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outstanding positions bug fix

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This commit is contained in:
Oleg Sheynin
2025-07-15 00:10:46 +00:00
parent 94ffb32f50
commit 80cf1b60ef
5 changed files with 166 additions and 99 deletions
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lib/pt_trading/fit_methods.py
+48 -27
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@@ -276,25 +276,27 @@ class SlidingFit(PairsTradingFitMethod):
if len(pair.training_df_) < training_minutes:
print(
f"{pair}: {self.curr_training_start_idx_} Not enough training data. Completing the job."
f"{pair}: current offset={self.curr_training_start_idx_}"
f" * Training data length={len(pair.training_df_)} < {training_minutes}"
" * Not enough training data. Completing the job."
)
if pair.user_data_["state"] == PairState.OPEN:
print(
f"{pair}: {self.curr_training_start_idx_} Position is not closed."
)
# outstanding positions
# last_row_index = self.curr_training_start_idx_ + training_minutes
if pair.predicted_df_ is not None:
bt_result.handle_outstanding_position(
pair=pair,
pair_result_df=pair.predicted_df_,
last_row_index=0,
open_side_a=pair.user_data_["open_side_a"],
open_side_b=pair.user_data_["open_side_b"],
open_px_a=pair.user_data_["open_px_a"],
open_px_b=pair.user_data_["open_px_b"],
open_tstamp=pair.user_data_["open_tstamp"],
)
# if pair.user_data_["state"] == PairState.OPEN:
# print(
# f"{pair}: {self.curr_training_start_idx_} Position is not closed."
# )
# # outstanding positions
# # last_row_index = self.curr_training_start_idx_ + training_minutes
# if pair.predicted_df_ is not None:
# bt_result.handle_outstanding_position(
# pair=pair,
# pair_result_df=pair.predicted_df_,
# last_row_index=0,
# open_side_a=pair.user_data_["open_side_a"],
# open_side_b=pair.user_data_["open_side_b"],
# open_px_a=pair.user_data_["open_px_a"],
# open_px_b=pair.user_data_["open_px_b"],
# open_tstamp=pair.user_data_["open_tstamp"],
# )
break
try:
@@ -367,6 +369,25 @@ class SlidingFit(PairsTradingFitMethod):
pair.add_trades(close_trades)
pair.user_data_["state"] = PairState.CLOSED
# Outstanding positions
if pair.user_data_["state"] == PairState.OPEN:
print(
f"{pair}: *** Position is NOT CLOSED. ***"
)
# outstanding positions
# last_row_index = self.curr_training_start_idx_ + training_minutes
if pair.predicted_df_ is not None:
bt_result.handle_outstanding_position(
pair=pair,
pair_result_df=pair.predicted_df_,
last_row_index=0,
open_side_a=pair.user_data_["open_side_a"],
open_side_b=pair.user_data_["open_side_b"],
open_px_a=pair.user_data_["open_px_a"],
open_px_b=pair.user_data_["open_px_b"],
open_tstamp=pair.user_data_["open_tstamp"],
)
def _get_open_trades(
self, pair: TradingPair, row: pd.Series, open_threshold: float
) -> Optional[pd.DataFrame]:
@@ -386,15 +407,15 @@ class SlidingFit(PairsTradingFitMethod):
open_px_a = open_row[f"{colname_a}"]
open_px_b = open_row[f"{colname_b}"]
# Ensure scalars for handle_outstanding_position
if isinstance(open_px_a, pd.Series):
open_px_a = open_px_a.iloc[0]
if isinstance(open_px_b, pd.Series):
open_px_b = open_px_b.iloc[0]
if isinstance(open_tstamp, pd.Series):
open_tstamp = open_tstamp.iloc[0]
open_px_a = float(open_px_a)
open_px_b = float(open_px_b)
open_tstamp = pd.Timestamp(open_tstamp)
# if isinstance(open_px_a, pd.Series):
# open_px_a = open_px_a.iloc[0]
# if isinstance(open_px_b, pd.Series):
# open_px_b = open_px_b.iloc[0]
# if isinstance(open_tstamp, pd.Series):
# open_tstamp = open_tstamp.iloc[0]
# open_px_a = float(open_px_a)
# open_px_b = float(open_px_b)
# open_tstamp = pd.Timestamp(open_tstamp)
if open_scaled_disequilibrium < open_threshold:
return None