49 lines
1.3 KiB
Python
49 lines
1.3 KiB
Python
from __future__ import annotations
|
|
|
|
from abc import ABC, abstractmethod
|
|
from enum import Enum
|
|
from typing import Dict, Optional, cast
|
|
|
|
import pandas as pd
|
|
from pt_trading.results import BacktestResult
|
|
from pt_trading.trading_pair import TradingPair
|
|
|
|
NanoPerMin = 1e9
|
|
|
|
|
|
class PairsTradingFitMethod(ABC):
|
|
TRADES_COLUMNS = [
|
|
"time",
|
|
"symbol",
|
|
"side",
|
|
"action",
|
|
"price",
|
|
"disequilibrium",
|
|
"scaled_disequilibrium",
|
|
"signed_scaled_disequilibrium",
|
|
"pair",
|
|
]
|
|
@staticmethod
|
|
def create(config: Dict) -> PairsTradingFitMethod:
|
|
import importlib
|
|
fit_method_class_name = config.get("fit_method_class", None)
|
|
assert fit_method_class_name is not None
|
|
module_name, class_name = fit_method_class_name.rsplit(".", 1)
|
|
module = importlib.import_module(module_name)
|
|
fit_method = getattr(module, class_name)()
|
|
return cast(PairsTradingFitMethod, fit_method)
|
|
|
|
@abstractmethod
|
|
def run_pair(
|
|
self, pair: TradingPair, bt_result: BacktestResult
|
|
) -> Optional[pd.DataFrame]: ...
|
|
|
|
@abstractmethod
|
|
def reset(self) -> None: ...
|
|
|
|
@abstractmethod
|
|
def create_trading_pair(
|
|
self, config: Dict, market_data: pd.DataFrame, symbol_a: str, symbol_b: str, price_column: str
|
|
) -> TradingPair: ...
|
|
|