Add price_data_delay_tolerance hint

tests/backtest/test_backtest_execution.py

@@ -5,8 +5,10 @@
 import logging
 from decimal import Decimal
 
+import pandas as pd
 import pytest
 
+from tradeexecutor.backtest.backtest_runner import guess_data_delay_tolerance
 from tradeexecutor.state.identifier import AssetIdentifier
 from tradeexecutor.state.trade import TradeStatus
 from tradeexecutor.strategy.reserve_currency import ReserveCurrency
@@ -260,7 +262,7 @@ def test_buy_with_fee(
     logger: logging.Logger,
     state: State,
     wallet: SimulatedWallet,
-        strategy_universe,
+    strategy_universe,
     routing_model: BacktestRoutingModel,
     pricing_model: BacktestPricing,
     wbnb: AssetIdentifier,
@@ -341,3 +343,11 @@ def test_buy_sell_backtest_with_fee(
     # Check our wallet was credited
     assert wallet.get_balance(busd.address) == pytest.approx(Decimal('9990.040840796019796453251579'))
     assert wallet.get_balance(wbnb.address) == 0
+
+
+def test_price_data_tolerance(
+    strategy_universe,
+):
+    """Workaround for Uni v3 issues"""
+    strategy_universe.price_data_delay_tolerance = datetime.timedelta(days=365)
+    assert guess_data_delay_tolerance(strategy_universe) == pd.Timedelta(days=365)

tradeexecutor/backtest/backtest_runner.py

@@ -1025,7 +1025,10 @@ def guess_data_delay_tolerance(universe: TradingStrategyUniverse) -> pd.Timedelt
 
     This could work around some data quality issues or early historical data.
     """
-    if universe.data_universe.time_bucket == TimeBucket.d7:
+
+    if universe.price_data_delay_tolerance:
+        return pd.Timedelta(universe.price_data_delay_tolerance)
+    elif universe.data_universe.time_bucket == TimeBucket.d7:
         data_delay_tolerance = pd.Timedelta("9d")
     else:
         data_delay_tolerance = pd.Timedelta("2d")

tradeexecutor/strategy/trading_strategy_universe.py

@@ -171,6 +171,16 @@ class TradingStrategyUniverse(StrategyExecutionUniverse):
     #:
     options: UniverseOptions | None = None
 
+    #: How much lag we allow in the price feed.
+    #:
+    #: This can be set for a very high value when working with open ended universes where the liquidity pools are
+    #: disappear when liquidity providers leave.
+    #:
+    #: TODO: Use carefully - this is mostly a workaround variable and
+    #: will have a more robust TVL/liquidity solution in the future.
+    #:
+    price_data_delay_tolerance: datetime.timedelta | None = None
+
     def __repr__(self):
         pair_count = self.data_universe.pairs.get_count()
         if pair_count <= 3: