"""以损定仓纯函数测试。""" from __future__ import annotations from app.strategy.risk_sizing import ( BASE_EXIT_USDT, BASE_OPTION_ETH, BASE_PERP_ETH, compute_k, floor_k_1dp, normalize_risk_leverage_basis, resolve_sizing_option_ask, unit_cost, ) def test_floor_k_1dp() -> None: assert floor_k_1dp(1.29) == 1.2 assert floor_k_1dp(0.19) == 0.1 assert floor_k_1dp(0.09) == 0.0 assert floor_k_1dp(2.0) == 2.0 def test_compute_k_scales_1_2_15() -> None: # I=2000, A=20, fee=0.0005 → unit = 2*20 + 2000*0.0005*3 = 40 + 3 = 43 # budget=43 → k=1.0 r = compute_k(budget=43.0, index_px=2000.0, option_ask=20.0, fee_rate=0.0005) assert r.ok assert r.k == 1.0 assert r.perp_qty_eth == BASE_PERP_ETH assert r.option_qty_eth == BASE_OPTION_ETH assert r.net_profit_target == BASE_EXIT_USDT assert r.max_loss is not None and r.max_loss <= 43.0 + 1e-6 assert r.budget == 43.0 def test_compute_k_custom_units() -> None: # option_unit=4 → premium unit = 20*4=80; fee=3; cost=83; budget=83 → k=1 r = compute_k( budget=83.0, index_px=2000.0, option_ask=20.0, fee_rate=0.0005, perp_unit=0.5, option_unit=4.0, exit_unit=30.0, ) assert r.ok assert r.k == 1.0 assert r.perp_qty_eth == 0.5 assert r.option_qty_eth == 4.0 assert r.net_profit_target == 30.0 def test_money_rounds_2dp() -> None: r = compute_k(budget=50.123456, index_px=1900.0, option_ask=18.5, fee_rate=0.0005) assert r.ok assert r.budget == round(50.123456, 2) assert r.max_loss is not None assert abs(r.max_loss * 100 - round(r.max_loss * 100)) < 1e-9 def test_compute_k_never_exceeds_budget() -> None: r = compute_k(budget=50.0, index_px=1900.0, option_ask=18.5, fee_rate=0.0005) assert r.ok assert r.k is not None assert abs(r.k * 10 - round(r.k * 10)) < 1e-9 # 一位小数 assert r.max_loss is not None and r.max_loss <= 50.0 + 1e-6 assert r.perp_qty_eth == round(1.0 * r.k, 4) assert r.option_qty_eth == round(2.0 * r.k, 4) assert r.net_profit_target == round(15.0 * r.k, 4) def test_compute_k_too_small() -> None: # unit≈43, budget=2 → k_raw≪0.1 r = compute_k(budget=2.0, index_px=2000.0, option_ask=20.0, fee_rate=0.0005) assert not r.ok assert "最小仓" in r.detail or "k=" in r.detail def test_unit_cost() -> None: assert abs(unit_cost(index_px=2000, option_ask=20, fee_rate=0.0005) - 43.0) < 1e-9 def test_normalize_risk_leverage_basis() -> None: assert normalize_risk_leverage_basis("actual") == "actual" assert normalize_risk_leverage_basis("selection") == "selection" assert normalize_risk_leverage_basis("min_option_leverage") == "selection" assert normalize_risk_leverage_basis("weird", default="selection") == "selection" def test_resolve_sizing_ask_selection_vs_actual() -> None: # 指数 2000、选约杠杆 100 → 隐含卖一 20;实际卖一更便宜 10 sel_ask, basis = resolve_sizing_option_ask( index_px=2000.0, option_ask=10.0, leverage_basis="selection", min_option_leverage=100.0, ) assert basis == "selection" assert abs(sel_ask - 20.0) < 1e-9 act_ask, basis2 = resolve_sizing_option_ask( index_px=2000.0, option_ask=10.0, leverage_basis="actual", min_option_leverage=100.0, ) assert basis2 == "actual" assert abs(act_ask - 10.0) < 1e-9 def test_selection_basis_yields_smaller_k_when_ask_cheap() -> None: # 预算 43:选约隐含 ask=20 → k=1;若用实际 ask=10 → 单位成本更小 → k 更大 r_sel = compute_k(budget=43.0, index_px=2000.0, option_ask=20.0, fee_rate=0.0005) r_act = compute_k(budget=43.0, index_px=2000.0, option_ask=10.0, fee_rate=0.0005) assert r_sel.ok and r_act.ok assert r_sel.k == 1.0 assert r_act.k is not None and r_act.k > r_sel.k def test_compute_risk_sizing_unit_overrides(tmp_path, monkeypatch) -> None: monkeypatch.setenv("MODE", "SIM") from app.models.db import Database from app.strategy.risk_sizing import compute_risk_sizing db = Database(tmp_path / "risk_units.db") db.set_setting("sizing_mode", "risk_based") db.set_setting("risk_loss_mode", "absolute") db.set_setting("risk_loss_usdt", "83") db.set_setting("fee_rate", "0.0005") db.set_setting("risk_leverage_basis", "selection") db.set_setting("min_option_leverage", "100") db.set_setting("risk_perp_unit", "1") db.set_setting("risk_option_unit", "2") db.set_setting("risk_exit_unit", "15") # 覆盖为单位 0.5:4、出场 5,并强制实际卖一(ask=20 → cost=80+3=83 → k=1) r = compute_risk_sizing( index_px=2000.0, option_ask=20.0, db=db, perp_unit=0.5, option_unit=4.0, exit_unit=5.0, leverage_basis="actual", ) assert r.ok assert r.leverage_basis == "actual" assert r.k == 1.0 assert r.perp_qty_eth == 0.5 assert r.option_qty_eth == 4.0 assert r.net_profit_target == 5.0 db.close() def test_compute_risk_sizing_respects_basis(tmp_path, monkeypatch) -> None: monkeypatch.setenv("MODE", "SIM") from app.models.db import Database from app.strategy.risk_sizing import compute_risk_sizing db = Database(tmp_path / "risk_basis.db") db.set_setting("sizing_mode", "risk_based") db.set_setting("risk_loss_mode", "absolute") db.set_setting("risk_loss_usdt", "43") db.set_setting("fee_rate", "0.0005") db.set_setting("min_option_leverage", "100") db.set_setting("risk_perp_unit", "1") db.set_setting("risk_option_unit", "2") db.set_setting("risk_exit_unit", "15") db.set_setting("risk_leverage_basis", "selection") r1 = compute_risk_sizing(index_px=2000.0, option_ask=10.0, db=db) assert r1.ok assert r1.leverage_basis == "selection" assert r1.k == 1.0 assert r1.actual_option_ask == 10.0 assert r1.option_ask == 20.0 db.set_setting("risk_leverage_basis", "actual") r2 = compute_risk_sizing(index_px=2000.0, option_ask=10.0, db=db) assert r2.ok assert r2.leverage_basis == "actual" assert r2.k is not None and r2.k > 1.0 assert r2.option_ask == 10.0 db.close() def test_consecutive_loss_days_and_martingale(tmp_path, monkeypatch) -> None: monkeypatch.setenv("MODE", "SIM") from datetime import datetime, timezone from zoneinfo import ZoneInfo from app.models.db import Database from app.strategy.risk_sizing import consecutive_loss_days, resolve_martingale db = Database(tmp_path / "mg.db") sh = ZoneInfo("Asia/Shanghai") def day_ms(ymd: str, hour: int = 16) -> int: dt = datetime.strptime(ymd, "%Y-%m-%d").replace( hour=hour, tzinfo=sh ) return int(dt.astimezone(timezone.utc).timestamp() * 1000) # 插入:盈利日打断后连亏 3 天(有成交日序列,跳过无成交日) rows = [ ("g1", day_ms("2026-07-28"), 10.0), ("g2", day_ms("2026-07-29"), -5.0), ("g3", day_ms("2026-07-30"), -3.0), ("g4", day_ms("2026-07-31"), -1.0), ] for gid, ms, pnl in rows: db.execute( """INSERT INTO groups( group_id, status, realized_pnl, close_at_ms, open_at_ms ) VALUES(?,?,?,?,?)""", (gid, "closed", pnl, ms, ms - 3600_000), ) assert consecutive_loss_days(db) == 3 db.set_setting("sizing_mode", "risk_based") db.set_setting("risk_loss_mode", "percent") db.set_setting("risk_loss_pct", "2") db.set_setting("martingale_enabled", "true") db.set_setting("martingale_start_after_loss_days", "2") db.set_setting("martingale_max_doubles", "3") mg = resolve_martingale(db, base_pct=2.0) assert mg["eligible"] is True assert mg["loss_days"] == 3 # 连亏3天、start=2 → doubles = min(3-2+1, 3) = 2 → 2%*4 = 8% assert mg["doubles"] == 2 assert abs(float(mg["effective_pct"]) - 8.0) < 1e-9 db.set_setting("risk_loss_pct", "3.1") mg2 = resolve_martingale(db, base_pct=3.1) assert mg2["eligible"] is False assert mg2["doubles"] == 0 assert abs(float(mg2["effective_pct"]) - 3.1) < 1e-9 db.close() def test_martingale_doubles_capped(tmp_path, monkeypatch) -> None: monkeypatch.setenv("MODE", "SIM") from datetime import datetime, timezone from zoneinfo import ZoneInfo from app.models.db import Database from app.strategy.risk_sizing import resolve_martingale db = Database(tmp_path / "mg_cap.db") sh = ZoneInfo("Asia/Shanghai") def day_ms(ymd: str) -> int: dt = datetime.strptime(ymd, "%Y-%m-%d").replace(hour=12, tzinfo=sh) return int(dt.astimezone(timezone.utc).timestamp() * 1000) for i, ymd in enumerate( ["2026-07-26", "2026-07-27", "2026-07-28", "2026-07-29", "2026-07-30"] ): db.execute( """INSERT INTO groups( group_id, status, realized_pnl, close_at_ms, open_at_ms ) VALUES(?,?,?,?,?)""", (f"c{i}", "closed", -1.0, day_ms(ymd), day_ms(ymd) - 1000), ) db.set_setting("sizing_mode", "risk_based") db.set_setting("risk_loss_mode", "percent") db.set_setting("martingale_enabled", "true") db.set_setting("martingale_start_after_loss_days", "2") db.set_setting("martingale_max_doubles", "3") mg = resolve_martingale(db, base_pct=2.0) # 连亏5、start2 → raw=4,cap=3 → 2%*8=16% assert mg["doubles"] == 3 assert abs(float(mg["effective_pct"]) - 16.0) < 1e-9 db.close() def test_expiry_settle_counts_as_loss_even_if_profit(tmp_path, monkeypatch) -> None: """到期结算小盈利也按亏损计入倍投连亏日。""" monkeypatch.setenv("MODE", "SIM") from datetime import datetime, timezone from zoneinfo import ZoneInfo from app.models.db import Database from app.strategy.risk_sizing import consecutive_loss_days db = Database(tmp_path / "mg_exp.db") sh = ZoneInfo("Asia/Shanghai") def day_ms(ymd: str) -> int: dt = datetime.strptime(ymd, "%Y-%m-%d").replace(hour=16, tzinfo=sh) return int(dt.astimezone(timezone.utc).timestamp() * 1000) # 达标盈利打断;随后两天均为到期小盈利 → 仍计连亏 2 rows = [ ("e0", day_ms("2026-07-28"), 20.0, "fixed_usdt"), ("e1", day_ms("2026-07-29"), 3.5, "expiry"), ("e2", day_ms("2026-07-30"), 1.2, "expiry"), ] for gid, ms, pnl, reason in rows: db.execute( """INSERT INTO groups( group_id, status, realized_pnl, close_at_ms, open_at_ms, close_reason ) VALUES(?,?,?,?,?,?)""", (gid, "closed", pnl, ms, ms - 3600_000, reason), ) assert consecutive_loss_days(db) == 2 # 再来一天达标盈利 → 连亏清零 db.execute( """INSERT INTO groups( group_id, status, realized_pnl, close_at_ms, open_at_ms, close_reason ) VALUES(?,?,?,?,?,?)""", ("e3", "closed", 15.0, day_ms("2026-07-31"), day_ms("2026-07-31") - 1000, "fixed_usdt"), ) assert consecutive_loss_days(db) == 0 db.close()