research/stat_pairs_backtest
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This commit is contained in:
Oleg Sheynin
2026-01-11 13:33:58 +00:00
parent 6dd0f97d74
commit b196863a34
26 changed files with 5365 additions and 5566 deletions
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lib/pt_strategy/model_data_policy.py
+16 -23
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@@ -12,8 +12,8 @@ from cvttpy_tools.config import Config
@dataclass
class DataWindowParams:
training_size: int
training_start_index: int
training_size_: int
training_start_index_: int
class ModelDataPolicy(ABC):
@@ -24,16 +24,9 @@ class ModelDataPolicy(ABC):
def __init__(self, config: Config, *args: Any, **kwargs: Any):
self.config_ = config
training_size = config.get_value("training_size", 120)
training_start_index = 0
if kwargs.get("is_real_time", False):
training_size = 120
training_start_index = 0
else:
training_size = config.get_value("training_size", 120)
self.current_data_params_ = DataWindowParams(
training_size=config.get_value("training_size", 120),
training_start_index=0,
training_size_=config.get_value("training_size", 120),
training_start_index_=0,
)
self.count_ = 0
self.is_real_time_ = kwargs.get("is_real_time", False)
@@ -66,9 +59,9 @@ 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_ = -self.current_data_params_.training_size_
else:
self.current_data_params_.training_start_index += 1
self.current_data_params_.training_start_index_ += 1
return self.current_data_params_
@@ -111,12 +104,12 @@ class OptimizedWndDataPolicy(ModelDataPolicy, ABC):
if self.is_real_time_:
self.end_index_ = len(self.mkt_data_df_) - 1
else:
self.end_index_ = self.current_data_params_.training_start_index + self.max_training_size_
self.end_index_ = self.current_data_params_.training_start_index_ + self.max_training_size_
if self.end_index_ > len(self.mkt_data_df_) - 1:
self.end_index_ = len(self.mkt_data_df_) - 1
self.current_data_params_.training_start_index = self.end_index_ - self.max_training_size_
if self.current_data_params_.training_start_index < 0:
self.current_data_params_.training_start_index = 0
self.current_data_params_.training_start_index_ = self.end_index_ - self.max_training_size_
if self.current_data_params_.training_start_index_ < 0:
self.current_data_params_.training_start_index_ = 0
col_a, col_b = self.pair_.colnames()
self.prices_a_ = np.array(self.mkt_data_df_[col_a])
@@ -153,8 +146,8 @@ class EGOptimizedWndDataPolicy(OptimizedWndDataPolicy):
eg_pvalue = float(coint(series_a, series_b)[1])
if eg_pvalue < last_pvalue:
last_pvalue = eg_pvalue
result.training_size = trn_size
result.training_start_index = start_index
result.training_size_ = trn_size
result.training_start_index_ = start_index
# print(
# f"*** DEBUG *** end_index={self.end_index_}, best_trn_size={self.current_data_params_.training_size}, {last_pvalue=}"
@@ -197,8 +190,8 @@ class ADFOptimizedWndDataPolicy(OptimizedWndDataPolicy):
if adf_pvalue < last_pvalue:
last_pvalue = adf_pvalue
result.training_size = trn_size
result.training_start_index = start_index
result.training_size_ = trn_size
result.training_start_index_ = start_index
# print(
# f"*** DEBUG *** end_index={self.end_index_},"
@@ -247,8 +240,8 @@ class JohansenOptdWndDataPolicy(OptimizedWndDataPolicy):
continue
if best_trn_size > 0:
result.training_size = best_trn_size
result.training_start_index = best_start_index
result.training_size_ = best_trn_size
result.training_start_index_ = best_start_index
else:
print("*** WARNING: No valid cointegration window found.")