Adriano Dal Pastro
e5e2d3ec9b
ensure_disaster_sl(): garantisce UN solo STOP_MARKET reduce_only a ~-30% coerente con la posizione, ad ogni run del loop, per asset: - flat -> cancella i bracket orfani; - long -> assicura lo stop (size = posizione, prezzo al tick); - gia' coerente (1 bracket, amount~=, stop entro 5%) -> lascia com'e' (niente churn ne' gap di protezione fra cancel e place). - deribit.py: open_orders (merge type all+trigger_all), disaster_stop_price. - execution.py: cancel_order + ensure_disaster_sl. - live_execute.py: gestione bracket ogni run, gated come l'esecuzione. Validato armato: flat -> disaster-SL 'flat' (cleanup), zero ordini. Test 28/28. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
91 lines
4.1 KiB
Python
91 lines
4.1 KiB
Python
"""Test deterministici dello SHADOW/esecuzione TP01 (src/live/deribit.py).
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Coprono la logica a rischio zero che NON tocca la rete: quantizzazione notional->contratti (INVERSE
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e LINEARE USDC), sizing target, costruzione ordine di ribilancio (buy/sell/exit/None), e PARITA' col
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backtest. Il conto reale e' USDC -> il path principale e' il LINEARE BTC_USDC-PERPETUAL. Il fill reale
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(slippage/fee) NON e' qui: si valida solo col micro-test mainnet.
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"""
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import sys
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from pathlib import Path
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PROJECT_ROOT = Path(__file__).resolve().parents[1]
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sys.path.insert(0, str(PROJECT_ROOT))
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from src.live.deribit import (build_rebalance_order, notional_to_amount, target_notional_usd)
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from src.strategies.trend_portfolio import CANONICAL, TrendPortfolio, resample_1d
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LIN = "BTC_USDC-PERPETUAL" # lineare USDC: amount in BTC, step 0.0001 (path reale del conto)
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PX = 64000.0
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def test_notional_linear_usdc():
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# amount in base-coin = notional/price, quantizzato a 0.0001, clamp al minimo
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assert notional_to_amount(LIN, 6.4, price=PX) == 0.0001 # 6.4/64000 = 0.0001
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assert notional_to_amount(LIN, 12.8, price=PX) == 0.0002
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assert notional_to_amount(LIN, 3.0, price=PX) == 0.0 # < mezzo step ($3.2) -> niente
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assert notional_to_amount(LIN, 100, price=None) == 0.0 # lineare senza prezzo -> 0
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assert notional_to_amount(LIN, -6.4, price=PX) == 0.0001 # usa il valore assoluto
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def test_notional_inverse_still_supported():
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# l'helper regge ancora gli inverse (amount in USD), senza prezzo
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assert notional_to_amount("BTC-PERPETUAL", 1000) == 1000
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assert notional_to_amount("BTC-PERPETUAL", 7) == 10 # clamp al minimo
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assert notional_to_amount("BTC-PERPETUAL", 3) == 0.0
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def test_no_float_artifacts():
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v = notional_to_amount(LIN, 0.0001 * PX * 72, price=PX) # 72 step esatti
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assert v == 0.0072 and abs(v - 0.0072) < 1e-12
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def test_target_notional_5050_weight():
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assert target_notional_usd(1.0, 0.5, 2000) == 1000
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assert target_notional_usd(2.0, 0.5, 2000) == 2000 # leva-cap 2x -> piena equity sull'asset
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assert target_notional_usd(0.0, 0.5, 2000) == 0.0
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def test_build_order_entry_linear():
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o = build_rebalance_order(LIN, target_fraction=1.0, weight=0.5,
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equity_usd=2000, current_pos_usd=0.0, price=PX)
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assert o["side"] == "buy" and o["reduce_only"] is False
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assert o["target_notional"] == 1000 and o["delta_notional"] == 1000
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assert abs(o["amount"] - 0.0156) < 1e-9 # 1000/64000=0.015625 -> 0.0156
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def test_build_order_exit_is_reduce_only():
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o = build_rebalance_order(LIN, target_fraction=0.0, weight=0.5,
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equity_usd=2000, current_pos_usd=1000.0, price=PX)
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assert o["side"] == "sell" and o["reduce_only"] is True and o["amount"] > 0
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def test_build_order_already_at_target_is_none():
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o = build_rebalance_order(LIN, 1.0, 0.5, 2000, current_pos_usd=1000.0, price=PX)
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assert o is None # delta 0 -> nessun ordine
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def test_build_order_subthreshold_is_none():
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# delta $2 (< mezzo step in notional, $3.2 a 64k) -> niente ordine
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o = build_rebalance_order(LIN, 1.0, 0.5, 2000, current_pos_usd=998.0, price=PX)
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assert o is None
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def test_partial_rebalance_direction():
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up = build_rebalance_order(LIN, 1.0, 0.5, 2000, 600.0, price=PX) # compra il delta
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dn = build_rebalance_order(LIN, 1.0, 0.5, 2000, 1400.0, price=PX) # vende il delta
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assert up["side"] == "buy" and up["delta_notional"] == 400
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assert dn["side"] == "sell" and dn["delta_notional"] == -400 and dn["reduce_only"] is False
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def test_disaster_stop_price():
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from src.live.deribit import disaster_stop_price
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assert disaster_stop_price(LIN, 64000, 0.30, long=True) == 44800.0 # -30%, al tick
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assert disaster_stop_price(LIN, 64000, 0.30, long=False) == 83200.0 # +30% (short)
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def test_parity_live_target_equals_backtest():
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from src.backtest.harness import load
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tp = TrendPortfolio(**CANONICAL)
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df = resample_1d(load("BTC", "1h"))
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assert tp.current_target(df) == tp.target_series(df)[-1]
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