# --- Do not remove these libs --- from freqtrade.strategy import IStrategy,merge_informative_pair from typing import Dict, List from functools import reduce from pandas import DataFrame from datetime import datetime, timedelta, timezone from typing import Optional from freqtrade.strategy import CategoricalParameter, DecimalParameter, IntParameter from freqtrade.persistence import PairLocks import logging import json import os # -------------------------------- import talib.abstract as ta import freqtrade.vendor.qtpylib.indicators as qtpylib from freqtrade.persistence import Trade, Order from typing import Optional, Tuple, Union from freqtrade.strategy import stoploss_from_open logger = logging.getLogger(__name__) class DCADMIPRICEStrategySpot(IStrategy): INTERFACE_VERSION: int = 3 can_short = False position_adjustment_enable = True max_entry_position_adjustment = -1 amend_last_stake_amount = True minimal_roi = { "0": 1 } stoploss = -0.99 # Trailing stop: trailing_stop = True trailing_stop_positive = 0.02 trailing_stop_positive_offset = 0.05 trailing_only_offset_is_reached = True order_types = { 'entry': 'market', 'exit': 'market', 'stoploss': 'market', 'stoploss_on_exchange': False } # Optional order time in force. order_time_in_force = { 'entry': 'GTC', 'exit': 'GTC' } adxWindow = IntParameter(7, 21, default=24, space="buy") adxThr = IntParameter(15, 35, default=25, space="buy") emaThrLong = IntParameter(5, 55, default=24, space="buy") emaThrShort = IntParameter(5, 55, default=24, space="buy") initStakeAmount = 10 stakeAmountPeriod = 10 smallGridPercent = 0.02 bigGridPercent = 0.1 # Optimal timeframe for the strategy timeframe = '1m' inf_tf = '4h' def informative_pairs(self): # get access to all pairs available in whitelist. pairs = self.dp.current_whitelist() # Assign tf to each pair so they can be downloaded and cached for strategy. informative_pairs = [(pair, self.inf_tf) for pair in pairs] return informative_pairs def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: adxWindow = self.adxWindow.value informative = self.dp.get_pair_dataframe(pair=metadata['pair'], timeframe=self.inf_tf) informative['plus_di'] = ta.PLUS_DI(informative,adxWindow) informative['minus_di'] = ta.MINUS_DI(informative,adxWindow) informative['emaLong'] = ta.EMA(informative, timeperiod=self.emaThrLong.value) informative['emaShort'] = ta.EMA(informative, timeperiod=self.emaThrShort.value) dataframe = merge_informative_pair(dataframe, informative, self.timeframe, self.inf_tf, ffill=True) return dataframe def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: """ Based on TA indicators, populates the buy signal for the given dataframe :param dataframe: DataFrame :return: DataFrame with buy column """ dataframe.loc[ ( # (dataframe['close'] < dataframe[f'emaLong_{self.inf_tf}']) # & # (dataframe[f'plus_di_{self.inf_tf}'] > dataframe[f'minus_di_{self.inf_tf}']) & (dataframe[f'plus_di_{self.inf_tf}']>self.adxThr.value) (dataframe['close'] > 0) ), 'enter_long'] = 1 return dataframe def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: """ Based on TA indicators, populates the sell signal for the given dataframe :param dataframe: DataFrame :return: DataFrame with buy column """ dataframe.loc[ ( ), 'exit_long'] = 0 dataframe.loc[ ( ), 'exit_short'] = 0 return dataframe # the initial order (opening trade) def custom_stake_amount(self, pair: str, current_time: datetime, current_rate: float, proposed_stake: float, min_stake: Optional[float], max_stake: float, leverage: float, entry_tag: Optional[str], side: str, **kwargs) -> float: return self.initStakeAmount def order_filled(self, pair: str, trade: Trade, order: Order, current_time: datetime, **kwargs) -> None: increase_tag = 'Increase Postion' decrease_tag = 'Decrease Postion' stoploss_tag = 'Stoploss Postion' filled_entries = trade.select_filled_orders() first_order = filled_entries[0] if first_order.order_id != order.order_id: # Not trade's first order return None # trade's first order metadataMap = {} metadataMap['stakeAmountList'] = [] metadataMap['smallGrid'] = 0.0 metadataMap['bigGrid'] = 0.0 metadataMap['lineList'] = [] metadataMap['fistOrderPrice'] = 0.0 metadataMap['vaildOrderIDs'] = [] current_rate = first_order.safe_price metadataMap['fistOrderPrice'] = current_rate # init stakeAmount metadataMap['stakeAmountList'] = [self.initStakeAmount, self.initStakeAmount+1*self.stakeAmountPeriod, self.initStakeAmount+2*self.stakeAmountPeriod] # init small price grid metadataMap['smallGrid'] = current_rate*self.smallGridPercent # init big price grid metadataMap['bigGrid'] = current_rate*self.bigGridPercent # init line if trade.entry_side == "buy" : metadataMap['lineList'] = [current_rate, current_rate-1*metadataMap['bigGrid'],current_rate-2*metadataMap['bigGrid'],current_rate-3*metadataMap['bigGrid']] elif trade.entry_side == "sell" : metadataMap['lineList'] = [current_rate, current_rate+1*metadataMap['bigGrid'],current_rate+2*metadataMap['bigGrid'],current_rate+3*metadataMap['bigGrid']] # init orderIDS metadataMap['vaildOrderIDs'] = [order.order_id] logger.info(f"init metadata, metadataMap {metadataMap}") trade.set_custom_data(key='GRIDMETADATAS',value=metadataMap) return None # GRID ORDERs def adjust_trade_position(self, trade: Trade, current_time: datetime, current_rate: float, current_profit: float, min_stake: Optional[float], max_stake: float, current_entry_rate: float, current_exit_rate: float, current_entry_profit: float, current_exit_profit: float, **kwargs ) -> Union[Optional[float], Tuple[Optional[float], Optional[str]]]: # --------------- read and check metadata ----------------- metadataMap = trade.get_custom_data(key='GRIDMETADATAS') lineList = metadataMap['lineList'] if len(lineList) != 4 : logger.error(f"{trade.pair} lineList is not 4, lineMap: {lineList}") return None smallGrid = metadataMap['smallGrid'] if smallGrid == 0.0 : logger.error(f"{trade.pair} smallGrid is 0, smallGrid: {smallGrid}") return None bigGrid = metadataMap['bigGrid'] if bigGrid == 0.0 : logger.error(f"{trade.pair} bigGrid is 0, bigGrid: {bigGrid}") return None stakeAmountList = metadataMap['stakeAmountList'] if len(stakeAmountList) != 3 : logger.error(f"{trade.pair} stakeAmountList is not 3, stakeAmountList: {stakeAmountList}") return None vaildOrderIDs = metadataMap['vaildOrderIDs'] if len(vaildOrderIDs) == 0 : logger.error(f"{trade.pair} vaildOrderIDs is 0, vaildOrderIDs: {vaildOrderIDs}") return None # ---------------- GRID stoploss position -------------- stoplossStartLine = lineList[0] # stoploss start line stoplossEndLine = lineList[1] # stoploss end line stoplossTriggerLine = lineList[3] # stoploss trigger line stoplossNextGridStackAmount = stakeAmountList[1] # stoploss next grid stack amount # ---------------- GRID increse position --------------- line0 = lineList[0] line1 = lineList[1] line2 = lineList[2] line3 = lineList[3] stakeAmount1 = stakeAmountList[0] # between line0 - line1 stakeAmount2 = stakeAmountList[1] # between line1 - line2 stakeAmount3 = stakeAmountList[2] # between line2 - line3 lastOperateOrder = find_last_operate_order(trade) if lastOperateOrder == None: logger.error(f"{trade.pair} lastOperateOrder is None") return None # long trade increase postion where curPrice <= lastPrice - GridPrice if trade.entry_side == 'buy' : if current_rate <= lastOperateOrder.safe_price - smallGrid: try: priod = (line0 - current_rate) / bigGrid stake_amount = stakeAmount1 + self.stakeAmountPeriod * int(priod) return stake_amount, f'Increase Postion, stake_amount: {stake_amount}, lastorderprice {lastOperateOrder.safe_price}, currentrate: {current_rate}, lines: {lineList}' except Exception as exception: return None return None def find_last_operate_order(trade: Trade) -> Order: stop_loss_tag = 'Stoploss Postion' filled_entries = trade.select_filled_orders() for order in reversed(filled_entries): if stop_loss_tag not in order.ft_order_tag: # exclude stoploss order return order return None def find_last_valid_order(trade: Trade, orderID: str) -> Order: filled_entries = trade.select_filled_orders() for order in reversed(filled_entries): if orderID == order.order_id: # exclude stoploss order return order return None def find_valid_buyorders_betweenline(trade: Trade, vaildOrderIDs: List[str], lineUp: float, lineDown: float) -> List[Order]: filled_entries = trade.select_filled_orders() vaild_orders: List[Order] = [] for order in filled_entries: if order.order_id in vaildOrderIDs and lineUp >= order.safe_price and order.safe_price > lineDown: vaild_orders.append(order) return vaild_orders def find_valid_sellorders_betweenline(trade: Trade, vaildOrderIDs: List[str], lineDown: float, lineUp: float) -> List[Order]: filled_entries = trade.select_filled_orders() vaild_orders: List[Order] = [] for order in filled_entries: if order.order_id in vaildOrderIDs and lineUp > order.safe_price and order.safe_price >= lineDown: vaild_orders.append(order) return vaild_orders def removeStoplossOrderIDs(metaDataOrderIDs: List[str],toRemoveOrderIDs: List[str]) -> List[str]: valid_order_ids: List[str]= [] for metaOrderID in metaDataOrderIDs: if metaOrderID not in toRemoveOrderIDs: valid_order_ids.append(metaOrderID) return valid_order_ids