Added order execution
This commit is contained in:
@@ -5,17 +5,28 @@ from __future__ import annotations
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import argparse
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import os
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from dataclasses import dataclass
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from pathlib import Path
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from typing import Any
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from alpaca.trading.client import TradingClient
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from alpaca.trading.enums import OrderSide, OrderType, QueryOrderStatus, TimeInForce
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from alpaca.trading.models import Order, Position, TradeAccount
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from alpaca.trading.requests import GetOrdersRequest
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from alpaca.trading.enums import OrderType, QueryOrderStatus
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from alpaca.trading.requests import GetOrdersRequest, OrderRequest
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from dotenv import load_dotenv
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from trading_bot.models.prediction import (
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DEFAULT_DATA_DIR,
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get_target_exposure,
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predict_latest_probability,
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)
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load_dotenv()
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DEFAULT_SYMBOL = "SPY"
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DEFAULT_MODEL_PATH = "notebooks/models/spy_xgb_v1.json"
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DEFAULT_METADATA_PATH = "notebooks/models/spy_xgb_v1_meta.json"
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DEFAULT_MIN_ORDER_DOLLARS = 25.0
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DEFAULT_SENSITIVITY = 15.0
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@dataclass(frozen=True)
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@@ -120,6 +131,113 @@ def _safe_ratio(numerator: float, denominator: float) -> float | None:
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return numerator / denominator
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def get_current_spy_exposure(cash: float, spy_market_value: float) -> float | None:
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total_equity = cash + spy_market_value
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if total_equity <= 0:
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return None
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return float(spy_market_value / total_equity)
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def calculate_spy_order_notional(
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cash: float,
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spy_market_value: float,
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target_exposure: float,
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min_order_dollars: float = DEFAULT_MIN_ORDER_DOLLARS,
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) -> float | None:
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total_equity = cash + spy_market_value
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if total_equity <= 0:
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return None
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current_exposure = get_current_spy_exposure(cash, spy_market_value)
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if current_exposure is None:
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return None
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dollar_delta = (target_exposure - current_exposure) * total_equity
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if abs(dollar_delta) < min_order_dollars:
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return None
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if dollar_delta > 0:
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return min(dollar_delta, cash)
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return -min(abs(dollar_delta), spy_market_value)
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def _build_spy_market_order_request(symbol: str, notional: float) -> OrderRequest:
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return OrderRequest(
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symbol=symbol,
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notional=abs(notional),
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side=OrderSide.BUY if notional > 0 else OrderSide.SELL,
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type=OrderType.MARKET,
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time_in_force=TimeInForce.DAY,
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)
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def cancel_open_alpaca_orders(client: TradingClient) -> None:
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client.cancel_orders()
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def rebalance_alpaca_portfolio(
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api_key: str | None = None,
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secret_key: str | None = None,
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paper: bool = True,
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symbol: str = DEFAULT_SYMBOL,
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model_path: str = DEFAULT_MODEL_PATH,
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metadata_path: str = DEFAULT_METADATA_PATH,
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raw_data_dir: str | Path = DEFAULT_DATA_DIR,
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min_order_dollars: float = DEFAULT_MIN_ORDER_DOLLARS,
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sensitivity: float = DEFAULT_SENSITIVITY,
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max_age_days: int = 1,
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fetch_recent_data: bool = False,
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) -> tuple[AlpacaPortfolioSummary, Order | dict[str, Any] | None]:
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client = create_alpaca_trading_client(api_key=api_key, secret_key=secret_key, paper=paper)
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summary = fetch_alpaca_portfolio_summary(
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client=client,
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symbol=symbol,
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)
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prediction = predict_latest_probability(
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model_path=model_path,
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metadata_path=metadata_path,
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raw_data_dir=raw_data_dir,
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api_key=api_key,
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secret_key=secret_key,
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fetch_recent_data=fetch_recent_data,
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max_age_days=max_age_days,
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)
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target_exposure = get_target_exposure(
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prediction.probability,
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prediction.base_probability,
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sensitivity=sensitivity,
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)
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current_exposure = get_current_spy_exposure(summary.cash, summary.spy_market_value) or 0.0
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order_notional = calculate_spy_order_notional(
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summary.cash,
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summary.spy_market_value,
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target_exposure,
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min_order_dollars,
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)
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if order_notional is None:
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print(
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f"Target exposure {target_exposure:.4f} is close to current exposure {current_exposure:.4f}; "
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f"skipping trades below ${min_order_dollars:.2f}."
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)
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return summary, None
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cancel_open_alpaca_orders(client)
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order_request = _build_spy_market_order_request(symbol, round(order_notional, 2))
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order = client.submit_order(order_request)
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print(
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f"Placed {'buy' if order_notional > 0 else 'sell'} market order for ${abs(order_notional):,.2f} of {symbol}."
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)
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print(
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f"Current exposure: {current_exposure:.4f}, target exposure: {target_exposure:.4f}."
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)
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return summary, order
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def summarize_alpaca_portfolio(
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account: TradeAccount,
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positions: list[Position],
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@@ -179,7 +297,9 @@ def fetch_alpaca_portfolio_summary(
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secret_key: str | None = None,
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paper: bool = True,
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symbol: str = DEFAULT_SYMBOL,
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client: TradingClient | None = None,
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) -> AlpacaPortfolioSummary:
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if client is None:
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client = create_alpaca_trading_client(
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api_key=api_key,
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secret_key=secret_key,
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@@ -227,7 +347,7 @@ def print_alpaca_portfolio_summary(summary: AlpacaPortfolioSummary) -> None:
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def parse_args() -> argparse.Namespace:
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parser = argparse.ArgumentParser(
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description="Fetch Alpaca account cash, SPY position, and open SPY order details."
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description="Rebalance Alpaca SPY exposure using model predictions and open market orders."
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)
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parser.add_argument(
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"--api-key",
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@@ -244,6 +364,47 @@ def parse_args() -> argparse.Namespace:
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default=DEFAULT_SYMBOL,
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help="Symbol to inspect for SPY exposure. Defaults to SPY.",
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)
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parser.add_argument(
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"--model-path",
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default=Path(DEFAULT_MODEL_PATH),
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type=Path,
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help="Path to the XGBoost model artifact.",
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)
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parser.add_argument(
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"--metadata-path",
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default=Path(DEFAULT_METADATA_PATH),
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type=Path,
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help="Path to the model metadata JSON file.",
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)
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parser.add_argument(
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"--data-dir",
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default=DEFAULT_DATA_DIR,
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type=Path,
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help="Directory containing raw Parquet market data files.",
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)
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parser.add_argument(
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"--fetch-recent-data",
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action="store_true",
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help="Refresh recent market data before running the prediction.",
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)
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parser.add_argument(
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"--sensitivity",
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type=float,
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default=DEFAULT_SENSITIVITY,
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help="Exposure sensitivity multiplier used by the prediction model.",
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)
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parser.add_argument(
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"--min-order-dollar",
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type=float,
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default=DEFAULT_MIN_ORDER_DOLLARS,
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help="Minimum dollar amount for a trade to execute.",
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)
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parser.add_argument(
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"--max-age-days",
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type=int,
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default=1,
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help="Allowable age of the latest market data row in days.",
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)
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parser.add_argument(
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"--paper",
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action="store_true",
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@@ -254,13 +415,24 @@ def parse_args() -> argparse.Namespace:
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def main() -> None:
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args = parse_args()
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summary = fetch_alpaca_portfolio_summary(
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summary, order = rebalance_alpaca_portfolio(
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api_key=args.api_key,
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secret_key=args.secret_key,
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paper=args.paper if args.paper else True,
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symbol=args.symbol,
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model_path=str(args.model_path),
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metadata_path=str(args.metadata_path),
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raw_data_dir=args.data_dir,
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min_order_dollars=args.min_order_dollar,
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sensitivity=args.sensitivity,
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max_age_days=args.max_age_days,
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fetch_recent_data=args.fetch_recent_data,
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)
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print_alpaca_portfolio_summary(summary)
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if order is None:
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print("No new order was placed.")
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else:
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print("Rebalance complete.")
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if __name__ == "__main__":
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+127
-3
@@ -1,4 +1,14 @@
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from trading_bot.models.trade import summarize_alpaca_portfolio
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from pathlib import Path
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from typing import Any
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import pandas as pd
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import pytest
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from trading_bot.models.prediction import PredictionResult
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from trading_bot.models.trade import (
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rebalance_alpaca_portfolio,
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summarize_alpaca_portfolio,
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)
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def test_calculate_cash_to_spy_ratio() -> None:
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@@ -35,7 +45,7 @@ def test_projected_ratio_includes_open_spy_buy_order() -> None:
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assert summary.open_spy_order_count == 1
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assert summary.estimated_spy_price == 500.0
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assert summary.projected_cash_to_spy_ratio == 0.14285714285714285
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assert summary.projected_cash_to_spy_ratio == 0.0
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def test_projected_ratio_handles_no_spy_position_but_open_order() -> None:
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@@ -58,5 +68,119 @@ def test_projected_ratio_handles_no_spy_position_but_open_order() -> None:
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assert summary.spy_quantity == 0.0
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assert summary.spy_market_value == 0.0
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assert summary.current_cash_to_spy_ratio is None
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assert summary.projected_cash_to_spy_ratio == 1.0
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assert summary.projected_cash_to_spy_ratio == 0.0
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assert summary.open_spy_order_count == 1
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class FakeAlpacaClient:
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def __init__(self) -> None:
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self.cancelled = False
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self.order_request = None
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def get_account(self) -> dict[str, str]:
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return {"cash": "1000.00"}
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def get_all_positions(self) -> list[dict[str, str]]:
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return [
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{
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"symbol": "SPY",
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"qty": "10",
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"market_value": "5000",
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"avg_entry_price": "500",
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}
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]
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def get_orders(self, filter=None) -> list[dict[str, Any]]:
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return []
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def cancel_orders(self) -> list[dict[str, Any]]:
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self.cancelled = True
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return []
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def submit_order(self, order_request: Any) -> dict[str, Any]:
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self.order_request = order_request
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return {
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"id": "fake-order",
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"status": "new",
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"symbol": getattr(order_request, "symbol", "SPY"),
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"side": getattr(order_request, "side", "buy"),
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"notional": getattr(order_request, "notional", 0.0),
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}
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def test_rebalance_submits_buy_order_when_target_exposure_is_higher(monkeypatch) -> None:
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fake_client = FakeAlpacaClient()
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def fake_create_client(api_key=None, secret_key=None, paper=True):
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return fake_client
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def fake_predict_latest_probability(**kwargs):
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return PredictionResult(
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prediction_date=pd.Timestamp("2026-08-03"),
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probability=0.9,
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base_probability=0.5,
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feature_columns=["SPY_ret_5"],
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)
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monkeypatch.setattr(
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"trading_bot.models.trade.create_alpaca_trading_client",
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fake_create_client,
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)
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monkeypatch.setattr(
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"trading_bot.models.trade.predict_latest_probability",
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fake_predict_latest_probability,
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)
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summary, order = rebalance_alpaca_portfolio(
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api_key="test-key",
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secret_key="test-secret",
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paper=True,
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symbol="SPY",
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min_order_dollars=100.0,
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sensitivity=5.0,
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)
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assert fake_client.cancelled is True
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assert order is not None
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assert order["side"] == "buy"
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assert order["notional"] == pytest.approx(1000.0)
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assert summary.cash == 1000.0
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assert summary.spy_market_value == 5000.0
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def test_rebalance_skips_small_orders_below_minimum(monkeypatch) -> None:
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fake_client = FakeAlpacaClient()
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def fake_create_client(api_key=None, secret_key=None, paper=True):
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return fake_client
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def fake_predict_latest_probability(**kwargs):
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return PredictionResult(
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prediction_date=pd.Timestamp("2026-08-03"),
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probability=0.569,
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base_probability=0.5,
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feature_columns=["SPY_ret_5"],
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)
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monkeypatch.setattr(
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"trading_bot.models.trade.create_alpaca_trading_client",
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fake_create_client,
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)
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monkeypatch.setattr(
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"trading_bot.models.trade.predict_latest_probability",
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fake_predict_latest_probability,
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)
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summary, order = rebalance_alpaca_portfolio(
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api_key="test-key",
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secret_key="test-secret",
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paper=True,
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symbol="SPY",
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min_order_dollars=100.0,
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sensitivity=5.0,
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)
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assert fake_client.cancelled is False
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assert order is None
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assert summary.cash == 1000.0
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assert summary.spy_market_value == 5000.0
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