserManagement(BaseModel):
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"""Schema for user access management."""
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has_access: bool
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class PasswordReset(BaseModel):
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"""Schema for resetting a user's password."""
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new_password: str = Field(..., min_length=6)
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class CreateUserRequest(BaseModel):
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"""Schema for admin-created user accounts."""
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username: str = Field(..., min_length=1)
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password: str = Field(..., min_length=6)
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role: str = Field(default="user", pattern=r"^(user|admin)$")
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has_access: bool = False
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class RegistrationToggle(BaseModel):
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"""Schema for toggling registration on/off."""
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enabled: bool
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class SystemSettingUpdate(BaseModel):
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"""Schema for updating a system setting."""
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value: str = Field(..., min_length=1)
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class DataCleanupRequest(BaseModel):
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"""Schema for data cleanup — delete records older than N days."""
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older_than_days: int = Field(..., gt=0)
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class JobToggle(BaseModel):
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"""Schema for enabling/disabling a scheduled job."""
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enabled: bool
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class RecommendationConfigUpdate(BaseModel):
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high_confidence_threshold: float | None = Field(default=None, ge=0, le=100)
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moderate_confidence_threshold: float | None = Field(default=None, ge=0, le=100)
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confidence_diff_threshold: float | None = Field(default=None, ge=0, le=100)
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signal_alignment_weight: float | None = Field(default=None, ge=0, le=1)
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sr_strength_weight: float | None = Field(default=None, ge=0, le=1)
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momentum_technical_divergence_threshold: float | None = Field(default=None, ge=0, le=100)
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fundamental_technical_divergence_threshold: float | None = Field(default=None, ge=0, le=100)
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class TickerUniverseUpdate(BaseModel):
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universe: Literal["sp500", "nasdaq100", "nasdaq_all"]
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class ActivationConfigUpdate(BaseModel):
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"""Activation gate: what counts as an actionable signal."""
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min_momentum_percentile: float | None = Field(default=None, ge=0, le=100)
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min_rr: float | None = Field(default=None, ge=0)
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min_confidence: float | None = Field(default=None, ge=0, le=100)
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min_target_probability: float | None = Field(default=None, ge=0, le=100)
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require_high_conviction: bool | None = None
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exclude_conflicts: bool | None = None
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class ScheduleConfigUpdate(BaseModel):
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"""Cron schedule for the pipelines + fundamentals. Crons are 5-field
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(min hour dom month dow); timezone is an IANA name (e.g. Europe/Berlin)."""
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schedule_timezone: str | None = Field(default=None, max_length=64)
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schedule_daily_pipeline_cron: str | None = Field(default=None, max_length=120)
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schedule_intraday_pipeline_cron: str | None = Field(default=None, max_length=120)
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schedule_fundamentals_cron: str | None = Field(default=None, max_length=120)
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class SentimentConfigUpdate(BaseModel):
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"""Runtime sentiment LLM config. api_key is write-only; omit/empty to keep
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the stored key."""
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provider: Literal["openai", "gemini", "deepseek", "xai", "openai_compatible"] | None = None
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model: str | None = Field(default=None, max_length=100)
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api_key: str | None = Field(default=None, max_length=400)
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base_url: str | None = Field(default=None, max_length=300)
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class SentimentTestRequest(BaseModel):
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ticker: str = Field(default="AAPL", max_length=10)
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class AlertConfigUpdate(BaseModel):
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"""Telegram alert config. bot_token is write-only; omit/empty to keep the
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stored token."""
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enabled: bool | None = None
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bot_token: str | None = Field(default=None, max_length=200)
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telegram_chat_id: str | None = Field(default=None, max_length=64)
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qualified_enabled: bool | None = None
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sr_proximity_enabled: bool | None = None
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score_drop_enabled: bool | None = None
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digest_enabled: bool | None = None
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