{"approach": "Spread-3-only demand-calibrated tick-1 YES stock. Each instance copies the base P/C dictionaries and uses the unchanged self.s inference; only self.s == 3 receives the new stock-estimation parameters and rule. Every original constant is retained. The proxy observes public sell-filled quantities while the primary ask has at least 5.0 notional and lies more than max(0.005, two modeled one-step standard deviations) above the belief. It skips competitor-ask increases exceeding one tick and corrects the observed notional for clipping at the quoted size using the base lognormal model. A 200-exposure prior at 0.6 notional per step shrinks the estimate; the existing tick-1 stock target is multiplied by the estimated flow divided by 0.6, clipped to [0.5, 2.0]. This is a noisy public-fill proxy, not knowledge of the aggressor or hidden retail parameters. Constants were screened first: larger ordinary size, ask caps, stock banks, entry thresholds, cash budgets, cover windows and side-specific risk; second ask levels, including persistent FIFO versions, were also screened. The final rule had the highest mean of five full-range finalists in both A (470 spread-3 runs from 4000-5999) and B (523 spread-3 runs from 6000-7999). Initial paired A64 evidence {\"n\":64,\"edge_delta\":0.7624264790062519,\"standard_error\":1.0391980376922347,\"retail_delta\":0.8519752505062517,\"arb_delta\":-0.08954877149999993}; disjoint B128 evidence {\"n\":128,\"edge_delta\":0.6432523016843763,\"standard_error\":0.4568447480609462,\"retail_delta\":0.39359688495234424,\"arb_delta\":0.24965541672812508}. Code frozen at 2026-11-06T02:55:15.280873+00:00 before any unseen performance evaluation. The full base 4000-run batch finished after freeze, so these expanded paired figures are reported for attribution, not used to select a different file: A470 {\"n\":470,\"edge_delta\":0.5506858928846821,\"standard_error\":0.31033825465268045,\"retail_delta\":0.4427389494704252,\"arb_delta\":0.10794694341531923}; B523 {\"n\":523,\"edge_delta\":0.3117344098814534,\"standard_error\":0.14525230093702146,\"retail_delta\":0.15073163901548753,\"arb_delta\":0.16100277086653939}. Among the expanded constant-only finalists, W=100 alone had pooled spread-3 gain 0.10089807153917428 (paired SE 0.04759751497683854); W=100 with g1=2 gained 0.09452643878056402; g1=2 alone lost 0.15099932589859; ydf1=0.75 lost 0.06125695622386668. The selected rule gained 0.4248332991176241 (SE 0.1655696794530299), so its larger local gain requires the guarded rule in addition to parameters. All selection used only spread-3 seeds in 4000-7999. The candidate 600-run isolation mean on 1000-1599 was 108.86424790539084 and was not used for selection. Exact dictionary equality on every non-3 per-run result holds for 453 scorer-check runs, 3007 full-training runs and 2983 unseen runs. Frozen full-file training and unseen scores are each 4000 successful simulations. The final training score exactly reproduces the compact tuning results on all 993 spread-3 seeds. Simulator commit b244530ee2a6247b5f930830eeca9dd950da0e7e; no sandbox or external Python dependencies. On unseen spread-3 runs the retail-edge change is 0.42692665186971457 and the signed arb-edge change is 0.31901547610196673 (positive means less arbitrage loss).", "blocked": null, "python_version": "3.12.3", "base_mean_edge": 109.27254289017199, "base_holdout_mean_edge": 98.28063388702982, "score": {"mean_edge": 98.84950498965385, "retail_edge": 124.4013873695152, "arb_edge": -25.551882379876773, "simulations": 4000, "seed_start": 4000, "failures": 0}, "holdout": {"mean_edge": 98.47028967306635, "retail_edge": 126.1276183775221, "arb_edge": -27.657328704453427, "simulations": 4000, "seed_start": 50000, "failures": 0}, "by_spread": [{"spread": 1, "runs": 1016, "base": 35.099921878704336, "yours": 35.099921878704336, "diff": 0.0, "standard_error": 0.0}, {"spread": 2, "runs": 998, "base": 83.51205221971222, "yours": 83.51205221971222, "diff": 0.0, "standard_error": 0.0}, {"spread": 3, "runs": 1017, "base": 122.97345583671554, "yours": 123.71939796468614, "diff": 0.7459421279705998, "standard_error": 0.2441846966634406}, {"spread": 4, "runs": 969, "base": 153.82041508580312, "yours": 153.82041508580312, "diff": 0.0, "standard_error": 0.0}], "constants": {"P.flow_prior": 200, "P.flow_level": 0.6, "P.flow_strength": 1.0, "P.flow_safety": 2.0, "P.flow_exposure_min": 5.0}, "code": "\"\"\"Stale-quote defence with tick probes, a sub-tick belief and cheap YES stock.\n\nEvery step the arbitrageur removes any order on the wrong side of p, so tiny\ntwo-sided probes around the estimate locate p to a tick; a grid filter narrows\nthat further.  Quotes sit one tick inside the competitor and are sized by the\nmarginal rule: one more share is worth quoting while the chance a retail order\nreaches it, times its edge, exceeds the expected arbitrage loss.  Near p=0 a\nretail buy pays almost its whole notional as edge, so YES is held to cover low\nasks.  That YES is bought when it is cheap: a large bid rests at tick 1 while p\nis above it, so the arbitrageur fills it on the crossing for about 0.1 tick a\nshare instead of nearly a full tick once p is near zero, and smaller bids sit on\nwhichever tick p is within 0.15 of.  Below tick 1 the estimate of p decays with\nthe time spent there, since no probe can see it.\n\"\"\"\nimport math\nfrom orderbook_pm_challenge.strategy import BaseStrategy\nfrom orderbook_pm_challenge.types import CancelOrder, PlaceOrder, Side\n\nP = dict(lam_r=0.25, m=5.0, sig_n=1.2, lam_j=0.0019, sig_j=0.35, sig=0.02,\n         qmax=3000.0, rmin=2, kA=0.7, kL=0.15, pL=0.05,\n         ammo=1.0, ydem=0.4, W=200.0, fy=0.6, ammo_q=60.0, ammo_pmax=0.05, ammo_maxpay=0.02,\n         fb=0.9, fu=0.7, xu=0.1, sticky=1.0, min_ahead=2.0, keep_hi=1.5, keep_lo=0.7, Hu=300.0, bins=8.0, filt=1.0, uni=0.01, jumpinfo=1.0, dmin=0.0, kLb=0.08, kLf=0.08, pinf=1.0, pre=0.0, H1=100.0,\n         ydf=0.6, Wf=2000.0, g_hi=0.15, g_lo=0.15, qf=400.0, pmaxf=0.05, pre_gap=1.0,\n         ydf1=0.6, g1=5.0, f1=0.6, a1=100.0, nb1=0.0, gs=1.0, p1t=1.0, m1=1.0, zd=1.0, pfl=0.0005)\nP.update({'W': 50, 'ammo_pmax': 0.02, 'fy': 0.7, 'fu': 0.25, 'Hu': 500})\nC = {'W': 50, 'ammo_pmax': 0.02, 'fy': 0.7, 'reserve': 200, 'scar': 0.0025, 'fu': 0.25, 'Hu': 500}\nSQ2 = math.sqrt(2.0)\nSQ2PI = math.sqrt(2.0 * math.pi)\ndef cdf(x): return 0.5 * (1.0 + math.erf(x / SQ2))\ndef pdf(x): return math.exp(-0.5 * x * x) / SQ2PI\ndef inv(p):\n    p = min(max(p, 1e-9), 1 - 1e-9)\n    t = math.sqrt(-2.0 * math.log(min(p, 1 - p)))\n    x = t - (2.515517 + 0.802853 * t + 0.010328 * t * t) / (1 + 1.432788 * t + 0.189269 * t * t + 0.001308 * t ** 3)\n    x = -x if p < 0.5 else x\n    for _ in range(2):\n        d = pdf(x)\n        if d < 1e-12:\n            break\n        x -= (cdf(x) - p) / d\n    return x\ndef lpm(k):\n    return pdf(k) + k * cdf(k)\ndef fl(q):\n    return math.floor(q * 100 + 1e-9) / 100\n\nNODES = [(-2.2, .06), (-1.3, .17), (-0.6, .27), (0.6, .27), (1.3, .17), (2.2, .06)]\nPROBE = 0.01\n\n\nclass Strategy(BaseStrategy):\n    def __init__(self):\n        self.n = 0\n        self.ahead = set()     # main orders placed strictly ahead of any competitor order at their tick\n        self.res = {}          # order id -> uncovered quantity at placement\n        self.bc = None         # belief: sub-tick grid centres (ticks)\n        self.bw = None         # belief: weights\n        self.st = 0.5          # last one-step sd in ticks\n        self.pcb = self.pca = None\n        self.pb = set()\n        self.pa = set()\n        self.tb = 0\n        self.s = None          # competitor spread parameter\n        self.flow_notional = 0.0\n        self.flow_exposure = 0\n        self.last_ask_tick = None\n        self.last_quote_exposed = False\n        self.last_flow_ca = None\n        self.last_flow_cap = 0.0\n        self.last_flow_correction = 1.0\n        self.params = P.copy()\n        self.controls = C.copy()\n\n    def _oid(self, tag):\n        self.n += 1\n        return tag + str(self.n)\n\n    def on_step(self, state):\n        H = max(1, state.steps_remaining)\n        cb = state.competitor_best_bid_ticks or 0\n        ca = state.competitor_best_ask_ticks or 100\n        if self.s is None:\n            self.s = max(1, (ca - cb + 1) // 2)\n            if self.s == 3:\n                self.params.update({'flow_prior': 200, 'flow_level': 0.6, 'flow_strength': 1.0, 'flow_safety': 2.0, 'flow_exposure_min': 5.0})\n                self.controls.update({})\n        P, C = self.params, self.controls\n        if self.s == 3 and self.last_quote_exposed and ca <= self.last_flow_ca + 1:\n            self.flow_exposure += 1\n            self.flow_notional += min(self.last_flow_cap, state.sell_filled_quantity * self.last_ask_tick / 100.0) * self.last_flow_correction\n        lo, hi = cb, ca\n        for o in state.own_orders:\n            if o.side is Side.BUY:\n                lo = max(lo, o.price_ticks)\n            else:\n                hi = min(hi, o.price_ticks)\n        if P['pinf'] > 0:\n            sb = {o.price_ticks for o in state.own_orders if o.side is Side.BUY and o.remaining_quantity <= PROBE + 1e-9}\n            sa = {o.price_ticks for o in state.own_orders if o.side is Side.SELL and o.remaining_quantity <= PROBE + 1e-9}\n            ea = self.pa - sa\n            eb = self.pb - sb\n            if sa and ea:\n                lo = max(lo, min(max(ea), hi))\n            if eb and (sb or min(eb) <= P['p1t']):\n                hi = min(hi, max(min(eb), lo))\n        if P['jumpinfo'] > 0 and self.pcb is not None:\n            if ca > self.pca + 1:\n                lo = max(lo, ca - 1)\n            if cb < self.pcb - 1:\n                hi = min(hi, cb + 1)\n        self.pcb, self.pca = cb, ca\n        if lo > hi:\n            lo, hi = hi, lo\n        # sub-tick belief over p_(t-1): predict with one-step noise, truncate to [lo, hi]\n        wid = max(hi - lo, 1e-6)\n        nb = max(2, min(48, int(round(wid * P['bins']))))\n        cs = [lo + (i + 0.5) * wid / nb for i in range(nb)]\n        if self.bc is None or P['filt'] <= 0:\n            ws = [1.0 / nb] * nb\n        else:\n            sg = max(self.st, 0.6 * wid / nb)\n            k = -0.5 / (sg * sg)\n            ws = []\n            uni = P['uni'] * sg\n            for c in cs:\n                t = uni\n                for ci, wi in zip(self.bc, self.bw):\n                    d = c - ci\n                    d2 = d * d * k\n                    if d2 > -12.5:\n                        t += wi * math.exp(d2)\n                ws.append(t)\n            tot = sum(ws)\n            ws = [w / tot for w in ws]\n        self.bc, self.bw = cs, ws\n        mean_t = sum(c * w for c, w in zip(cs, ws))\n        var_t = max(sum(c * c * w for c, w in zip(cs, ws)) - mean_t * mean_t, 0.0)\n        phat = min(max(mean_t / 100.0, 0.002), 0.998)\n        var = P['sig'] ** 2 + P['lam_j'] * P['sig_j'] ** 2\n        sd = math.sqrt(H * var)\n        self.tb = self.tb + 1 if hi <= 1 else 0\n        if self.tb > 0 and P['zd'] > 0:\n            # below the last tick there is no probe: the score keeps walking away from it\n            phat = min(phat, max(P['pfl'], cdf(inv(0.01) - P['zd'] * 0.02 * math.sqrt(self.tb) / sd)))\n        z = inv(phat)\n        Z = z * sd\n        sp = pdf(z) / sd * P['sig']\n        self.st = sp * 100.0\n        s = math.sqrt(sp * sp + var_t / 1e4 + 1e-8)\n        sd1 = math.sqrt(max(1.0, H - 1.0) * var)\n        jp = [(cdf((Z + n * P['sig_j']) / sd1), w) for n, w in NODES]\n        lj = P['lam_j']\n\n        def AB(x):\n            k = (x - phat) / s\n            a = s * lpm(k)\n            b = a - (x - phat)\n            ja = sum(w * max(0.0, x - p) for p, w in jp)\n            jb = sum(w * max(0.0, p - x) for p, w in jp)\n            return (1 - lj) * a + lj * ja, (1 - lj) * b + lj * jb\n\n        if H == 1:\n            def AB(x):\n                return (1 - phat) * x, phat * (1 - x)\n        rho = P['lam_r'] * 0.5\n        mu = math.log(P['m']) - 0.5 * P['sig_n'] ** 2\n        kA = P['kL'] if phat < P['pL'] else P['kA']\n\n        def qsize(loss, gain, px):\n            loss *= kA\n            if gain <= 0:\n                return 0.0\n            tail = loss / (rho * gain)\n            if tail >= 1.0:\n                return 0.0\n            return min(P['qmax'], math.exp(mu + P['sig_n'] * inv(1 - max(tail, 1e-6))) / px)\n\n        ptk = phat * 100\n        def qbid(t):\n            if not 1 <= t <= 99:\n                return 0.0\n            a, b = AB(t / 100.0)\n            if phat * 100 - t < P['dmin']:\n                return 0.0\n            if P['nb1'] > 0 and self.s == 1 and t == 1 and ptk < 1.0:\n                return 0.0\n            if phat < P['pL']:\n                ytg = P['ydem'] * min(H, P['W']) / max(ca - 1, ptk + 1) * 100.0\n                a *= (P['kLb'] if state.yes_inventory < ytg else P['kLf']) / P['kL']\n            return qsize(a, b, max(phat, 0.05))\n\n        def qask(t):\n            if not 1 <= t <= 99:\n                return 0.0\n            a, b = AB(t / 100.0)\n            if t - phat * 100 < P['dmin']:\n                return 0.0\n            if phat < C.get('scar_p', .1):\n                a = max(0.0, a - C.get('scar', 0.0) * (1 - min(1.0, state.yes_inventory / C.get('stock', 3000.0))))\n            return min(C.get('askcap', P['qmax']), qsize(b, a, t / 100.0))\n\n        bids = [o for o in state.own_orders if o.side is Side.BUY and o.remaining_quantity > PROBE + 1e-9]\n        asks = [o for o in state.own_orders if o.side is Side.SELL and o.remaining_quantity > PROBE + 1e-9]\n        sticky = P['sticky'] > 0\n        def top(orders, comp, step):\n            if sticky and sum(o.remaining_quantity for o in orders if o.price_ticks == comp and o.order_id in self.ahead) >= P['min_ahead']:\n                return comp\n            return comp + step\n        bid_t = top(bids, cb, 1)\n        ask_t = top(asks, ca, -1)\n        qb = min(C.get('bidcap', 3000.0), qbid(bid_t))\n        qa = qask(ask_t)\n\n        Y = state.yes_inventory\n        if ask_t == 1 and H > P['H1'] and P['pre'] > 0:\n            qa = qa if Y >= P['a1'] > 0 else 0.0          # let the competitor's 2-tick ask erode instead of fronting it for nothing\n        # ammunition: hold YES so that low asks are covered\n        ptick = phat * 100\n        amt = 0\n        qam = 0.0\n        if P['ammo'] > 0 and ask_t >= 2 and phat < max(P['ammo_pmax'], P['pmaxf']):\n            wealth = state.cash + Y * phat\n            x = max(ask_t, ptick + 1) / 100.0\n            capw = P['fy'] * wealth / max(phat, 0.005)\n            target = min(P['ydem'] * min(H, P['W']) / x, capw)\n            full = min(P['ydf'] * min(H, P['Wf']) / x, capw) if phat < P['pmaxf'] else 0.0\n            t = max(1, min(99, int(math.ceil(ptick + 1e-9))))\n            g = t - ptick\n            if Y < full and g <= P['g_hi'] and bid_t <= t < ask_t:\n                amt, qam = t, min(P['qf'], full - Y)     # a tick p has just crossed: nearly free\n            elif Y < target and phat < P['ammo_pmax'] and bid_t <= t < ask_t and t / 100.0 - phat < P['ammo_maxpay']:\n                amt, qam = t, min(P['ammo_q'], target - Y)\n            elif Y < full and t >= 2 and 1.0 - g <= P['g_lo']:\n                amt, qam = t - 1, min(P['qf'], full - Y)  # rest just under p: filled only on the crossing, or by retail\n\n        if P['pre'] > 0 and ca == 2 and phat < 0.01 and H > P['H1'] and Y < P['pre'] and not qam and 1.0 - ptick < P['pre_gap']:\n            amt, qam = 1, min(P['ammo_q'], P['pre'] - Y)\n        q1 = 0.0\n        if P['ydf1'] > 0 and P['m1'] < ptick < P['g1'] + 1.0 and amt != 1:\n            stock_rate = P['ydf1']\n            if self.s == 3:\n                flow = (self.flow_notional + P['flow_prior'] * P['flow_level']) / (P['flow_prior'] + self.flow_exposure)\n                scale = max(0.5, min(2.0, flow / P['flow_level']))\n                stock_rate *= 1.0 + P['flow_strength'] * (scale - 1.0)\n            q1 = max(0.0, stock_rate * min(H, P['Wf']) / (self.s / 100.0) - Y)\n        # order management\n        actions = []\n        free = state.free_cash - 2.0\n        keep_ask = 0.0\n        new_b = []\n        new_a = []\n        def cancel(o):\n            nonlocal free\n            actions.append(CancelOrder(o.order_id))\n            x = o.price_ticks / 100.0\n            if o.side is Side.BUY:\n                free += x * o.remaining_quantity\n            else:\n                free += (1 - x) * min(self.res.get(o.order_id, 0.0), o.remaining_quantity)\n            self.ahead.discard(o.order_id)\n            self.res.pop(o.order_id, None)\n        for o in state.own_orders:\n            if o.remaining_quantity <= PROBE + 1e-9:\n                cancel(o)\n        kept_ids = set()\n        def manage(orders, t, q, comp):\n            kept = 0.0\n            for o in orders:\n                if not (C.get('recover', 0) and o.side is Side.SELL and t < comp and self.res.get(o.order_id, 0.0) > 1 and state.yes_inventory > C.get('recover_yes', 1) and state.free_cash < C.get('recover_cash', 200)) and o.price_ticks == t and q > 0 and kept + o.remaining_quantity <= max(q * P['keep_hi'], 1.0):\n                    kept += o.remaining_quantity\n                    kept_ids.add(o.order_id)\n                else:\n                    cancel(o)\n            return kept\n        kb = manage(bids, bid_t, qb, cb)\n        ka = manage(asks, ask_t, qa, ca)\n        add_b = (qb - kb) if (kb < qb * P['keep_lo'] and bid_t != cb) else 0.0\n        add_a = (qa - ka) if (ka < qa * P['keep_lo'] and ask_t != ca) else 0.0\n\n        budget = P['fb'] * max(free, 0.0)\n        cost = add_b * bid_t / 100.0 + qam * amt / 100.0\n        if cost > budget:\n            f = budget / cost\n            add_b *= f\n            qam *= f\n            cost = budget\n        out = []\n        q1 = min(q1, P['f1'] * max(budget - cost, 0.0) * 100.0)\n        if q1 >= 0.01:\n            out.append(PlaceOrder(side=Side.BUY, price_ticks=1, quantity=fl(q1)))\n            free -= fl(q1) / 100.0 + 1e-6\n        if amt and qam >= 0.01:\n            q = fl(qam)\n            out.append(PlaceOrder(side=Side.BUY, price_ticks=amt, quantity=q))\n            free -= q * amt / 100.0 + 1e-6\n        if bid_t >= 1 and add_b >= 0.01:\n            q = fl(add_b)\n            oid = self._oid('b')\n            out.append(PlaceOrder(side=Side.BUY, price_ticks=bid_t, quantity=q, client_order_id=oid))\n            free -= q * bid_t / 100.0 + 1e-6\n            if bid_t > cb:\n                self.ahead.add(oid)\n        if ask_t <= 99 and add_a >= 0.01:\n            x = ask_t / 100.0\n            covk = sum(o.remaining_quantity - min(self.res.get(o.order_id, 0.0), o.remaining_quantity)\n                       for o in asks if o.order_id in kept_ids)\n            cov = max(0.0, Y - covk - 0.1)\n            unc = max(0.0, add_a - cov)\n            if unc > 0:\n                ub = max(0.0, free - (1 - P['fu']) * max(state.cash, 0.0)) if x >= P['xu'] else 0.0\n                if H < P['Hu'] and phat < 0.05:\n                    ub = max(0.0, free * (1 - H / P['Hu']))\n                ub = min(ub, max(0.0, free - C.get('reserve', 0.0) * min(1.0, H / C.get('release', 50.0))))\n                unc = min(unc, ub / (1 - x))\n            q = fl(min(add_a, cov + unc))\n            if q >= 0.01:\n                oid = self._oid('a')\n                out.append(PlaceOrder(side=Side.SELL, price_ticks=ask_t, quantity=q, client_order_id=oid))\n                r = max(0.0, q - cov)\n                self.res[oid] = r\n                free -= r * (1 - x) + 1e-6\n                if ask_t < ca:\n                    self.ahead.add(oid)\n\n        # probes: tiny orders that the arbitrageur removes when p crosses them\n        f = int(math.floor(ptick + 1e-9))\n        r = max(int(P['rmin']), int(math.ceil(2.0 * s * 100)))\n        self.pb = set()\n        self.pa = set()\n        if free > 1.0:\n            for t in range(f, f + r + 1):\n                if cb < t < ca and 1 <= t <= 99:\n                    out.append(PlaceOrder(side=Side.BUY, price_ticks=t, quantity=PROBE))\n                    self.pb.add(t)\n            for t in range(f + 1 - r, f + 2):\n                if cb < t < ca and 1 <= t <= 99:\n                    out.append(PlaceOrder(side=Side.SELL, price_ticks=t, quantity=PROBE))\n                    self.pa.add(t)\n        if self.s == 3:\n            self.last_ask_tick = ask_t\n            self.last_flow_ca = ca\n            exposed_qty = ka + sum(o.quantity for o in out if o.side is Side.SELL and o.price_ticks == ask_t and o.quantity > PROBE)\n            self.last_flow_cap = exposed_qty * ask_t / 100.0\n            self.last_quote_exposed = ask_t / 100.0 > phat + max(0.005, P['flow_safety'] * self.st / 100.0) and self.last_flow_cap >= P['flow_exposure_min']\n            if self.last_quote_exposed:\n                logcap = math.log(self.last_flow_cap)\n                mu_flow = math.log(P['m']) - 0.5 * P['sig_n'] ** 2\n                clipped = P['m'] * cdf((logcap - mu_flow - P['sig_n'] ** 2) / P['sig_n']) + self.last_flow_cap * (1.0 - cdf((logcap - mu_flow) / P['sig_n']))\n                self.last_flow_correction = min(3.0, P['m'] / max(clipped, 0.01))\n        return actions + out\n", "code_sha256": "95401cdb118b2fcbe2f3b98e2b3422a4fa814feaa885241eda201832097b4510", "tried": ["Scorer check: base mean 109.27254289017199 on seeds 1000-1599, 600 runs, 0 failures; exactly matches the supplied author measurement. A screening uses spread-3 seeds from 4000-5999; B confirmation uses disjoint spread-3 seeds from 6000-7999. All reported arb values are signed edge (negative is loss).", "Tuning audit: 14373 unique strategy/seed pairs; all cached trials use spread 3 and seeds 4000-7999; zero failed simulations; repeated cached results agree exactly. These are training-only observations.", "adapt1200_10 observed-fill stock target; a64(4003-4272): edge=149.60014538657188 retail=173.97488449980312 arb=-24.374739113082814 delta=0.5146850845656243 dRetail=0.690957155900001 dArb=-0.17627207133281267", "adapt1200_5 observed-fill stock target; a64(4003-4272): edge=149.56146411485 retail=173.7731731050672 arb=-24.211708990073436 delta=0.47600381284375043 dRetail=0.48924576116406415 dArb=-0.01324194832343728", "adapt200_10 observed-fill stock target; a64(4003-4272): edge=149.37692127048126 retail=174.14211830722812 arb=-24.7651970366 delta=0.29146096847499997 dRetail=0.8581909633250016 dArb=-0.5667299948500001", "adapt200_5 observed-fill stock target; a64(4003-4272): edge=149.64128361578437 retail=173.97934045615938 arb=-24.338056840223437 delta=0.5558233137781223 dRetail=0.6954131122562504 dArb=-0.13958979847343705; b128(6000-6463): edge=114.40939571639531 retail=136.5251697092367 arb=-22.11577399299531 delta=0.4513818944156267 dRetail=0.3130467446304699 dArb=0.13833514978281267", "adapt600_10 observed-fill stock target; a64(4003-4272): edge=149.64770288321563 retail=174.13849342294844 arb=-24.490790539589064 delta=0.5622425812093751 dRetail=0.854566079045314 dArb=-0.2923234978390624; b128(6000-6463): edge=114.48430621443437 retail=136.5792631539375 arb=-22.094956939654686 delta=0.5262923924546878 dRetail=0.36714018933125137 dArb=0.15915220312343764", "adapt600_5 observed-fill stock target; a64(4003-4272): edge=149.5438919749203 retail=173.78125937120626 arb=-24.237367396139064 delta=0.45843167291406095 dRetail=0.4973320273031261 dArb=-0.03890035438906228", "adapt7_1200_10 observed-fill stock target; a64(4003-4272): edge=149.59772661518906 retail=173.66390733316095 arb=-24.066180717820313 delta=0.5122663131828112 dRetail=0.3799799892578126 dArb=0.13228632392968767", "adapt7_1200_5 observed-fill stock target; a64(4003-4272): edge=149.36767718739532 retail=173.47146579025312 arb=-24.1037886027125 delta=0.2822168853890615 dRetail=0.1875384463500014 dArb=0.09467843903750059", "adapt7_200_10 observed-fill stock target; a64(4003-4272): edge=149.73564670833593 retail=173.69033147855782 arb=-23.954684770075 delta=0.6501864063296868 dRetail=0.40640413465468894 dArb=0.24378227167500005", "adapt7_200_5 observed-fill stock target; a64(4003-4272): edge=149.58831043865467 retail=173.6624321825172 arb=-24.0741217437125 delta=0.5028501366484358 dRetail=0.37850483861406303 dArb=0.12434529803750038", "adapt7_600_10 observed-fill stock target; a64(4003-4272): edge=149.65277506887813 retail=173.6547452988828 arb=-24.001970229854688 delta=0.5673147668718767 dRetail=0.37081795497968795 dArb=0.1964968118953128", "adapt7_600_5 observed-fill stock target; a64(4003-4272): edge=149.47035409703594 retail=173.57236372134062 arb=-24.102009624151563 delta=0.38489379502968724 dRetail=0.2884363774375003 dArb=0.09645741759843773", "ask10k {\"P.qmax\":10000,\"C.askcap\":10000}; a64(4003-4272): edge=149.62733290986407 retail=173.8834643585 arb=-24.256131448485938 delta=0.5418726078578118 dRetail=0.5995370145968746 dArb=-0.05766440673593726", "ask6k {\"P.qmax\":6000,\"C.askcap\":6000}; a64(4003-4272): edge=149.62733136615313 retail=173.8834643585 arb=-24.256132992196875 delta=0.5418710641468749 dRetail=0.5995370145968746 dArb=-0.057665950446875; b128(6000-6463): edge=113.56735549635782 retail=136.51822631331407 arb=-22.95087081711328 delta=-0.3906583256218745 dRetail=0.3061033487078135 dArb=-0.6967616743351561", "askcash {\"P.fu\":0.5,\"P.Hu\":800,\"C.reserve\":100}; a64(4003-4272): edge=149.01386563127187 retail=173.41123769530938 arb=-24.39737206388594 delta=-0.07159467073437653 dRetail=0.1273103514062499 dArb=-0.19890502213593764", "askcashall {\"P.fu\":0.75,\"P.Hu\":1000,\"C.reserve\":0}; a64(4003-4272): edge=149.0020719433703 retail=173.98241921309375 arb=-24.9803472695625 delta=-0.08338835863593974 dRetail=0.6984918691906241 dArb=-0.7818802278124996", "askrisk07 {\"P.ask_risk\":0.7}; a64(4003-4272): edge=148.60399981998282 retail=175.19417617343282 arb=-26.590176353351563 delta=-0.4814604820234395 dRetail=1.9102488295296847 dArb=-2.391709311601562", "askrisk15 {\"P.ask_risk\":1.5}; a64(4003-4272): edge=150.17146012295157 retail=172.4477109627375 arb=-22.276250839679687 delta=1.08599982094531 dRetail=-0.8362163811656278 dArb=1.9222162020703126; b128(6000-6463): edge=113.39926367484688 retail=133.51837198108595 arb=-20.11910830636328 delta=-0.5587501471328111 dRetail=-2.693750983520313 dArb=2.135000836414844", "askrisk2 {\"P.ask_risk\":2.0}; a64(4003-4272): edge=148.6238396331 retail=169.7657852518969 arb=-21.141945618725 delta=-0.4616206689062514 dRetail=-3.5181420920062503 dArb=3.0565214230250004", "bidrisk07 {\"P.bid_risk\":0.7}; a64(4003-4272): edge=149.52245557381406 retail=175.97819276583283 arb=-26.45573719186875 delta=0.43699527180781184 dRetail=2.694265421929691 dArb=-2.25727015011875; b128(6000-6463): edge=112.92905182499297 retail=138.3264878803414 arb=-25.397436055502343 delta=-1.0289619969867185 dRetail=2.1143649157351563 dArb=-3.1433269127242185", "bidrisk15 {\"P.bid_risk\":1.5}; a64(4003-4272): edge=146.92316025370155 retail=169.30515740864843 arb=-22.38199715485 delta=-2.1623000483046897 dRetail=-3.978769935254688 dArb=1.8164698869", "cashopen {\"P.Hu\":2000,\"P.xu\":0.03,\"P.fu\":0.5,\"C.reserve\":100}; a64(4003-4272): edge=146.46737109931405 retail=172.66902229637188 arb=-26.20165119690156 delta=-2.6180892026921874 dRetail=-0.6149050475312525 dArb=-2.0031841551515623", "cashreserve0 {\"C.reserve\":0}; a64(4003-4272): edge=148.6518603061125 retail=173.26635386370313 arb=-24.614493557440625 delta=-0.4335999958937502 dRetail=-0.0175734802000016 dArb=-0.4160265156906249", "cashreserve100 {\"C.reserve\":100}; a64(4003-4272): edge=149.24235697857344 retail=173.41533559039843 arb=-24.172978611676562 delta=0.1568966765671873 dRetail=0.13140824649531302 dArb=0.025488430073437485", "cashsafe {\"P.Hu\":1200,\"P.xu\":0.05,\"P.fu\":0.4,\"C.reserve\":100}; a64(4003-4272): edge=148.13314934136562 retail=172.8357581084625 arb=-24.70260876694375 delta=-0.9523109606406267 dRetail=-0.4481692354406275 dArb=-0.5041417251937499", "combo100g2 {\"P.W\":100,\"P.g1\":2}; a64(4003-4272): edge=150.15170614529376 retail=174.01897215541564 arb=-23.86726600997656 delta=1.0662458432875 dRetail=0.735044811512501 dArb=0.33120103177343796; afull470(4003-5999): edge=136.71185343849382 retail=161.78226961368702 arb=-25.07041617526532 delta=0.06854823097531944 dRetail=0.3602155969255314 dArb=-0.2916673659463829; b128(6000-6463): edge=114.29558885482031 retail=136.6112406563742 arb=-22.315651801708594 delta=0.3375750328406245 dRetail=0.39911769176796874 dArb=-0.061542658930468716; bfull523(6000-7997): edge=114.49147709423958 retail=137.77226443002715 arb=-23.280787335859273 delta=0.11787205573747599 dRetail=0.0570673941007645 dArb=0.060804661637667394", "combo100g2low {\"P.W\":100,\"P.g1\":2,\"P.kL\":0.08}; a64(4003-4272): edge=150.92072550670937 retail=175.34397769017656 arb=-24.423252183309376 delta=1.8352652047031248 dRetail=2.0600503462734396 dArb=-0.22478514155937485; b128(6000-6463): edge=114.12562594704922 retail=136.9988962566789 arb=-22.87327030978672 delta=0.16761212506953233 dRetail=0.7867732920726571 dArb=-0.6191611670085938", "combo100g2stock {\"P.W\":100,\"P.g1\":2,\"P.ydf1\":0.75}; a128(4003-4591): edge=135.91695381101016 retail=164.9627240985625 arb=-29.045770287503125 delta=0.25900520934843785 dRetail=0.6799355555695323 dArb=-0.42093034621171854; b128(6000-6463): edge=114.41156093991329 retail=136.7863205476492 arb=-22.374759607894532 delta=0.45354711793359415 dRetail=0.5741975830429696 dArb=-0.1206504651164062", "combo100g3 {\"P.W\":100,\"P.g1\":3}; a64(4003-4272): edge=149.96619566710157 retail=174.02539871790313 arb=-24.059203050649998 delta=0.8807353650953125 dRetail=0.7414713740000005 dArb=0.13926399110000034; b128(6000-6463): edge=114.2188413200547 retail=136.61044118802735 arb=-22.391599868126562 delta=0.2608274980749994 dRetail=0.3983182234210939 dArb=-0.13749072534843745", "combo200g2 {\"P.W\":200,\"P.g1\":2}; a64(4003-4272): edge=149.99855390777188 retail=174.06284927288283 arb=-24.064295364975 delta=0.9130936057656236 dRetail=0.7789219289796896 dArb=0.13417167677500028; b128(6000-6463): edge=114.25824418120078 retail=136.64343347023672 arb=-22.385189289188283 delta=0.30023035922109353 dRetail=0.43131050563046924 dArb=-0.13108014641015614", "cover03 {\"P.ammo_pmax\":0.03}; a64(4003-4272): edge=149.09884232361875 retail=173.30661260289062 arb=-24.207770279123437 delta=0.013382021612499795 dRetail=0.022685258987499957 dArb=-0.009303237373437467", "cover05 {\"P.ammo_pmax\":0.05}; a64(4003-4272): edge=148.96158917165155 retail=173.48781449799844 arb=-24.52622532619844 delta=-0.12387113035468672 dRetail=0.203887154095314 dArb=-0.32775828444843724", "cover100 {\"P.W\":100}; a64(4003-4272): edge=149.55794669532813 retail=174.0664457402047 arb=-24.50849904472969 delta=0.47248639332187437 dRetail=0.7825183963015636 dArb=-0.31003200297968736; afull470(4003-5999): edge=136.78868282624703 retail=161.81061881909383 arb=-25.021935992921275 delta=0.1453776187285109 dRetail=0.3885648023323399 dArb=-0.24318718360234037; b128(6000-6463): edge=114.21486129744687 retail=136.61044470426407 arb=-22.395583406970314 delta=0.256847475467187 dRetail=0.3983217396578126 dArb=-0.14147426419218745; bfull523(6000-7997): edge=114.43453105042562 retail=137.88884064089865 arb=-23.454309590545314 delta=0.060926011923518035 dRetail=0.17364360497227513 dArb=-0.11271759304837477", "cover100d6 {\"P.W\":100,\"P.ydem\":0.6}; a64(4003-4272): edge=149.5621190696422 retail=174.62121420969376 arb=-25.059095139900002 delta=0.47665876763593484 dRetail=1.3372868657906265 dArb=-0.8606280981500001", "cover200 {\"P.W\":200}; a64(4003-4272): edge=149.4826509186453 retail=174.11064792294687 arb=-24.62799700416094 delta=0.39719061663906063 dRetail=0.826720579043752 dArb=-0.42952996241093744; b128(6000-6463): edge=114.17751662382734 retail=136.64263751812655 arb=-22.46512089445 delta=0.21950280184765603 dRetail=0.4305145535203131 dArb=-0.2110117516718749", "cover200p03 {\"P.W\":200,\"P.ammo_pmax\":0.03}; a64(4003-4272): edge=149.19924006065625 retail=174.0410407771422 arb=-24.841800716340625 delta=0.11377975864999829 dRetail=0.7571134332390639 dArb=-0.6433336745906251", "cover200p05 {\"P.W\":200,\"P.ammo_pmax\":0.05}; a64(4003-4272): edge=147.87111143559062 retail=174.71462611037344 arb=-26.843514674645313 delta=-1.2143488664156248 dRetail=1.430698766470313 dArb=-2.6450476328953125", "cover200q120 {\"P.W\":200,\"P.ammo_q\":120}; a64(4003-4272): edge=149.62237219045625 retail=174.34652412472187 arb=-24.724151934120314 delta=0.5369118884499995 dRetail=1.0625967808187515 dArb=-0.5256848923703126", "cover25 {\"P.W\":25}; a64(4003-4272): edge=148.26193788207655 retail=172.0269974385203 arb=-23.7650595563 delta=-0.8235224199296882 dRetail=-1.2569299053828127 dArb=0.4334074854500002", "cover500 {\"P.W\":500}; a64(4003-4272): edge=149.2629913343422 retail=174.1191347081375 arb=-24.85614337365469 delta=0.1775310323359376 dRetail=0.8352073642343769 dArb=-0.6576763319046872", "coverq120 {\"P.ammo_q\":120}; a64(4003-4272): edge=149.14490120633437 retail=173.3799481342578 arb=-24.235046927785937 delta=0.05944090432812321 dRetail=0.09602079035468858 dArb=-0.03657988603593723", "coverq400 {\"P.ammo_q\":400}; a64(4003-4272): edge=149.15929057872657 retail=173.41796195142967 arb=-24.258671372560936 delta=0.07383027672031184 dRetail=0.13403460752656216 dArb=-0.06020433081093757", "crossstock {\"P.qf\":800,\"P.g_hi\":0.3,\"P.g_lo\":0.3}; a64(4003-4272): edge=145.4536209101344 retail=174.05407661057814 arb=-28.600455700290624 delta=-3.6318393918718743 dRetail=0.7701492666749998 dArb=-4.401988658540625", "endstock {\"P.Wf\":500}; a64(4003-4272): edge=144.67178484887344 retail=171.54070347389688 arb=-26.868918624873437 delta=-4.413675453132812 dRetail=-1.7432238700062488 dArb=-2.670451583123437", "fullstock03 {\"P.ydf\":0.3}; a64(4003-4272): edge=149.13224322741561 retail=173.37257236947812 arb=-24.240329141915623 delta=0.04678292540937562 dRetail=0.08864502557499998 dArb=-0.041862100165624846", "fullstock12 {\"P.ydf\":1.2}; a64(4003-4272): edge=148.9540140873375 retail=173.48249679865 arb=-24.528482711170312 delta=-0.13144621466875095 dRetail=0.19856945474687482 dArb=-0.33001566942031263", "hu1200 {\"P.Hu\":1200}; a64(4003-4272): edge=149.183708685375 retail=173.28445840509843 arb=-24.100749719575 delta=0.0982483833687493 dRetail=0.0005310611953146527 dArb=0.09771732217499984", "hu2000 {\"P.Hu\":2000}; a64(4003-4272): edge=149.309101320675 retail=173.65104275730312 arb=-24.341941436479686 delta=0.22364101866874875 dRetail=0.36711541340000187 dArb=-0.14347439472968726; b128(6000-6463): edge=113.84635246948515 retail=136.1365402454586 arb=-22.290187776127343 delta=-0.11166135249453146 dRetail=-0.07558271914765702 dArb=-0.036078633349218805", "hu4000 {\"P.Hu\":4000}; a64(4003-4272): edge=149.32371481280313 retail=173.66565624943283 arb=-24.341941436479686 delta=0.23825451079687432 dRetail=0.38172890552968974 dArb=-0.14347439472968726", "insure1000 {\"P.insurance_stock\":1000}; a64(4003-4272): edge=149.10389498198595 retail=173.2681005158172 arb=-24.164205533689064 delta=0.018434679979685842 dRetail=-0.015826828085938383 dArb=0.03426150806093742", "insure300 {\"P.insurance_stock\":300}; a64(4003-4272): edge=149.12168265816874 retail=173.28067201764063 arb=-24.158989359329688 delta=0.03622235616249908 dRetail=-0.003255326262501357 dArb=0.039477682420312465", "insure3000 {\"P.insurance_stock\":3000}; a64(4003-4272): edge=149.18772935198282 retail=173.32866951460937 arb=-24.1409401624875 delta=0.10226904997656089 dRetail=0.044742170706249196 dArb=0.05752687926249994; b128(6000-6463): edge=114.37406522671563 retail=136.4802594876125 arb=-22.10619426105469 delta=0.4160514047359395 dRetail=0.2681365230062503 dArb=0.1479148817234374", "insure6000 {\"P.insurance_stock\":6000}; a64(4003-4272): edge=148.90491382018593 retail=173.26060259413907 arb=-24.35568877381094 delta=-0.18054648182031308 dRetail=-0.02332474976406307 dArb=-0.15722173206093765", "insurepower1 {\"P.insurance_power\":1}; a64(4003-4272): edge=148.85803920607032 retail=173.0572860050156 arb=-24.19924679880625 delta=-0.22742109593593887 dRetail=-0.22664133888750085 dArb=-0.0007797570562496567", "insurepower2 {\"P.insurance_power\":2}; a64(4003-4272): edge=149.1110102942828 retail=173.2616773970578 arb=-24.1506671026375 delta=0.02554999227656235 dRetail=-0.02224994684531112 dArb=0.047799939112500245", "insurepower3 {\"P.insurance_power\":3}; a64(4003-4272): edge=149.21237428451406 retail=173.3393751339203 arb=-24.127000849270313 delta=0.12691398250781166 dRetail=0.05544779001718725 dArb=0.07146619247968772", "longstock {\"P.Wf\":3000,\"P.ydf1\":1.0}; a64(4003-4272): edge=148.29016471888124 retail=174.1573126402469 arb=-25.86714792122031 delta=-0.7952955831249995 dRetail=0.8733852963437507 dArb=-1.6686808794703127", "lowbid04 {\"P.kLb\":0.04,\"P.kLf\":0.04}; a64(4003-4272): edge=148.47812787328436 retail=173.6561139181578 arb=-25.177986044721877 delta=-0.6073324287218744 dRetail=0.3721865742546877 dArb=-0.9795190029718747", "lowbid16 {\"P.kLb\":0.16,\"P.kLf\":0.16}; a64(4003-4272): edge=149.17940211549845 retail=172.80386959451874 arb=-23.624467478882814 delta=0.09394181349218617 dRetail=-0.4800577493843755 dArb=0.5739995628671877", "lowbidlb02 {\"P.kLb\":0.02}; a64(4003-4272): edge=149.09564743071562 retail=173.45896849235157 arb=-24.36332106148281 delta=0.010187128709374882 dRetail=0.17504114844843777 dArb=-0.1648540197328122", "lowbidlb2 {\"P.kLb\":0.2}; a64(4003-4272): edge=148.87193908561093 retail=172.9512568247828 arb=-24.079317739026564 delta=-0.2135212163953129 dRetail=-0.33267051912031276 dArb=0.11914930272343738", "lowbidlf3 {\"P.kLf\":0.3}; a64(4003-4272): edge=148.70371800435626 retail=172.20625698408125 arb=-23.502538979557812 delta=-0.38174229765000117 dRetail=-1.0776703598218726 dArb=0.6959280621921874", "lowbidlf5 {\"P.kLf\":0.5}; a64(4003-4272): edge=148.61609175241406 retail=171.89513675479844 arb=-23.2790450022375 delta=-0.4693685495921883 dRetail=-1.3887905891046892 dArb=0.9194220395125001", "lowrisk025 {\"P.kL\":0.25}; a64(4003-4272): edge=149.89157918371407 retail=173.51885256341876 arb=-23.627273379553124 delta=0.8061188817078115 dRetail=0.23492521951562417 dArb=0.5711936621968751; b128(6000-6463): edge=113.2627695188914 retail=135.3251980681625 arb=-22.06242854943125 delta=-0.6952443030882809 dRetail=-0.8869248964437517 dArb=0.1916805933468751", "lowrisk08 {\"P.kL\":0.08}; a64(4003-4272): edge=149.70648608841563 retail=174.55349268409532 arb=-24.847006595520313 delta=0.6210257864093741 dRetail=1.2695653401921874 dArb=-0.6485395537703125; b128(6000-6463): edge=113.7394164392914 retail=136.58516309610235 arb=-22.845746656967187 delta=-0.21859738268828047 dRetail=0.3730401314960946 dArb=-0.5916375141890624", "midask075 {\"P.ask_mid_risk\":0.75}; a64(4003-4272): edge=148.44117386951717 retail=174.08514207105938 arb=-25.643968201426564 delta=-0.6442864324890655 dRetail=0.801214727156248 dArb=-1.4455011596765628", "midask15 {\"P.ask_mid_risk\":1.5}; a64(4003-4272): edge=149.13189829946563 retail=171.68512262784688 arb=-22.553224328282813 delta=0.046437997459376726 dRetail=-1.5988047160562493 dArb=1.6452427134671876", "midask15low08 {\"P.ask_mid_risk\":1.5,\"P.kL\":0.08}; a64(4003-4272): edge=149.7907566501797 retail=172.90376656900781 arb=-23.11300991871719 delta=0.7052963481734388 dRetail=-0.38016077489531463 dArb=1.0854571230328125", "midask15low25 {\"P.ask_mid_risk\":1.5,\"P.kL\":0.25}; a64(4003-4272): edge=149.86677534104376 retail=171.97785459649376 arb=-22.111079255353125 delta=0.7813150390374989 dRetail=-1.3060727474093758 dArb=2.0873877863968753", "midask2 {\"P.ask_mid_risk\":2.0}; a64(4003-4272): edge=148.70259477007968 retail=170.57058269381093 arb=-21.8679879236625 delta=-0.3828655319265638 dRetail=-2.7133446500921883 dArb=2.3304791180875", "midask2low25 {\"P.ask_mid_risk\":2.0,\"P.kL\":0.25}; a64(4003-4272): edge=149.2166744644672 retail=170.62019594472656 arb=-21.4035214801875 delta=0.13121416246093465 dRetail=-2.663731399176563 dArb=2.7949455615625", "nearstock {\"P.ydem\":0.8,\"P.W\":100,\"P.ammo_q\":120}; a64(4003-4272): edge=148.96481546988593 retail=174.78124601046406 arb=-25.81643054043125 delta=-0.12064483212031407 dRetail=1.4973186665609388 dArb=-1.61796349868125", "noammo {\"P.ammo\":0}; a64(4003-4272): edge=147.1063833845422 retail=170.20809215848593 arb=-23.101708773785937 delta=-1.9790769174640626 dRetail=-3.075835185417188 dArb=1.0967582679640628", "noscar {\"C.scar\":0}; a64(4003-4272): edge=149.1410035765297 retail=173.58801409773437 arb=-24.44701052105 delta=0.05554327452343466 dRetail=0.30408675383125006 dArb=-0.24854347929999973", "persist025 {\"C.second_level\":0.25} persistent covered back ask; a64(4003-4272): edge=146.4889759375625 retail=172.67626993011876 arb=-26.18729399243125 delta=-2.596484364443751 dRetail=-0.6076574137843755 dArb=-1.98882695068125", "persist10 {\"C.second_level\":1.0} persistent covered back ask; a64(4003-4272): edge=142.835350192 retail=173.3899375749547 arb=-30.554587382835937 delta=-6.2501101100062515 dRetail=0.10601023105156249 dArb=-6.356120341085937", "persist30 {\"C.second_level\":3.0} persistent covered back ask; a64(4003-4272): edge=136.70831954862032 retail=172.18642409315 arb=-35.47810454439375 delta=-12.37714075338594 dRetail=-1.0975032507531277 dArb=-11.27963750264375", "queuewide {\"P.keep_lo\":0.9,\"P.keep_hi\":2.0}; a64(4003-4272): edge=149.6330242722125 retail=174.86824779066563 arb=-25.235223518228125 delta=0.5475639702062469 dRetail=1.584320446762501 dArb=-1.0367564764781247", "risk045 {\"P.kA\":0.45}; a64(4003-4272): edge=148.7929837836375 retail=177.8563487359328 arb=-29.063364952125 delta=-0.29247651836875094 dRetail=4.5724213920296854 dArb=-4.864897910374999", "risk095 {\"P.kA\":0.95}; a64(4003-4272): edge=147.9415457343375 retail=170.23061960351407 arb=-22.289073869079687 delta=-1.1439145676687497 dRetail=-3.053307740389063 dArb=1.9093931726703128", "risk12 {\"P.kA\":1.2}; a64(4003-4272): edge=145.70933433258907 retail=166.83555377606876 arb=-21.12621944341875 delta=-3.3761259694171906 dRetail=-6.448373567834374 dArb=3.07224759833125", "risklowcash {\"P.fu\":0.1,\"P.Hu\":300}; a64(4003-4272): edge=148.84023620306093 retail=173.10223471594688 arb=-24.261998512729686 delta=-0.24522409894531375 dRetail=-0.18169262795624974 dArb=-0.06353147097968759", "safeflow15p200 {\"P.flow_prior\":200,\"P.flow_level\":0.6,\"P.flow_strength\":1.0,\"P.flow_safety\":1.5,\"P.flow_exposure_min\":5.0}; a64(4003-4272): edge=149.49605056414688 retail=174.1441641305875 arb=-24.648113566293752 delta=0.4105902621406236 dRetail=0.8602367866843759 dArb=-0.4496465245437499", "safeflow15p600 {\"P.flow_prior\":600,\"P.flow_level\":0.6,\"P.flow_strength\":1.0,\"P.flow_safety\":1.5,\"P.flow_exposure_min\":5.0}; a64(4003-4272): edge=149.70499605176093 retail=174.1279949292375 arb=-24.422998877326563 delta=0.6195357497546853 dRetail=0.844067585334376 dArb=-0.22453183557656212", "safeflow20p600 {\"P.flow_prior\":600,\"P.flow_level\":0.6,\"P.flow_strength\":1.0,\"P.flow_safety\":2.0,\"P.flow_exposure_min\":5.0}; a64(4003-4272): edge=149.73052607984218 retail=173.98276137167656 arb=-24.25223529168594 delta=0.6450657778359365 dRetail=0.6988340277734393 dArb=-0.05376824993593743", "safeflow25p200 {\"P.flow_prior\":200,\"P.flow_level\":0.6,\"P.flow_strength\":1.0,\"P.flow_safety\":2.5,\"P.flow_exposure_min\":5.0}; a64(4003-4272): edge=150.01018259756876 retail=174.138474543925 arb=-24.128291946210936 delta=0.9247222955624984 dRetail=0.8545472000218766 dArb=0.07017509553906276", "safeflow25p600 {\"P.flow_prior\":600,\"P.flow_level\":0.6,\"P.flow_strength\":1.0,\"P.flow_safety\":2.5,\"P.flow_exposure_min\":5.0}; a64(4003-4272): edge=149.7018075772031 retail=173.80819403411562 arb=-24.106386456764064 delta=0.6163472751968716 dRetail=0.5242666902125013 dArb=0.0920805849859373", "scar5 {\"C.scar\":0.005}; a64(4003-4272): edge=149.27251170877187 retail=172.96074824360937 arb=-23.68823653468125 delta=0.18705140676562387 dRetail=-0.32317910029375196 dArb=0.5102305070687503", "second1 {\"C.second_level\":1.0} covered back ask; a64(4003-4272): edge=143.2598918593656 retail=173.10698587859375 arb=-29.847094019092186 delta=-5.825568442640627 dRetail=-0.1769414653093752 dArb=-5.648626977342187", "second25 {\"C.second_level\":0.25} covered back ask; a64(4003-4272): edge=147.3705000473797 retail=173.36667440213907 arb=-25.9961743546375 delta=-1.7149602546265637 dRetail=0.08274705823593703 dArb=-1.7977073128874999", "second3 {\"C.second_level\":3.0} covered back ask; a64(4003-4272): edge=139.4079767571203 retail=172.57151908573593 arb=-33.16354232847656 delta=-9.677483544885938 dRetail=-0.7124082581671878 dArb=-8.965075286726563", "shortstock {\"P.Wf\":1000}; a64(4003-4272): edge=148.97256565796874 retail=173.2559772366594 arb=-24.283411578545312 delta=-0.1128946440374996 dRetail=-0.02795010724374869 dArb=-0.08494453679531222", "size35 {\"P.m\":3.5}; a64(4003-4272): edge=146.3642402465578 retail=166.51776483822655 arb=-20.15352459150625 delta=-2.721220055448437 dRetail=-6.766162505676565 dArb=4.04494245024375", "size4 {\"P.m\":4.0}; a64(4003-4272): edge=148.29264263483907 retail=169.8992473013797 arb=-21.606604666473437 delta=-0.792817667167188 dRetail=-3.3846800425234376 dArb=2.5918623752765626", "size7 {\"P.m\":7}; a64(4003-4272): edge=149.3402436556797 retail=179.25795260013905 arb=-29.917708944321873 delta=0.2547833536734359 dRetail=5.974025256235937 dArb=-5.719241902571874", "size9 {\"P.m\":9}; a64(4003-4272): edge=147.73389833015312 retail=183.2509529643 arb=-35.51705463401094 delta=-1.3515619718531264 dRetail=9.967025620396875 dArb=-11.318587592260938", "stock03 {\"P.ydf1\":0.3}; a64(4003-4272): edge=143.59379914138125 retail=170.08919322975314 arb=-26.4953940882375 delta=-5.491661160624998 dRetail=-3.1947341141499996 dArb=-2.2969270464875", "stock045 {\"P.ydf1\":0.45}; a64(4003-4272): edge=146.7077610256828 retail=171.7936905520953 arb=-25.08592952624844 delta=-2.377699276323438 dRetail=-1.490236791807812 dArb=-0.8874624844984373", "stock06late {\"P.g1\":3}; a64(4003-4272): edge=149.5823535818578 retail=173.31150963358436 arb=-23.729156051573437 delta=0.4968932798515633 dRetail=0.027582289681249872 dArb=0.4693109901765626", "stock06latecash {\"P.g1\":3,\"P.f1\":0.9}; a64(4003-4272): edge=149.5823535818578 retail=173.31150963358436 arb=-23.729156051573437 delta=0.4968932798515633 dRetail=0.027582289681249872 dArb=0.4693109901765626", "stock075 {\"P.ydf1\":0.75}; a64(4003-4272): edge=149.3427849456875 retail=173.93819462290782 arb=-24.595409677076564 delta=0.25732464368124786 dRetail=0.6542672790046886 dArb=-0.3969426353265627; afull470(4003-5999): edge=136.64821086899659 retail=161.82480741214914 arb=-25.176596543230424 delta=0.004905661478086053 dRetail=0.40275339538765925 dArb=-0.3978477339114894; b128(6000-6463): edge=114.1321522772586 retail=136.5945691059789 arb=-22.462416828876563 delta=0.1741384552789073 dRetail=0.382446141372657 dArb=-0.20830768609843747; bfull523(6000-7997): edge=114.25289028051931 retail=137.89513258245486 arb=-23.64224230200765 delta=-0.1207147579827917 dRetail=0.17993554652848956 dArb=-0.30065030451070734", "stock09 {\"P.ydf1\":0.9}; a64(4003-4272): edge=148.89134339945 retail=174.13503045553125 arb=-25.243687055934377 delta=-0.19411690255625147 dRetail=0.8511031116281265 dArb=-1.045220014184375", "stock1 {\"P.ydf1\":1.0}; a64(4003-4272): edge=148.29016471888124 retail=174.1573126402469 arb=-25.86714792122031 delta=-0.7952955831249995 dRetail=0.8733852963437507 dArb=-1.6686808794703127", "stock12cash {\"P.ydf1\":1.2,\"P.f1\":0.9}; a64(4003-4272): edge=146.40045876605782 retail=174.27251660900313 arb=-27.872057842798437 delta=-2.685001535948438 dRetail=0.9885892651000012 dArb=-3.6735908010484377", "stock15 {\"P.ydf1\":1.5}; a64(4003-4272): edge=145.04113918290625 retail=174.1320015472578 arb=-29.09086236420469 delta=-4.044321119099999 dRetail=0.8480742033546873 dArb=-4.8923953224546874", "stockcash {\"P.f1\":0.9,\"P.fy\":0.9}; a64(4003-4272): edge=148.99049687738594 retail=173.2301024146078 arb=-24.239605537076564 delta=-0.09496342462031215 dRetail=-0.05382492929531324 dArb=-0.041138495326562496", "stockearly {\"P.g1\":10}; a64(4003-4272): edge=149.02965164995626 retail=173.21382889066095 arb=-24.184177240565624 delta=-0.05580865205000013 dRetail=-0.07009845324218755 dArb=0.014289801184375006", "stocklargeearly {\"P.ydf1\":1.0,\"P.g1\":10,\"P.f1\":0.9}; a64(4003-4272): edge=146.68146393947814 retail=174.10808606973126 arb=-27.426622130117188 delta=-2.403996362528125 dRetail=0.8241587258281242 dArb=-3.2281550883671875", "stocklate {\"P.g1\":2}; a64(4003-4272): edge=149.76785850014062 retail=173.30508307109687 arb=-23.537224570807812 delta=0.6823981981343752 dRetail=0.021155727193750362 dArb=0.6612424709421877; afull470(4003-5999): edge=136.37210249264874 retail=161.11900656896702 arb=-24.746904076392553 delta=-0.271202714869787 dRetail=-0.3030474477944679 dArb=0.03184473292638299; b128(6000-6463): edge=114.03874137935313 retail=136.2129189167164 arb=-22.174177537516407 delta=0.0807275573734375 dRetail=0.0007959521101561506 dArb=0.07993160526171873; bfull523(6000-7997): edge=114.33062787860058 retail=137.4625465191799 arb=-23.13191864065086 delta=-0.04297715990152964 dRetail=-0.252650516746463 dArb=0.20967335684608035", "stocklatecash {\"P.g1\":2,\"P.f1\":0.9}; a64(4003-4272): edge=149.76901521457188 retail=173.30508307109687 arb=-23.53606785637344 delta=0.6835549125656253 dRetail=0.021155727193750362 dArb=0.6623991853765627", "stocklowcash {\"P.f1\":0.3}; a64(4003-4272): edge=148.64010937985 retail=173.19553055083594 arb=-24.5554211708375 delta=-0.44535092215625127 dRetail=-0.08839679306718651 dArb=-0.3569541290874998", "stocknear {\"P.g1\":0.5}; a64(4003-4272): edge=147.16532793751563 retail=172.0867856972203 arb=-24.921457759557814 delta=-1.920132364490625 dRetail=-1.1971416466828115 dArb=-0.7229907178078125", "stocknocross {\"P.ydf1\":0.0}; a64(4003-4272): edge=138.80952443557342 retail=168.31504898042186 arb=-29.505524544707814 delta=-10.275935866432814 dRetail=-4.968878363481251 dArb=-5.307057502957813", "stocknolimit {\"P.g1\":98,\"P.f1\":0.4}; a64(4003-4272): edge=146.7120197097953 retail=170.63970322419843 arb=-23.927683514282812 delta=-2.373440592210937 dRetail=-2.6442241197046887 dArb=0.2707835274671878", "stockwide {\"P.g1\":20}; a64(4003-4272): edge=148.10263090208593 retail=172.310761448175 arb=-24.2081305459375 delta=-0.9828293999203128 dRetail=-0.9731658957281274 dArb=-0.009663504187499838", "xu01 {\"P.xu\":0.01}; a64(4003-4272): edge=149.0000765387672 retail=173.46809936698438 arb=-24.468022828059375 delta=-0.08538376323906327 dRetail=0.18417202308125002 dArb=-0.2695557863093746", "xu03 {\"P.xu\":0.03}; a64(4003-4272): edge=149.0000765387672 retail=173.46809936698438 arb=-24.468022828059375 delta=-0.08538376323906327 dRetail=0.18417202308125002 dArb=-0.2695557863093746", "xu03fu5 {\"P.xu\":0.03,\"P.fu\":0.5}; a64(4003-4272): edge=148.10102045304376 retail=172.74420342965936 arb=-24.64318297646875 delta=-0.9844398489625003 dRetail=-0.5397239142437509 dArb=-0.4447159347187495", "safeflow20p200 {\"P.flow_prior\":200,\"P.flow_level\":0.6,\"P.flow_strength\":1.0,\"P.flow_safety\":2.0,\"P.flow_exposure_min\":5.0}; a64(4003-4272): edge=149.8478867810125 retail=174.13590259440937 arb=-24.28801581325 delta=0.7624264790062519 dRetail=0.8519752505062517 dArb=-0.08954877149999993; afull470(4003-5999): edge=137.1939911004032 retail=161.8647929662319 arb=-24.670801865903616 delta=0.5506858928846821 dRetail=0.4427389494704252 dArb=0.10794694341531923; b128(6000-6463): edge=114.60126612366406 retail=136.6057198495586 arb=-22.00445372605 delta=0.6432523016843763 dRetail=0.39359688495234424 dArb=0.24965541672812508; bfull523(6000-7997): edge=114.68533944838356 retail=137.86592867494187 arb=-23.180589226630403 delta=0.3117344098814534 dRetail=0.15073163901548753 dArb=0.16100277086653939; FROZEN full-file train4000={\"total_edge\":98.84950498965385,\"retail_edge\":124.4013873695152,\"arb_edge\":-25.551882379876773}; unseen4000={\"total_edge\":98.47028967306635,\"retail_edge\":126.1276183775221,\"arb_edge\":-27.657328704453427}; unseen base4000={\"total_edge\":98.28063388702982,\"retail_edge\":126.01907227628422,\"arb_edge\":-27.73843838925235}; unseen spread-3 delta=0.7459421279705998 SE=0.2441846966634406; zero failures; code SHA256 95401cdb118b2fcbe2f3b98e2b3422a4fa814feaa885241eda201832097b4510. No code or parameter changes followed freeze or unseen evaluation."], "next": "The unseen spread-3 gain exceeds two paired standard errors. Merge this guarded estimator with its per-instance parameters, then check the combined four-spread policy on a fresh seed bank before expanding the goal. Merging this candidate requires the self.s == 3 guarded estimator as well as its five parameters. For further stock research, separate demand estimation from stock-entry timing and near-zero cover replenishment. Back levels behind competitor liquidity were consistently poor in this screening."}