Volatility-targeted sizing for an opening range breakout

1"""Volatility-targeted sizing for a 15-minute opening range breakout, on Micro E-mini S&P 500 (MES).2 3The entries and exits stay the same; only the size changes. The paper compares three ways to size it.4 5Rules:6  1. The trade is the 15-minute opening range breakout: the first 5-minute close outside the 09:30-09:457     ET range, until 12:00 ET, stop at the other side, target 2 times the risk, flat at 15:55 ET.8  2. Volatility is the standard deviation of the last `vol_len` (20) daily returns (regular-session9     closes); its long-run level is the average of that over the last 250 days.10  3. Size (`sizing` "vol"): risk `risk_usd` (250) dollars times long-run volatility over current11     volatility, between 0.25 and `cap` (2) times, in micro contracts, rounded down, at least 1.12     "risk" risks a flat 250 dollars a trade; "fixed" trades `contracts` (2) micros every time.13"""14import math15 16import qy17 18 19def ready(*values):20    """True when every value is a number (indicators have no value until they have enough data)."""21    return all(v is not None and v == v for v in values)22 23 24class Bot(qy.Strategy):25    """The opening range breakout, sized to volatility."""26 27    symbol = "MES"28    timeframe = "5m"29    session = "rth"30    params = {"sizing": "vol", "vol_len": 20, "cap": 2.0, "contracts": 2, "risk_usd": 250, "max_contracts": 50}31    max_position = 5032    entry_window = ("09:45", "12:00")33    flatten_time = "15:55"34    overnight = False35 36    def setup(self):37        self.or_high, self.or_low = self.opening_range(minutes=15)38        self.day = None39        self.last = None40        self.closes, self.vols = [], []41        self.done_day = None42 43    def _scale(self):44        n = self.p.vol_len45        if len(self.closes) <= n or not self.vols:46            return 1.047        rets = [math.log(b / a) for a, b in zip(self.closes[-n - 1:-1], self.closes[-n:])]48        m = sum(rets) / n49        vol = math.sqrt(sum((r - m) ** 2 for r in rets) / (n - 1))50        long_run = sum(self.vols) / len(self.vols)51        return max(0.25, min(self.p.cap, long_run / vol)) if vol > 0 else 1.052 53    def _size(self, risk_points):54        if self.p.sizing == "fixed":55            return self.p.contracts56        budget = self.p.risk_usd * (self._scale() if self.p.sizing == "vol" else 1.0)57        per_contract = risk_points * self.point_value58        n = int(budget // per_contract) if per_contract > 0 else 159        return max(1, min(self.p.max_contracts, n))60 61    def _end_of_day(self):62        self.closes = (self.closes + [self.last])[-300:]63        n = self.p.vol_len64        if len(self.closes) > n:65            rets = [math.log(b / a) for a, b in zip(self.closes[-n - 1:-1], self.closes[-n:])]66            m = sum(rets) / n67            self.vols = (self.vols + [math.sqrt(sum((r - m) ** 2 for r in rets) / (n - 1))])[-250:]68 69    def on_bar(self, bar):70        if bar.date != self.day:71            if self.day is not None:72                self._end_of_day()73            self.day = bar.date74        self.last = bar.close75        high, low = self.or_high[0], self.or_low[0]76        if not ready(high, low) or self.done_day == bar.date or not self.position.is_flat:77            return78        close = bar.close79        if low <= close <= high:80            return81        self.done_day = bar.date82        if bar.dt.hour * 60 + bar.dt.minute + 5 > 720:83            return84        f = self._scale()85        if close > high:86            self.buy(self._size(close - low), stop_price=low, target_r=2.0, tag=f"ORB long | f={f:.4f}")87        else:88            self.sell(self._size(high - close), stop_price=high, target_r=2.0, tag=f"ORB short | f={f:.4f}")