research/stat_pairs_backtest
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This commit is contained in:
Oleg Sheynin
2026-01-12 21:26:15 +00:00
parent bd6cf1d4d0
commit c0fabcb429
15 changed files with 1205 additions and 568 deletions
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lib/pt_strategy/model_data_policy.py
+11 -9
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@@ -25,7 +25,7 @@ class ModelDataPolicy(ABC):
def __init__(self, config: Config, *args: Any, **kwargs: Any):
self.config_ = config
self.current_data_params_ = DataWindowParams(
training_size_=config.get_value("training_size", 120),
training_size_=config.get_value("model/training_size", 120),
training_start_index_=0,
)
self.count_ = 0
@@ -34,14 +34,15 @@ class ModelDataPolicy(ABC):
@abstractmethod
def advance(self, mkt_data_df: Optional[pd.DataFrame] = None) -> DataWindowParams:
self.count_ += 1
print(self.count_, end="\r")
if not self.is_real_time_:
print(self.count_, end="\r")
return self.current_data_params_
@staticmethod
def create(config: Config, *args: Any, **kwargs: Any) -> ModelDataPolicy:
import importlib
model_data_policy_class_name = config.get_value("model_data_policy_class", None)
model_data_policy_class_name = config.get_value("model/model_data_policy_class", None)
assert model_data_policy_class_name is not None
module_name, class_name = model_data_policy_class_name.rsplit(".", 1)
module = importlib.import_module(module_name)
@@ -59,7 +60,9 @@ class RollingWindowDataPolicy(ModelDataPolicy):
def advance(self, mkt_data_df: Optional[pd.DataFrame] = None) -> DataWindowParams:
super().advance(mkt_data_df)
if self.is_real_time_:
self.current_data_params_.training_start_index_ = -self.current_data_params_.training_size_
self.current_data_params_.training_start_index_ = 0
if mkt_data_df and len(mkt_data_df) > self.curren_data_params_.training_size_:
self.current_data_params_.training_start_index_ = -self.curren_data_params_.training_size_
else:
self.current_data_params_.training_start_index_ += 1
return self.current_data_params_
@@ -79,11 +82,10 @@ class OptimizedWndDataPolicy(ModelDataPolicy, ABC):
assert (
kwargs.get("pair") is not None
), "pair must be provided"
assert (
"min_training_size" in config.data() and "max_training_size" in config.data()
), "min_training_size and max_training_size must be provided"
self.min_training_size_ = cast(int, config.get_value("min_training_size"))
self.max_training_size_ = cast(int, config.get_value("max_training_size"))
assert (config.key_exists("model/max_training_size") and config.key_exists("model/min_training_size")
), "min_training_size and max_training_size must be provided"
self.min_training_size_ = cast(int, config.get_value("model/min_training_size"))
self.max_training_size_ = cast(int, config.get_value("model/max_training_size"))
from pairs_trading.lib.pt_strategy.trading_pair import TradingPair
self.pair_ = cast(TradingPair, kwargs.get("pair"))