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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/research_strategy.py
+30 -30
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@@ -1,56 +1,56 @@
from __future__ import annotations
from typing import Any, Dict, List, Optional
from typing import Any, Dict, List, Optional, Tuple
import pandas as pd
# ---
from cvttpy_tools.config import Config
# ---
from cvttpy_trading.trading.instrument import ExchangeInstrument
# ---
from pairs_trading.lib.pt_strategy.model_data_policy import ModelDataPolicy
from pairs_trading.lib.pt_strategy.pt_market_data import ResearchMarketData
from pairs_trading.lib.pt_strategy.pt_model import Prediction
from pairs_trading.lib.pt_strategy.trading_pair import PairState, TradingPair
from pairs_trading.lib.pt_strategy.trading_pair import PairState, TradingPair, ResearchTradingPair
class PtResearchStrategy:
config_: Dict[str, Any]
trading_pair_: TradingPair
config_: Config
trading_pair_: ResearchTradingPair
model_data_policy_: ModelDataPolicy
pt_mkt_data_: ResearchMarketData
trades_: List[pd.DataFrame]
predictions_: pd.DataFrame
predictions_df_: pd.DataFrame
def __init__(
self,
config: Dict[str, Any],
datafiles: List[str],
instruments: List[Dict[str, str]],
config: Config,
instruments: List[ExchangeInstrument]
):
from pairs_trading.lib.pt_strategy.model_data_policy import ModelDataPolicy
from pairs_trading.lib.pt_strategy.trading_pair import TradingPair
self.config_ = config
self.trades_ = []
self.trading_pair_ = TradingPair(config=config, instruments=instruments)
self.predictions_ = pd.DataFrame()
self.trading_pair_ = ResearchTradingPair(config=config, instruments=instruments)
self.predictions_df_ = pd.DataFrame()
import copy
# modified config must be passed to PtMarketData
config_copy = copy.deepcopy(config)
config_copy["instruments"] = instruments
config_copy["datafiles"] = datafiles
self.pt_mkt_data_ = ResearchMarketData(config=config_copy)
config_copy.set_value("instruments", instruments)
self.pt_mkt_data_ = ResearchMarketData(config=config_copy, instruments=instruments)
self.pt_mkt_data_.load()
self.model_data_policy_ = ModelDataPolicy.create(
Config(config_copy), mkt_data=self.pt_mkt_data_.market_data_df_, pair=self.trading_pair_
config_copy, mkt_data=self.pt_mkt_data_.market_data_df_, pair=self.trading_pair_
)
def outstanding_positions(self) -> List[Dict[str, Any]]:
return list(self.trading_pair_.user_data_.get("outstanding_positions", []))
def run(self) -> None:
training_minutes = self.config_.get("training_minutes", 120)
training_minutes = self.config_.get_value("training_minutes", 120)
market_data_series: pd.Series
market_data_df = pd.DataFrame()
@@ -74,8 +74,8 @@ class PtResearchStrategy:
prediction = self.trading_pair_.run(
market_data_df, self.model_data_policy_.advance(mkt_data_df=market_data_df)
)
self.predictions_ = pd.concat(
[self.predictions_, prediction.to_df()], ignore_index=True
self.predictions_df_ = pd.concat(
[self.predictions_df_, prediction.to_df()], ignore_index=True
)
assert prediction is not None
@@ -95,8 +95,8 @@ class PtResearchStrategy:
pair = self.trading_pair_
trades = None
open_threshold = self.config_["dis-equilibrium_open_trshld"]
close_threshold = self.config_["dis-equilibrium_close_trshld"]
open_threshold = self.config_.get_value("dis-equilibrium_open_trshld")
close_threshold = self.config_.get_value("dis-equilibrium_close_trshld")
scaled_disequilibrium = prediction.scaled_disequilibrium_
abs_scaled_disequilibrium = abs(scaled_disequilibrium)
@@ -145,7 +145,7 @@ class PtResearchStrategy:
if pair.user_data_["state"] == PairState.OPEN:
print(f"{pair}: *** Position is NOT CLOSED. ***")
# outstanding positions
if self.config_["close_outstanding_positions"]:
if self.config_.get_value("close_outstanding_positions", False):
close_position_row = pd.Series(pair.market_data_.iloc[-2])
# close_position_row["disequilibrium"] = 0.0
# close_position_row["scaled_disequilibrium"] = 0.0
@@ -161,14 +161,14 @@ class PtResearchStrategy:
pair.on_close_trades(trades)
else:
pair.add_outstanding_position(
symbol=pair.symbol_a_,
symbol=pair.symbol_a(),
open_side=pair.user_data_["open_side_a"],
open_px=pair.user_data_["open_px_a"],
open_tstamp=pair.user_data_["open_tstamp"],
last_mkt_data_row=pair.market_data_.iloc[-1],
)
pair.add_outstanding_position(
symbol=pair.symbol_b_,
symbol=pair.symbol_b(),
open_side=pair.user_data_["open_side_b"],
open_px=pair.user_data_["open_px_b"],
open_tstamp=pair.user_data_["open_tstamp"],
@@ -192,7 +192,7 @@ class PtResearchStrategy:
return pd.DataFrame(columns=columns).astype(types)
def _create_open_trades(
self, pair: TradingPair, row: pd.Series, prediction: Prediction
self, pair: ResearchTradingPair, row: pd.Series, prediction: Prediction
) -> Optional[pd.DataFrame]:
colname_a, colname_b = pair.exec_prices_colnames()
@@ -226,7 +226,7 @@ class PtResearchStrategy:
# create opening trades
df.loc[len(df)] = {
"time": tstamp,
"symbol": pair.symbol_a_,
"symbol": pair.symbol_a(),
"side": side_a,
"action": "OPEN",
"price": px_a,
@@ -237,7 +237,7 @@ class PtResearchStrategy:
}
df.loc[len(df)] = {
"time": tstamp,
"symbol": pair.symbol_b_,
"symbol": pair.symbol_b(),
"side": side_b,
"action": "OPEN",
"price": px_b,
@@ -249,7 +249,7 @@ class PtResearchStrategy:
return df
def _create_close_trades(
self, pair: TradingPair, row: pd.Series, prediction: Optional[Prediction] = None
self, pair: ResearchTradingPair, row: pd.Series, prediction: Optional[Prediction] = None
) -> Optional[pd.DataFrame]:
colname_a, colname_b = pair.exec_prices_colnames()
@@ -271,7 +271,7 @@ class PtResearchStrategy:
# create opening trades
df.loc[len(df)] = {
"time": tstamp,
"symbol": pair.symbol_a_,
"symbol": pair.symbol_a(),
"side": pair.user_data_["close_side_a"],
"action": "CLOSE",
"price": px_a,
@@ -282,7 +282,7 @@ class PtResearchStrategy:
}
df.loc[len(df)] = {
"time": tstamp,
"symbol": pair.symbol_b_,
"symbol": pair.symbol_b(),
"side": pair.user_data_["close_side_b"],
"action": "CLOSE",
"price": px_b,