Use alpaca instead of ibkr.

notebooks/ibkr_scratch.ipynb

@@ -0,0 +1,107 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "cd849b8e",
+   "metadata": {},
+   "source": [
+    "# IBKR scratch notebook\n",
+    "\n",
+    "This notebook is for quick manual testing of the IBKR gateway connection, portfolio lookup, and a simple SPY order flow.\n",
+    "\n",
+    "> Use this only with a paper-trading or test setup unless you explicitly intend to submit a live order.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "543426a2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import sys\n",
+    "from pathlib import Path\n",
+    "\n",
+    "from ib_insync import IB, Stock\n",
+    "\n",
+    "# Allow the notebook to import local source code from the repository.\n",
+    "repo_root = Path.cwd().resolve()\n",
+    "if (repo_root / \"src\").exists():\n",
+    "    repo_root = repo_root\n",
+    "else:\n",
+    "    repo_root = repo_root.parent\n",
+    "\n",
+    "src_path = repo_root / \"src\"\n",
+    "if str(src_path) not in sys.path:\n",
+    "    sys.path.insert(0, str(src_path))\n",
+    "\n",
+    "from trading_bot.data.fetch_ibkr_daily import (\n",
+    "    IBKR_CLIENT_ID,\n",
+    "    IBKR_CONNECT_TIMEOUT_SECONDS,\n",
+    "    IBKR_HOST,\n",
+    "    IBKR_PORT,\n",
+    ")\n",
+    "\n",
+    "ib = IB()\n",
+    "print(f\"Connecting to IBKR Gateway at {IBKR_HOST}:{IBKR_PORT} with client id {IBKR_CLIENT_ID}...\")\n",
+    "ib.connect(IBKR_HOST, IBKR_PORT, clientId=IBKR_CLIENT_ID, timeout=IBKR_CONNECT_TIMEOUT_SECONDS)\n",
+    "print(\"Connection established.\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ecdc721f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "print(f\"Connected: {ib.isConnected()}\")\n",
+    "print(f\"Client ID: {ib.clientId}\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "10ebc240",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "portfolio = ib.portfolio()\n",
+    "if not portfolio:\n",
+    "    print(\"No open portfolio positions were returned.\")\n",
+    "else:\n",
+    "    for item in portfolio:\n",
+    "        print(\n",
+    "            f\"{item.contract.symbol}: position={item.position}, \"\n",
+    "            f\"market_value={item.marketValue}, unrealized_pnl={item.unrealizedPNL}\"\n",
+    "        )\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "fed654ec",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from ib_insync import MarketOrder\n",
+    "\n",
+    "contract = Stock(\"SPY\", \"SMART\", \"USD\")\n",
+    "ib.qualifyContracts(contract)\n",
+    "\n",
+    "# Adjust the quantity as needed before running this cell.\n",
+    "order = MarketOrder(\"BUY\", 1)\n",
+    "trade = ib.placeOrder(contract, order)\n",
+    "\n",
+    "print(f\"Submitted order for {contract.symbol}: {trade}\")\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "language_info": {
+   "name": "python"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

notebooks/models/spy_xgb_v1_meta.json

@@ -1,5 +1,5 @@
 {
-  "p_base": 0.5830346475507766,
+  "p_base": 0.5833333333333334,
   "feature_cols": [
     "VIX_rank_20",
     "TLT_ret_10",
@@ -9,5 +9,5 @@
     "SPY_ret_20",
     "SPY_dist_sma50"
   ],
-  "last_trained_date": "2026-07-17 00:00:00"
+  "last_trained_date": "2026-07-24 00:00:00"
 }

notebooks/spy_direction_dataset.ipynb

@@ -20,7 +20,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "metadata": {},
    "outputs": [
     {
@@ -52,7 +52,8 @@
     "\n",
     "\n",
     "PROJECT_ROOT = find_project_root()\n",
-    "RAW_DATA_DIR = PROJECT_ROOT / \"data\" / \"ibkr\" / \"daily\"\n",
+    "#RAW_DATA_DIR = PROJECT_ROOT / \"data\" / \"ibkr\" / \"daily\"\n",
+    "RAW_DATA_DIR = PROJECT_ROOT / \"data\" / \"alpaca\" / \"daily\"\n",
     "OUTPUT_PATH = PROJECT_ROOT / \"data\" / \"training\" / \"spy_direction_5d.parquet\"\n",
     "\n",
     "SPY_SYMBOL = \"SPY\"\n",
@@ -233,7 +234,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "metadata": {},
    "outputs": [
     {
@@ -383,7 +384,7 @@
     "df[\"TLT_ret_10\"] = df[\"TLT_close\"].pct_change(10)\n",
     "df[\"USO_ret_5\"] = df[\"USO_close\"].pct_change(5)\n",
     "df[\"SPY_TLT_ratio_ret\"] = (df[\"SPY_close\"] / df[\"TLT_close\"]).pct_change(5)\n",
-    "\n",
+    "df_model\n",
     "spy_forward_close = df[\"SPY_close\"].shift(-5)\n",
     "df[\"spy_up_5d\"] = np.nan\n",
     "df.loc[spy_forward_close > df[\"SPY_close\"], \"spy_up_5d\"] = 1.0\n",

pyproject.toml

@@ -5,11 +5,13 @@ description = "Python trading bot using machine learning and the IBKR API."
 readme = "README.md"
 requires-python = ">=3.11,<3.12"
 dependencies = [
+    "alpaca-py>=0.43.5",
     "ib-insync>=0.9.86",
     "matplotlib>=3.11.1",
     "pandas>=2.3.0",
     "pyarrow>=20.0.0",
     "pytest>=9.1.1",
+    "python-dotenv>=1.2.2",
     "scikit-learn>=1.9.0",
     "xgboost>=3.2.0",
 ]

src/trading_bot/data/fetch_alpaca_daily.py

@@ -0,0 +1,314 @@
+"""Alpaca daily candle fetcher."""
+
+from __future__ import annotations
+
+import argparse
+import os
+import re
+from dataclasses import dataclass
+from datetime import date, datetime, time, timedelta
+from pathlib import Path
+from zoneinfo import ZoneInfo
+
+import pandas as pd
+from dotenv import load_dotenv
+
+# Load environment variables from .env file if available
+load_dotenv()
+
+DEFAULT_OUTPUT_DIR = Path("data/alpaca/daily")
+DEFAULT_DURATION = "1 W"
+EASTERN_TZ = ZoneInfo("America/New_York")
+DURATION_PATTERN = re.compile(r"^(\d+)\s*([DWMY])$")
+
+
+@dataclass(frozen=True)
+class DailyCandle:
+    """Daily OHLCV market data for one trading session."""
+
+    trading_day: date
+    open: float
+    high: float
+    low: float
+    close: float
+    volume: int
+
+
+def default_end_date() -> date:
+    """Return yesterday's date in the US/Eastern market timezone."""
+
+    return datetime.now(EASTERN_TZ).date() - timedelta(days=1)
+
+
+def current_market_date() -> date:
+    """Return today's date in the US/Eastern market timezone."""
+
+    return datetime.now(EASTERN_TZ).date()
+
+
+def parse_end_date(value: str) -> date:
+    """Parse an end date in YYYYMMDD format."""
+
+    try:
+        return datetime.strptime(value, "%Y%m%d").date()
+    except ValueError as exc:
+        raise argparse.ArgumentTypeError(
+            "end date must use YYYYMMDD format, such as 20250605"
+        ) from exc
+
+
+def parse_duration(value: str) -> str:
+    """Normalize and validate a duration string like '1 W' or '1 M'."""
+
+    normalized = " ".join(value.upper().split())
+    if not DURATION_PATTERN.fullmatch(normalized):
+        raise argparse.ArgumentTypeError(
+            "duration must look like '1 D', '1 W', '1 M', or '1 Y'"
+        )
+    return normalized
+
+
+def duration_to_start_date(end_date: date, duration: str) -> date:
+    """Calculate the start date based on end date and a duration string."""
+
+    match = DURATION_PATTERN.match(duration)
+    if not match:
+        raise ValueError(f"Invalid duration format: {duration}")
+
+    amount = int(match.group(1))
+    unit = match.group(2)
+
+    if unit == "D":
+        return end_date - timedelta(days=amount)
+    if unit == "W":
+        return end_date - timedelta(weeks=amount)
+    if unit == "M":
+        return end_date - timedelta(days=amount * 30)
+    if unit == "Y":
+        return end_date - timedelta(days=amount * 365)
+
+    raise ValueError(f"Unsupported duration unit: {unit}")
+
+
+def fetch_daily_candles(
+    symbol: str,
+    end_date: date,
+    duration: str,
+    api_key: str | None = None,
+    secret_key: str | None = None,
+) -> list[DailyCandle]:
+    """Fetch daily candles for a symbol using Alpaca Market Data API."""
+
+    try:
+        from alpaca.data.historical import StockHistoricalDataClient
+        from alpaca.data.requests import StockBarsRequest
+        from alpaca.data.timeframe import TimeFrame
+    except ImportError as exc:
+        raise SystemExit(
+            "Missing dependency: alpaca-py. Install it via 'pip install alpaca-py' "
+            "before running the script."
+        ) from exc
+
+    start_date = duration_to_start_date(end_date, duration)
+
+    start_dt = datetime.combine(start_date, time.min, tzinfo=EASTERN_TZ)
+    end_dt = datetime.combine(end_date, time.max, tzinfo=EASTERN_TZ)
+
+    print(start_dt, end_dt)
+
+    client = StockHistoricalDataClient(api_key=api_key, secret_key=secret_key)
+
+    request_params = StockBarsRequest(
+        symbol_or_symbols=symbol,
+        timeframe=TimeFrame.Day,
+        start=start_dt,
+        end=end_dt,
+    )
+
+    bars = client.get_stock_bars(request_params)
+
+    if not bars or symbol not in bars.data:
+        print(f"Alpaca returned no historical bars for {symbol}.")
+        return []
+
+    candles: list[DailyCandle] = []
+    for bar in bars[symbol]:
+        trading_day = bar.timestamp.astimezone(EASTERN_TZ).date()
+        candles.append(
+            DailyCandle(
+                trading_day=trading_day,
+                open=float(bar.open),
+                high=float(bar.high),
+                low=float(bar.low),
+                close=float(bar.close),
+                volume=int(bar.volume),
+            )
+        )
+
+    return candles
+
+
+def candles_to_frame(symbol: str, candles: list[DailyCandle]) -> pd.DataFrame:
+    """Convert candles to a date-indexed dataframe ready for Parquet storage."""
+
+    rows = [
+        {
+            "date": candle.trading_day,
+            "symbol": symbol,
+            "open": candle.open,
+            "high": candle.high,
+            "low": candle.low,
+            "close": candle.close,
+            "volume": candle.volume,
+        }
+        for candle in candles
+    ]
+    frame = pd.DataFrame.from_records(rows)
+    if frame.empty:
+        return pd.DataFrame(
+            columns=["symbol", "open", "high", "low", "close", "volume"],
+            index=pd.Index([], name="date"),
+        )
+
+    frame["date"] = pd.to_datetime(frame["date"]).dt.date
+    return frame.set_index("date")
+
+
+def read_existing_candles(path: Path) -> pd.DataFrame:
+    """Read an existing candle Parquet file as a date-indexed dataframe."""
+
+    if not path.exists():
+        return pd.DataFrame(
+            columns=["symbol", "open", "high", "low", "close", "volume"],
+            index=pd.Index([], name="date"),
+        )
+
+    frame = pd.read_parquet(path)
+    if "date" in frame.columns:
+        frame["date"] = pd.to_datetime(frame["date"]).dt.date
+        frame = frame.set_index("date")
+
+    frame.index = pd.to_datetime(frame.index).date
+    frame.index.name = "date"
+    return frame
+
+
+def oldest_stored_date_or_today(path: Path) -> date:
+    """Return the oldest stored candle date, or today if no data exists yet."""
+
+    existing = read_existing_candles(path)
+    if existing.empty:
+        return current_market_date()
+    return min(existing.index)
+
+
+def write_candles(path: Path, symbol: str, candles: list[DailyCandle]) -> pd.DataFrame:
+    """Append candles to a ticker Parquet file, keeping one row per date."""
+
+    existing = read_existing_candles(path)
+    fetched = candles_to_frame(symbol, candles)
+    combined = pd.concat([existing, fetched])
+    if not combined.empty:
+        combined = combined[~combined.index.duplicated(keep="last")]
+        combined = combined.sort_index()
+
+    path.parent.mkdir(parents=True, exist_ok=True)
+    combined.to_parquet(path, index=True)
+    return combined
+
+
+def print_candles(symbol: str, candles: list[DailyCandle]) -> None:
+    """Print candles in a compact table."""
+
+    print("date,symbol,open,high,low,close,volume")
+    for candle in candles:
+        print(
+            f"{candle.trading_day.isoformat()},"
+            f"{symbol},"
+            f"{candle.open:.2f},"
+            f"{candle.high:.2f},"
+            f"{candle.low:.2f},"
+            f"{candle.close:.2f},"
+            f"{candle.volume}"
+        )
+
+
+def parse_args() -> argparse.Namespace:
+    """Parse command line arguments."""
+
+    parser = argparse.ArgumentParser(description="Fetch daily Alpaca candles.")
+    parser.add_argument("symbol", help="Ticker symbol to fetch, such as SPY.")
+    end_date_group = parser.add_mutually_exclusive_group()
+    end_date_group.add_argument(
+        "--end-date",
+        type=parse_end_date,
+        help="Request end date in YYYYMMDD format. Defaults to yesterday.",
+    )
+    end_date_group.add_argument(
+        "--end-date-from-parquet",
+        action="store_true",
+        help=(
+            "Use the oldest date from the symbol Parquet file as the request "
+            "end date. Defaults to today if the file is missing or empty."
+        ),
+    )
+    parser.add_argument(
+        "--duration",
+        type=parse_duration,
+        default=DEFAULT_DURATION,
+        help=(
+            "Duration string, such as '1 W', '1 M', or '1 Y'. "
+            f"Defaults to {DEFAULT_DURATION}."
+        ),
+    )
+    parser.add_argument(
+        "--output-dir",
+        type=Path,
+        default=DEFAULT_OUTPUT_DIR,
+        help=f"Directory for Parquet files. Defaults to {DEFAULT_OUTPUT_DIR}.",
+    )
+    parser.add_argument(
+        "--api-key",
+        default=os.getenv("ALPACA_API_KEY"),
+        help="Alpaca API Key ID (defaults to ALPACA_API_KEY env var or .env).",
+    )
+    parser.add_argument(
+        "--secret-key",
+        default=os.getenv("ALPACA_SECRET_KEY"),
+        help="Alpaca Secret Key (defaults to ALPACA_SECRET_KEY env var or .env).",
+    )
+    return parser.parse_args()
+
+
+def main() -> None:
+    """Run the daily candle fetcher."""
+
+    args = parse_args()
+    symbol = args.symbol.upper()
+    output_path = args.output_dir / f"{symbol}.parquet"
+    end_date = (
+        oldest_stored_date_or_today(output_path)
+        if args.end_date_from_parquet
+        else args.end_date or default_end_date()
+    )
+
+    print(oldest_stored_date_or_today(output_path))
+
+    print(
+        f"Fetching {symbol} daily candles ending {end_date:%Y-%m-%d} "
+        f"for duration {args.duration} via Alpaca API"
+    )
+    candles = fetch_daily_candles(
+        symbol,
+        end_date,
+        args.duration,
+        api_key=args.api_key,
+        secret_key=args.secret_key,
+    )
+    #print_candles(symbol, candles)
+    stored = write_candles(output_path, symbol, candles)
+    print(f"Wrote {len(stored)} total daily rows to {output_path}")
+
+
+if __name__ == "__main__":
+    main()

src/trading_bot/models/prediction.py

@@ -10,6 +10,7 @@ from __future__ import annotations
 
 import argparse
 import json
+import os
 import warnings
 from dataclasses import dataclass
 from pathlib import Path
@@ -18,6 +19,12 @@ from typing import Any
 import numpy as np
 import pandas as pd
 import xgboost as xgb
+from dotenv import load_dotenv
+
+# Load environment variables from .env file if available
+load_dotenv()
+
+DEFAULT_DATA_DIR = Path("data/alpaca/daily")
 
 FEATURE_COLUMNS = [
     "SPY_ret_5",
@@ -218,8 +225,18 @@ def parse_args() -> argparse.Namespace:
     parser.add_argument(
         "--data-dir",
         type=Path,
-        default=Path("data/ibkr/daily"),
-        help="Directory containing the raw Parquet market data files.",
+        default=DEFAULT_DATA_DIR,
+        help=f"Directory containing the raw Parquet market data files. Defaults to {DEFAULT_DATA_DIR}.",
+    )
+    parser.add_argument(
+        "--api-key",
+        default=os.getenv("ALPACA_API_KEY"),
+        help="Alpaca API Key ID (defaults to ALPACA_API_KEY env var or .env).",
+    )
+    parser.add_argument(
+        "--secret-key",
+        default=os.getenv("ALPACA_SECRET_KEY"),
+        help="Alpaca Secret Key (defaults to ALPACA_SECRET_KEY env var or .env).",
     )
     return parser.parse_args()
 

tests/test_prediction.py

@@ -7,7 +7,7 @@ def test_predict_latest_probability_returns_probability_between_zero_and_one() -
     result = predict_latest_probability(
         model_path=Path("notebooks/models/spy_xgb_v1.json"),
         metadata_path=Path("notebooks/models/spy_xgb_v1_meta.json"),
-        raw_data_dir=Path("data/ibkr/daily"),
+        raw_data_dir=Path("data/alpaca/daily"),
     )
 
     assert set(result.feature_columns).issubset(FEATURE_COLUMNS)

uv.lock

@@ -7,6 +7,33 @@ resolution-markers = [
     "sys_platform != 'emscripten' and sys_platform != 'win32'",
 ]
 
+[[package]]
+name = "alpaca-py"
+version = "0.43.5"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "msgpack" },
+    { name = "pandas" },
+    { name = "pydantic" },
+    { name = "pytz" },
+    { name = "requests" },
+    { name = "sseclient-py" },
+    { name = "websockets" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/b8/9c/0d5b0565f31a6a439876cb343282c1b7353f20ff90fefb57d33f94b4e215/alpaca_py-0.43.5.tar.gz", hash = "sha256:7b09ba442cb0c6f957c2c57a30c6035456e2e670e63e383d439c639ffdbf98ba", size = 98289, upload-time = "2026-07-02T07:22:07.016Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/02/40/83c7ef8bc3e74e73cda6308f7107fe57815dcfc808dc9cd03bd09aa22dd3/alpaca_py-0.43.5-py3-none-any.whl", hash = "sha256:0b4cac9b743851310f19f6a9aa84f57ddf95ae75b601350395746a893f54a2da", size = 122677, upload-time = "2026-07-02T07:22:08.06Z" },
+]
+
+[[package]]
+name = "annotated-types"
+version = "0.8.0"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/5f/56/a8120250d128bed162cd73c76d45f6ef9991f3e068f62a8ee060afa3104a/annotated_types-0.8.0.tar.gz", hash = "sha256:13b2beaad985e05e2d6407ee4c4f35590b11f8d693a258a561055cac8f64cab7", size = 15893, upload-time = "2026-07-23T20:16:13.995Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/99/91/8acff4f5e50511b911bbccb72b8628a49c68ce14148cd9f6431094859a90/annotated_types-0.8.0-py3-none-any.whl", hash = "sha256:f072f4d804ea359e4eaf198b1af7a8b0943881a87f31bb764f8bf219bb9419e0", size = 13427, upload-time = "2026-07-23T20:16:12.938Z" },
+]
+
 [[package]]
 name = "appnope"
 version = "0.1.4"
@@ -25,6 +52,15 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/d4/2b/04b8a15f3a1c77bc79ddf5c73875327f34b4fa75982df2b76e45e402d364/asttokens-3.0.2-py3-none-any.whl", hash = "sha256:9da13157f5b28becde0bd374fc677dcd3c290614264eff096f167c469cd9f933", size = 28702, upload-time = "2026-07-12T03:31:47.542Z" },
 ]
 
+[[package]]
+name = "certifi"
+version = "2026.7.22"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/a3/c2/24167ea9858356b47a87a50d39908bfdb72ceeefe0041586e704e5376b3a/certifi-2026.7.22.tar.gz", hash = "sha256:741e2c3b351ddf169a738da9f2c048608ff7f2c5cc02f1ebc6b118bb090d5d55", size = 138112, upload-time = "2026-07-22T03:35:12.644Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/0b/a7/71ac2cff56fec219ed242bb11b8efb69fcc4bec75db06fb7bfe35de520e6/certifi-2026.7.22-py3-none-any.whl", hash = "sha256:62f22742b58a1a33014a2b6b706588a8d7e2a88ae7bd1a6ebe8c992928483775", size = 136983, upload-time = "2026-07-22T03:35:11.276Z" },
+]
+
 [[package]]
 name = "cffi"
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