Dca Weekly

position_adjustment_enable = True
max_entry_position_adjustment = 26   # cap on number of weekly adds
max_dca_multiplier = 27.0            # 1 initial + 26 adds

from freqtrade.strategy import IStrategy
from freqtrade.persistence import Trade
from datetime import datetime
import pandas as pd


class WeeklyDcaBtcStrategy(IStrategy):
    minimal_roi = {"0": 100.0}   # never exit on profit target
    stoploss = -0.99             # never exit on stop
    trailing_stop = False
    timeframe = "1d"
    process_only_new_candles = True
    startup_candle_count = 5
    can_short = False

    # The piece naive translations miss.
    position_adjustment_enable = True
    max_entry_position_adjustment = 26   # ~6 months of weekly buys
    max_dca_multiplier = 27.0            # 1 initial + 26 weekly adds

    def populate_indicators(self, dataframe: pd.DataFrame, metadata: dict) -> pd.DataFrame:
        dataframe["dow"] = pd.to_datetime(dataframe["date"]).dt.dayofweek
        return dataframe

    def populate_entry_trend(self, dataframe: pd.DataFrame, metadata: dict) -> pd.DataFrame:
        # Initial entry on the first Monday encountered.
        dataframe.loc[(dataframe["dow"] == 0) & (dataframe["volume"] > 0), "enter_long"] = 1
        return dataframe

    def populate_exit_trend(self, dataframe: pd.DataFrame, metadata: dict) -> pd.DataFrame:
        return dataframe

    def custom_stake_amount(self, pair: str, current_time: datetime, current_rate: float,
                            proposed_stake: float, min_stake, max_stake: float,
                            leverage: float, entry_tag, side: str, **kwargs) -> float:
        # Reserve room for the future weekly adds.
        return proposed_stake / self.max_dca_multiplier

    def adjust_trade_position(self, trade: Trade, current_time: datetime,
                              current_rate: float, current_profit: float,
                              min_stake, max_stake: float,
                              current_entry_rate: float, current_exit_rate: float,
                              current_entry_profit: float, current_exit_profit: float,
                              **kwargs):
        if trade.has_open_orders:
            return None
        if current_time.weekday() != 0:   # Monday only
            return None
        # Skip the Monday on which the initial entry was placed (Freqtrade
        # calls adjust_trade_position on the same candle as the initial
        # entry; without this guard you double-buy on week 1).
        filled = trade.select_filled_orders(trade.entry_side)
        if filled:
            last_dt = filled[-1].order_filled_utc
            if last_dt and last_dt.date() == current_time.date():
                return None
        # Buy the same notional as the initial entry every Monday.
        first_stake = filled[0].stake_amount_filled if filled else (min_stake or 10)
        return (first_stake, "weekly_dca")

{
  "exchange": { "name": "hyperliquid", "pair_whitelist": ["BTC/USDC"] },
  "stake_currency": "USDC",
  "stake_amount": 1000,
  "dry_run_wallet": {"USDC": 10000},
  "timeframe": "1d",
  "max_open_trades": 1,
  "stoploss": -0.99,
  "minimal_roi": { "0": 100.0 },
  "entry_pricing": { "price_side": "same" },
  "exit_pricing": { "price_side": "same" },
  "pairlists": [{ "method": "StaticPairList" }]
}