Gahow Wang
e2b06f1b1c
rebalance treated only today's S&P 500 members as the strategy's, so a held name that left the index (or was renamed on Wikipedia) was never sold and its value shrank the investable amount, unlike quant-trading's engine, which sells non-members at the next rebalance. Now every USD stock/ETF position is managed except execution.unmanaged (AAOI); a holding without bars is priced from the account for its exit. On the paper account the managed set is unchanged (the 10 current members). Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
81 lines
3.4 KiB
Python
81 lines
3.4 KiB
Python
import asyncio
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import dataclasses
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import datetime as dt
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from pathlib import Path
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from unittest.mock import AsyncMock
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import pandas as pd
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import pytest
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from ibkr_quant import cli
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from ibkr_quant.broker import AccountState, Broker, Holding
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from ibkr_quant.config import load_config
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from ibkr_quant.rebalance import plan_orders
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def test_closes_dropped_names_and_sells_before_buys():
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orders = plan_orders(
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target_weights={"AAPL": 0.5, "MSFT": 0.5},
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positions={"AAPL": 10, "NVDA": 7},
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prices={"AAPL": 100.0, "MSFT": 300.0, "NVDA": 50.0},
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investable=10_000,
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min_trade_value=200,
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)
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assert [(o.symbol, o.delta) for o in orders] == [("NVDA", -7), ("AAPL", 40), ("MSFT", 16)]
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def test_skips_small_adjustments_but_not_full_exits():
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orders = plan_orders(
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target_weights={"AAPL": 1.0},
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positions={"AAPL": 99, "KO": 1},
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prices={"AAPL": 100.0, "KO": 60.0},
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investable=10_000,
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min_trade_value=200,
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)
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assert [(o.symbol, o.delta) for o in orders] == [("KO", -1)]
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def test_refuses_to_plan_without_prices():
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with pytest.raises(ValueError, match="NVDA"):
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plan_orders({"AAPL": 1.0}, {"NVDA": 5}, {"AAPL": 100.0}, 10_000, 0)
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def test_resize_band_keeps_near_target_holdings():
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orders = plan_orders(
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target_weights={"AAPL": 0.5, "MSFT": 0.5},
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positions={"AAPL": 46, "MSFT": 10},
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prices={"AAPL": 100.0, "MSFT": 300.0},
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investable=10_000,
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min_trade_value=50,
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resize_band=0.10,
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)
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# AAPL is 8% under target and stays; MSFT is 40% under and tops up.
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assert [(o.symbol, o.delta) for o in orders] == [("MSFT", 6)]
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def test_rebalance_sells_a_holding_that_left_the_index_and_skips_unmanaged(monkeypatch, tmp_path):
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cfg = load_config(Path(__file__).resolve().parents[1] / "config.toml")
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cfg = dataclasses.replace(cfg, root=tmp_path, strategy=dataclasses.replace(cfg.strategy, top_n=2),
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execution=dataclasses.replace(cfg.execution, unmanaged=["XYZ"]))
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idx = pd.bdate_range(end=dt.date(2026, 10, 13), periods=300)
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panel = pd.DataFrame(100.0, index=idx, columns=["AAA", "BBB", "CCC"])
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monkeypatch.setattr(cli, "load_universe", lambda _: list(panel.columns))
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monkeypatch.setattr(cli, "load_bars", lambda *_: (panel, panel))
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monkeypatch.setattr(cli, "sessions_until_rebalance", lambda *_: 0)
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monkeypatch.setattr(cli, "signal_overnight_recovery",
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lambda o, c: pd.DataFrame({"AAA": 0.9, "BBB": 0.8, "CCC": 0.1}, index=o.index))
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holdings = [Holding("AAA", "STK", "USD", 44, 100.0, 4_400.0),
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Holding("OLD", "STK", "USD", 10, 30.0, 300.0), # left the index: no bars
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Holding("XYZ", "STK", "USD", 10, 100.0, 1_000.0)] # unmanaged
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broker = Broker(cfg.ib)
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monkeypatch.setattr(Broker, "__aenter__", AsyncMock(return_value=broker))
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monkeypatch.setattr(Broker, "__aexit__", AsyncMock(return_value=None))
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monkeypatch.setattr(cli, "Broker", lambda _: broker)
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monkeypatch.setattr(broker, "account_state", AsyncMock(return_value=AccountState("DU123", 10_000, 4_300, holdings)))
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asyncio.run(cli.rebalance(cfg, submit=False))
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plan = pd.read_csv(next((tmp_path / "runs").glob("*/plan.csv")))
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# investable = 10,000 * 0.98 - 1,000 (XYZ) = 8,800: 4,400 per name, so AAA is on target.
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assert list(zip(plan.symbol, plan.delta, plan.price)) == [("OLD", -10, 30.0), ("BBB", 44, 100.0)]
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