Celes Renata
4ffde8cc06
- Database migration 018 with 13 tables for trading engine state - Trading engine service (services/trading/) with 12 pure computation modules: position sizer, stop-loss manager, reserve pool, circuit breaker, risk tier controller, correlation matrix, tax lots, trading window, gradual entry, notifications, micro-trading, backtester - Core TradingEngine with pre-trade evaluation pipeline and integration wiring - FastAPI HTTP service with 14 endpoints (health, config, decisions, metrics, backtest) - Performance tracker with Sharpe ratio, drawdown, profit factor computation - 194 Python tests (165 property-based + 29 integration) - Frontend: 13 TanStack Query hooks, 7 dashboard panels, tabbed Trading Engine page - Helm chart entry, network policy, nginx proxy, ingress for trading-engine - Shared infrastructure: enums, Redis keys, TradingConfig in AppConfig
88 lines
2.7 KiB
Python
88 lines
2.7 KiB
Python
"""Risk tier auto-adjustment controller for the autonomous trading engine.
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Pure computation module — no DB access. Persistence of tier changes is
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handled by the caller. All methods operate on values passed in as
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arguments and return deterministic results.
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Tier ordering: conservative → moderate → aggressive
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"""
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from __future__ import annotations
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from services.trading.models import PerformanceMetrics
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# Ordered from lowest to highest risk.
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TIER_ORDER: list[str] = ["conservative", "moderate", "aggressive"]
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class RiskTierController:
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"""Evaluates performance metrics and determines whether the active
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risk tier should change.
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Downgrade conditions (any one triggers a downgrade by one level):
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- Trailing 30-day win rate < 40%
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- Current drawdown > 15%
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Upgrade conditions (ALL must be true):
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- Trailing 30-day win rate > 55%
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- Reserve pool > 20% of total portfolio
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- Current drawdown < 5%
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"""
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def __init__(self) -> None:
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# No configuration needed — uses TIER_ORDER for ordering.
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pass
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def evaluate(
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self,
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current_tier: str,
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metrics: PerformanceMetrics,
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reserve_pct: float,
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) -> str | None:
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"""Evaluate whether the tier should change based on performance.
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Parameters
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----------
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current_tier:
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The currently active tier name (e.g. ``"moderate"``).
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metrics:
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Latest portfolio performance metrics.
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reserve_pct:
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Reserve pool balance as a fraction of total portfolio value
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(e.g. 0.25 means 25%).
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Returns
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-------
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str | None
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The new tier name if a change is needed, or ``None`` if the
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current tier should remain.
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"""
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current_index = TIER_ORDER.index(current_tier)
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# --- Downgrade check (any condition triggers) ---
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should_downgrade = (
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metrics.win_rate < 0.40 or metrics.current_drawdown_pct > 0.15
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)
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if should_downgrade:
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if current_index > 0:
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return TIER_ORDER[current_index - 1]
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# Already at the lowest tier — no change.
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return None
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# --- Upgrade check (all conditions must be true) ---
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should_upgrade = (
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metrics.win_rate > 0.55
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and reserve_pct > 0.20
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and metrics.current_drawdown_pct < 0.05
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)
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if should_upgrade:
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if current_index < len(TIER_ORDER) - 1:
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return TIER_ORDER[current_index + 1]
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# Already at the highest tier — no change.
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return None
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# Neither condition met — stay at current tier.
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return None
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