Test New Idea

Here’s a complete QuantConnect algorithm implementing your strategy for TQQQ as described:

from AlgorithmImports import *

class DigitallTQQQStrategy(QCAlgorithm):
    """
    Digitall’s intraday strategy for TQQQ

    1. Build 5-minute TradeBars from minute data.
    2. Analyse the first 5-minute candle of each session:
       • Doji (open ≈ close) → no trade that day.  
       • Green candle        → go long with 25 % of portfolio
       • Red candle          → go short with 25 % of portfolio
       (entries are executed at the OPEN of the second 5-minute bar)
    3. After entry, place a stop-loss = 5 % of the current 14-day ATR (daily).
    4. Liquidate any remaining position one minute before the market close.
    5. At most one trade per day.
    """

    def initialize(self) -> None:
        # 1. Back-test parameters
        self.set_start_date(2021, 1, 1)
        self.set_end_date(2022, 1, 1)
        self.set_cash(100_000)

        # 2. Asset subscription
        self._tqqq: Symbol = self.add_equity("TQQQ", Resolution.MINUTE).symbol

        # 3. Indicator – 14-day ATR on daily data
        self._atr = self.atr(self._tqqq, 14, MovingAverageType.SIMPLE, Resolution.DAILY)
        self.set_warmup(timedelta(days=30), Resolution.DAILY)

        # 4. Schedule end-of-day liquidation (1 min before close)
        self.schedule.on(
            self.date_rules.every_day(self._tqqq),
            self.time_rules.before_market_close(self._tqqq, 1),
            self._close_positions_before_eod,
        )

        # 5. Daily-scope state variables
        self._current_day = None            # type: Optional[datetime.date]
        self._first_candle_analyzed = False
        self._trade_direction = 0           # +1 long, −1 short, 0 none
        self._trade_opened_today = False
        self._entry_ticket: Optional[OrderTicket] = None
        self._stop_price: float = 0.0
        self._epsilon: float = 1e-6

        # 6. 5-minute consolidator (added after warm-up)
        self._five_min_consolidator: Optional[IDataConsolidator] = None

    # ----------------------------------------------------------- #
    # Attach the consolidator once warm-up is finished
    def on_warmup_finished(self) -> None:
        self._five_min_consolidator = TradeBarConsolidator(timedelta(minutes=5))
        self._five_min_consolidator.data_consolidated += self._on_five_minute_bar
        self.subscription_manager.add_consolidator(self._tqqq, self._five_min_consolidator)

    # ----------------------------------------------------------- #
    # 5-minute bar handler
    def _on_five_minute_bar(self, sender: object, bar: TradeBar) -> None:
        # New trading day → reset flags
        if self._current_day != bar.time.date():
            self._reset_daily_flags(bar.time.date())

        if not self._atr.is_ready:
            return

        # FIRST 5-MINUTE CANDLE
        if not self._first_candle_analyzed:
            self._first_candle_analyzed = True

            if abs(bar.close - bar.open) <= self._epsilon:     # Doji → no trade
                self._trade_direction = 0
                return

            self._trade_direction = 1 if bar.close > bar.open else -1
            return                                              # wait for next bar

        # SECOND 5-MINUTE CANDLE → entry
        if (
            not self._trade_opened_today
            and self._trade_direction != 0
            and not self.portfolio.invested
        ):
            self._enter_position(bar)

    # ----------------------------------------------------------- #
    # Minute data – stop-loss monitoring
    def on_data(self, data: Slice) -> None:
        if (
            not self._trade_opened_today
            or not self.portfolio[self._tqqq].invested
            or not data.contains_key(self._tqqq)
        ):
            return

        price = data[self._tqqq].price

        # LONG stop
        if self._trade_direction == 1 and price <= self._stop_price - self._epsilon:
            self.liquidate(self._tqqq, "Stop-loss hit (long)")
            self._trade_direction = 0

        # SHORT stop
        elif self._trade_direction == -1 and price >= self._stop_price + self._epsilon:
            self.liquidate(self._tqqq, "Stop-loss hit (short)")
            self._trade_direction = 0

    # ----------------------------------------------------------- #
    # Entry helper
    def _enter_position(self, bar: TradeBar) -> None:
        price = bar.open
        if price <= 0:
            self.debug("Invalid price – aborting entry")
            return

        target_value = self.portfolio.total_portfolio_value * 0.25
        quantity = int(math.floor(target_value / price))
        if quantity == 0:
            self.debug("Quantity is zero – entry skipped")
            return

        quantity *= self._trade_direction
        self._entry_ticket = self.market_order(self._tqqq, quantity, False, "Daily entry")

        # Stop-loss = 5 % of ATR
        stop_distance = self._atr.current.value * 0.05
        if stop_distance <= 0:
            self.debug("ATR invalid – stop-loss not set")
            return

        self._stop_price = (
            price - stop_distance if self._trade_direction == 1
            else price + stop_distance
        )
        self._trade_opened_today = True

    # ----------------------------------------------------------- #
    # End-of-day liquidation
    def _close_positions_before_eod(self) -> None:
        if self.portfolio[self._tqqq].invested:
            self.liquidate(self._tqqq, "End-of-day liquidation")
        self._trade_direction = 0

    # ----------------------------------------------------------- #
    # Reset all per-day flags
    def _reset_daily_flags(self, new_day: datetime.date) -> None:
        self._current_day = new_day
        self._first_candle_analyzed = False
        self._trade_direction = 0
        self._trade_opened_today = False
        self._entry_ticket = None
        self._stop_price = 0.0

How it works:

• Sets up a 5-minute TradeBar consolidator for TQQQ minute data.
• Each morning, analyzes the first 5-minute candle:
  • If open == close, does nothing.
  • Otherwise, goes long (if close > open) or short (if close < open) at the open of the second 5-minute bar, using 25% of portfolio.
• Uses a 14-day ATR (daily) and calculates stop loss as 5% of ATR from entry.
• Monitors for stop loss throughout the day.
• Automatically exits any open position one minute before the market closes.

Let me know if you want to tweak anything or need help deploying/running this algo!

Sources: docs writing algorithms securities asset classes us equity handling data, docs writing algorithms trading and orders order management order tickets, docs writing algorithms portfolio key concepts, docs writing algorithms securities asset classes us equity shorting, Bear Call Ladder - QuantConnect.com