Aryan Singh
e1ac514f30
Introduces a dashboard-managed agent registry (`state/agents.json`) used by nightly research and market-open execution, including support for custom/disabled agents and per-agent time budgets. Expands personas to four agents (adds Maverick), shifts pick targets to include mandatory options, and updates prompts/finalization nudges to enforce option research without hard-failing runs. Strengthens execution safety by adding option-specific guardrails (conviction floor, premium cap, reserved option slot through trade/day/buying-power caps), validates OCC option symbols in schemas, and normalizes invalid option direction cases. The dashboard was refactored into modular views, adds an Agents admin tab, and improves live portfolio visibility with Alpaca-first data and snapshot fallback.
32 lines
1.4 KiB
Python
32 lines
1.4 KiB
Python
"""Risk guardrails. Generous-but-present defaults for a paper account.
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These are enforced programmatically in ``execution/guardrails.py`` — the LLM's
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requested sizing and stop/take levels are inputs that get clamped here, never trusted.
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"""
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from __future__ import annotations
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from pydantic import BaseModel
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class RiskConfig(BaseModel):
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max_position_pct: float = 0.10 # cap per single position, % of equity
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max_symbol_exposure_pct: float = 0.15 # aggregate cap per ticker across all agents
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max_trades_per_agent: int = 4 # 4 trades/day mandate (one of them an option)
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# NOTE: plan_orders runs once per persona against its own account, so this "day" cap
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# acts PER ACCOUNT. Kept equal to the per-agent cap on purpose.
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max_trades_per_day: int = 4
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allow_shorts: bool = True # shorts enabled; persona prompts decide when to use them
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default_stop_pct: float = 0.07
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default_take_pct: float = 0.15
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min_price: float = 3.0 # skip sub-$3 names
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max_price: float | None = None
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# --- options quality gate (the "high probability" mandate, enforced not just prompted) ---
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# Premium notional cap per option trade (% of equity). 0.10 so one large-cap 30-45DTE
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# contract (~$600-1000 premium) fits a $10k book — 0.05 made most contracts qty<1.
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max_option_weight_pct: float = 0.10
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min_option_conviction: float = 0.6 # drop option picks the agent itself isn't sure about
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DEFAULT_RISK = RiskConfig()
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