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fxhnt/tests/integration/test_bybit_oi_deleverage_oos.py

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Python

"""OOS / WALK-FORWARD validation harness for the Bybit OI-DELEVERAGING edge — the DEPLOY GATE.
The signal (forced OI-unwind overshoot) is near-parameterless, so OOS validation is about:
1. CONSISTENCY across held-out time -> rolling non-overlapping windows, fraction positive;
2. the DIRECTION CHOICE survives a real train/test split (re-pick on TRAIN, apply to never-seen TEST);
3. ROBUSTNESS -> drop-top-N contributors, liquidity sweep;
4. STRICT CAUSALITY -> a look-ahead audit (signal at d -> d->d+1 return only).
All fixtures are in-memory (sqlite), NO network, READ-ONLY (a write-tripwire never trips), memory-bounded.
"""
from __future__ import annotations
import math
from fxhnt.adapters.warehouse.timescale_feature_store import TimescaleFeatureStore
from fxhnt.application.bybit_oi_deleverage_eval import (
look_ahead_audit,
walk_forward_oi_deleverage,
)
_DAY = 86_400
_START = 19_358 # 2023-01-01 (epoch day)
class _WriteTripwireStore:
_FORBIDDEN = frozenset({
"write_features", "write_features_bulk", "upsert_feature_rows", "upsert_membership",
"replace_positions", "upsert_nav", "upsert_sleeve_ret", "replace_shadow_positions",
"replace_trades", "_create_schema", "_bulk_upsert",
})
def __init__(self, inner: TimescaleFeatureStore) -> None:
object.__setattr__(self, "_inner", inner)
def __getattr__(self, name: str):
if name in _WriteTripwireStore._FORBIDDEN:
raise AssertionError(f"READ-ONLY violation: harness called write method {name!r}")
return getattr(self._inner, name)
# --- fixtures ----------------------------------------------------------------------------------
def _seed_broad_reversion(store: TimescaleFeatureStore, *, days: int = 720, revert_frac: float = 0.9,
coins: tuple[str, ...] = ("AAAUSDT", "BBBUSDT", "CCCUSDT", "DDDUSDT",
"EEEUSDT", "FFFUSDT", "GGGUSDT", "HHHUSDT"),
start_day: int = _START) -> None:
"""Broad, consistently-positive reversion edge across many coins for the FULL span: each day ONE rotating
coin has a forced OI unwind (OI drops) + a sharp move that REVERTS next day (the fade earns). Non-unwind
coins keep OI flat (no signal). `revert_frac` < 1 leaves a net edge after the bounce."""
px = {c: 100.0 for c in coins}
oi = {c: 1_000_000.0 for c in coins}
pending: dict[str, float] = {}
for c in coins:
store.write_features(c, [(start_day * _DAY, {"open_interest": oi[c], "close": px[c]})])
for i in range(1, days + 1):
d = start_day + i
unwind = coins[i % len(coins)]
up = (i % 2 == 0)
for c in coins:
if c in pending:
px[c] *= pending.pop(c)
if c == unwind:
oi[c] *= 0.78
move = 0.06 if up else -0.06
px[c] *= (1.0 + move)
pending[c] = (1.0 - move * revert_frac)
else:
oi[c] *= 1.0005
store.write_features(c, [(d * _DAY, {"open_interest": oi[c], "close": px[c]})])
d = start_day + days + 1
for c in coins:
if c in pending:
px[c] *= pending.pop(c)
store.write_features(c, [(d * _DAY, {"open_interest": oi[c], "close": px[c]})])
def _seed_train_only(store: TimescaleFeatureStore, *, days: int = 600) -> None:
"""Reversion pays in TRAIN (first 60%) but the sign FLIPS in TEST (forced moves CONTINUE there). Train
picks 'reversion'; applied to TEST it LOSES — the train/holdout test must catch the overfit."""
coins = ("AAAUSDT", "BBBUSDT", "CCCUSDT", "DDDUSDT")
px = {c: 100.0 for c in coins}
oi = {c: 1_000_000.0 for c in coins}
split = int(days * 0.6)
pending: dict[str, float] = {}
for c in coins:
store.write_features(c, [(_START * _DAY, {"open_interest": oi[c], "close": px[c]})])
for i in range(1, days + 1):
d = _START + i
unwind = coins[i % len(coins)]
up = (i % 2 == 0)
for c in coins:
if c in pending:
px[c] *= pending.pop(c)
if c == unwind:
oi[c] *= 0.78
move = 0.06 if up else -0.06
px[c] *= (1.0 + move)
# TRAIN: revert (fade earns). TEST: continue (forced move keeps going -> fade loses).
pending[c] = (1.0 - move * 0.9) if i < split else (1.0 + move * 0.9)
else:
oi[c] *= 1.0005
store.write_features(c, [(d * _DAY, {"open_interest": oi[c], "close": px[c]})])
d = _START + days + 1
for c in coins:
if c in pending:
px[c] *= pending.pop(c)
store.write_features(c, [(d * _DAY, {"open_interest": oi[c], "close": px[c]})])
def _seed_one_coin(store: TimescaleFeatureStore, *, days: int = 400) -> None:
"""The reversion edge lives in ONE coin only: AAA unwinds + reverts (tradeable); the others NEVER unwind
(OI flat -> no signal). Dropping the top contributor should KILL it (concentration-driven / fragile)."""
coins = ("AAAUSDT", "BBBUSDT", "CCCUSDT", "DDDUSDT")
px = {c: 100.0 for c in coins}
oi = {c: 1_000_000.0 for c in coins}
pending: dict[str, float] = {}
for c in coins:
store.write_features(c, [(_START * _DAY, {"open_interest": oi[c], "close": px[c]})])
for i in range(1, days + 1):
d = _START + i
up = (i % 2 == 0)
for c in coins:
if c in pending:
px[c] *= pending.pop(c)
if c == "AAAUSDT":
oi[c] *= 0.78
move = 0.06 if up else -0.06
px[c] *= (1.0 + move)
pending[c] = (1.0 - move * 0.9)
else:
oi[c] *= 1.0005 # others never unwind -> no signal, flat price
store.write_features(c, [(d * _DAY, {"open_interest": oi[c], "close": px[c]})])
d = _START + days + 1
for c in coins:
if c in pending:
px[c] *= pending.pop(c)
store.write_features(c, [(d * _DAY, {"open_interest": oi[c], "close": px[c]})])
# --- 1. rolling windows ------------------------------------------------------------------------
def test_rolling_windows_broad_edge_mostly_positive() -> None:
store = TimescaleFeatureStore("sqlite://", table="bybit_features")
_seed_broad_reversion(store)
rep = walk_forward_oi_deleverage(store, universe=None, cost_bps=5.5, window_days=180)
store.close()
rw = rep["rolling_windows"]
assert rw["n_windows"] >= 3
assert rw["fraction_positive"] > 0.7
assert len(rw["windows"]) == rw["n_windows"]
for w in rw["windows"]:
assert {"start", "end", "sharpe", "total_return", "days"} <= set(w)
# --- 2. train / holdout DIRECTION test ---------------------------------------------------------
def test_train_holdout_direction_generalises_on_broad_edge() -> None:
store = TimescaleFeatureStore("sqlite://", table="bybit_features")
_seed_broad_reversion(store)
rep = walk_forward_oi_deleverage(store, universe=None, cost_bps=5.5)
store.close()
th = rep["train_holdout"]
assert th["train_direction"] == "reversion"
assert th["train_sharpe"] > 0.0
assert th["test_sharpe"] > 0.0
def test_train_holdout_catches_overfit_when_sign_flips_in_test() -> None:
store = TimescaleFeatureStore("sqlite://", table="bybit_features")
_seed_train_only(store)
rep = walk_forward_oi_deleverage(store, universe=None, cost_bps=5.5)
store.close()
th = rep["train_holdout"]
assert th["train_direction"] == "reversion"
assert th["train_sharpe"] > 0.0
assert th["test_sharpe"] < 0.0
# --- 3a. drop-top-N robustness -----------------------------------------------------------------
def test_drop_top_n_broad_edge_survives() -> None:
store = TimescaleFeatureStore("sqlite://", table="bybit_features")
_seed_broad_reversion(store)
rep = walk_forward_oi_deleverage(store, universe=None, cost_bps=5.5)
store.close()
dt = rep["drop_top_n"]
assert dt["full_sharpe"] > 0.0
assert dt["drop5"]["sharpe"] > 0.0
assert dt["drop5"]["n_dropped"] >= 1
assert isinstance(dt["drop5"]["dropped"], list)
def test_drop_top_n_one_coin_edge_collapses() -> None:
store = TimescaleFeatureStore("sqlite://", table="bybit_features")
_seed_one_coin(store)
rep = walk_forward_oi_deleverage(store, universe=None, cost_bps=5.5)
store.close()
dt = rep["drop_top_n"]
assert dt["full_sharpe"] > 0.0
assert dt["drop5"]["sharpe"] < dt["full_sharpe"]
assert dt["drop5"]["sharpe"] < 0.5
# --- 3b. liquidity sweep -----------------------------------------------------------------------
def test_liquidity_sweep_returns_metric_per_threshold() -> None:
store = TimescaleFeatureStore("sqlite://", table="bybit_features")
coins = ("AAAUSDT", "BBBUSDT", "CCCUSDT", "DDDUSDT",
"EEEUSDT", "FFFUSDT", "GGGUSDT", "HHHUSDT")
_seed_broad_reversion(store, coins=coins)
for i in range(722):
d = _START + i
for c in coins:
store.write_features(c, [(d * _DAY, {"turnover": 50_000_000.0})])
rep = walk_forward_oi_deleverage(store, universe=None, cost_bps=5.5,
liquidity_grid=(5_000_000.0, 10_000_000.0, 25_000_000.0))
store.close()
ls = rep["liquidity_sweep"]
assert set(ls) == {5_000_000.0, 10_000_000.0, 25_000_000.0}
for _thr, m in ls.items():
assert "sharpe" in m and "n_coins" in m
assert math.isfinite(m["sharpe"])
assert m["n_coins"] >= 0
# --- 4. look-ahead audit -----------------------------------------------------------------------
def test_look_ahead_audit_passes_on_causal_signal() -> None:
store = TimescaleFeatureStore("sqlite://", table="bybit_features")
_seed_broad_reversion(store, days=120)
rep = look_ahead_audit(store, universe=None)
store.close()
assert rep["causal"] is True
assert rep["leak_days"] == 0
def test_look_ahead_audit_catches_a_deliberately_leaked_mapping() -> None:
store = TimescaleFeatureStore("sqlite://", table="bybit_features")
_seed_broad_reversion(store, days=120)
rep = look_ahead_audit(store, universe=None, _leak=True) # use the same-day return (leak)
store.close()
assert rep["causal"] is False
assert rep["leak_days"] > 0
def test_walk_forward_includes_look_ahead_audit() -> None:
store = TimescaleFeatureStore("sqlite://", table="bybit_features")
_seed_broad_reversion(store)
rep = walk_forward_oi_deleverage(store, universe=None, cost_bps=5.5)
store.close()
assert rep["look_ahead"]["causal"] is True
# --- 5. PASS/FAIL verdict ----------------------------------------------------------------------
def test_verdict_pass_on_broad_generalising_edge() -> None:
store = TimescaleFeatureStore("sqlite://", table="bybit_features")
coins = ("AAAUSDT", "BBBUSDT", "CCCUSDT", "DDDUSDT",
"EEEUSDT", "FFFUSDT", "GGGUSDT", "HHHUSDT")
_seed_broad_reversion(store, coins=coins)
for i in range(722):
d = _START + i
for c in coins:
store.write_features(c, [(d * _DAY, {"turnover": 50_000_000.0})])
rep = walk_forward_oi_deleverage(store, universe=None, cost_bps=5.5, window_days=180,
liquidity_grid=(5_000_000.0, 10_000_000.0, 25_000_000.0))
store.close()
v = rep["verdict"]
assert v["deployable"] is True
assert v["checks"]["rolling_windows_positive"] is True
assert v["checks"]["oos_direction_positive"] is True
assert v["checks"]["survives_drop_top5"] is True
assert v["checks"]["liquidity_robust"] is True
assert v["checks"]["look_ahead_clean"] is True
def test_verdict_fail_on_overfit_edge() -> None:
store = TimescaleFeatureStore("sqlite://", table="bybit_features")
_seed_train_only(store)
rep = walk_forward_oi_deleverage(store, universe=None, cost_bps=5.5)
store.close()
v = rep["verdict"]
assert v["deployable"] is False
assert v["checks"]["oos_direction_positive"] is False
# --- 6. read-only ------------------------------------------------------------------------------
def test_walk_forward_is_read_only() -> None:
inner = TimescaleFeatureStore("sqlite://", table="bybit_features")
_seed_broad_reversion(inner)
store = _WriteTripwireStore(inner)
rep = walk_forward_oi_deleverage(store, universe=None, cost_bps=5.5)
inner.close()
assert rep["rolling_windows"]["n_windows"] >= 1
# --- 7. CLI ------------------------------------------------------------------------------------
def test_cli_walk_forward_prints_verdict(monkeypatch) -> None:
from typer.testing import CliRunner
import fxhnt.cli as cli
store = TimescaleFeatureStore("sqlite://", table="bybit_features")
_seed_broad_reversion(store)
monkeypatch.setattr(
"fxhnt.adapters.warehouse.timescale_feature_store.TimescaleFeatureStore",
lambda *_a, **_k: store, raising=False)
result = CliRunner().invoke(cli.app, ["bybit-oi-deleverage-eval", "--all", "--walk-forward"])
store.close()
assert result.exit_code == 0, result.output
out = result.output.lower()
assert "walk-forward" in out or "walk forward" in out
assert "rolling" in out
assert "oos" in out or "holdout" in out
assert "verdict" in out
assert "pass" in out or "fail" in out