Files
fxhnt/tests/integration/test_execution.py
jgrusewski 7fb14c47a0 feat: multi-strategy execution layer (domain netting + Broker port + ExecutionService)
Layer-by-layer: domain/portfolio (Book + StrategyAllocation + compute_target_weights — nets many
sleeves, incl. same market, into per-market targets capped at gross leverage) | ports/broker (Broker
contract + Order/AccountState DTOs) | application/execution (ExecutionService: net → reconcile vs
broker → whole-share orders with entry-floor/hysteresis, behind the hard-won gates: paper-guard,
data-consistency/conservative-NLV, leverage-cap) | config ExecutionSettings. Tested with fake
data+broker (no network/IBKR): netting, leverage cap, buy-from-flat, in-band no-op, live-block,
inconsistent-data-block. 10/10 tests green. IBKR adapter (behind Broker port) is the next step.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-09 13:52:32 +02:00

83 lines
3.1 KiB
Python

"""Execution engine end-to-end with a FAKE data provider + FAKE broker (no network, no IBKR).
Proves the multi-strategy rebalance: netting → reconcile vs broker → whole-share orders → gates."""
from __future__ import annotations
import numpy as np
from fxhnt.application import ExecutionService
from fxhnt.config import ExecutionSettings, Settings
from fxhnt.domain.models import AssetClass, Market, PriceSeries, StrategySpec
from fxhnt.domain.portfolio import Book, StrategyAllocation
from fxhnt.ports.broker import AccountState, Order
SPY = Market(symbol="SPY", asset_class=AssetClass.ETF)
class FakeData:
name = "fake"
def fetch(self, market: Market, start=None, end=None) -> PriceSeries:
close = 100.0 * np.cumprod(1.0 + np.full(400, 0.001)) # uptrend -> trend long
return PriceSeries(market=market, dates=tuple(str(i) for i in range(400)), close=close)
class FakeBroker:
name = "fake"
def __init__(self, state: AccountState) -> None:
self.state = state
self.placed: list[Order] = []
def account_state(self) -> AccountState:
return self.state
def place_order(self, order: Order) -> str:
self.placed.append(order)
return "Filled"
def _book() -> Book:
return Book(name="b", max_gross_leverage=1.0, allocations=[
StrategyAllocation(spec=StrategySpec(kind="trend", params={"window": 50}), market=SPY, weight=1.0),
])
def _settings() -> Settings:
return Settings(execution=ExecutionSettings(allow_live=False))
def test_rebalance_from_flat_places_buy() -> None:
broker = FakeBroker(AccountState(nlv=100_000, cash=100_000, positions={}, is_paper=True))
svc = ExecutionService(FakeData(), broker, _settings())
plan = svc.rebalance(_book(), execute=True)
assert not plan.blocked
assert plan.executed and len(broker.placed) == 1
o = broker.placed[0]
assert o.symbol == "SPY" and o.side == "BUY"
# ~100% of 100k at price ~149 (100*1.001^399) -> ~670 shares
assert 600 < o.quantity < 750
def test_in_band_when_already_on_target_no_orders() -> None:
# already holding ~full target -> hysteresis says do nothing
broker = FakeBroker(AccountState(nlv=100_000, cash=0, positions={"SPY": 670}, is_paper=True))
svc = ExecutionService(FakeData(), broker, _settings())
plan = svc.rebalance(_book(), execute=True)
assert not plan.executed and not broker.placed
assert any("in band" in n for n in plan.notes)
def test_live_account_blocked_without_allow_live() -> None:
broker = FakeBroker(AccountState(nlv=100_000, cash=100_000, positions={}, is_paper=False))
svc = ExecutionService(FakeData(), broker, _settings())
plan = svc.rebalance(_book(), execute=True)
assert plan.blocked and not broker.placed
def test_inconsistent_account_data_blocks() -> None:
# NLV says 100k but cash+positions says 60k -> 40% gap > data_tol -> refuse
broker = FakeBroker(AccountState(nlv=100_000, cash=10_000, positions={}, is_paper=True, gross_position_value=50_000))
svc = ExecutionService(FakeData(), broker, _settings())
plan = svc.rebalance(_book(), execute=True)
assert plan.blocked and not broker.placed