""" Step 2: Sweep Z Entry × TP × SL (core R:R params) Uses cached data from step1. NATR/CHOP/Vol at defaults. Usage: cd /home/app/trading-bot-bybit python3 backtests/step2_sweep_z_tp_sl.py """ import json import time import numpy as np from itertools import product # ============================================================ # FIXED CONFIG # ============================================================ ORDER_USD = 7.0 LEVERAGE = 3 VWAP_PERIOD = 50 TAKER_FEE = 0.00055 DAYS = 30 # Fixed filters (defaults from current bot) NATR_MIN = 0.5 NATR_MAX = 3.0 CHOP_MIN = 45 COOLDOWN = 12 # bars # ============================================================ # SWEEP GRID — only core params # ============================================================ Z_ENTRIES = [1.5, 1.8, 2.0, 2.5, 3.0, 3.5, 4.0] Z_MAXES = [0, 3.0, 4.0, 5.0, 6.0] TP_PCTS = [0.3, 0.5, 0.75, 1.0, 1.5, 2.0, 3.0, 5.0] SL_PCTS = [0.5, 1.0, 1.5, 2.0, 3.0, 5.0, 8.0, 10.0] def simulate(z_scores, natr, chop, closes, highs, lows, z_entry, z_max, tp_pct, sl_pct): n = len(closes) deals = [] in_trade = False side = None entry_price = 0 entry_bar = 0 cooldown_until = 0 for i in range(VWAP_PERIOD, n): if in_trade: z = z_scores[i] closed = False close_price = 0 reason = "" if side == "LONG": tp_p = entry_price * (1 + tp_pct / 100) sl_p = entry_price * (1 - sl_pct / 100) if lows[i] <= sl_p: close_price = sl_p; reason = "SL"; closed = True elif highs[i] >= tp_p: close_price = tp_p; reason = "TP"; closed = True elif z >= -0.3 and closes[i] > entry_price: close_price = closes[i]; reason = "Z-TP"; closed = True else: tp_p = entry_price * (1 - tp_pct / 100) sl_p = entry_price * (1 + sl_pct / 100) if highs[i] >= sl_p: close_price = sl_p; reason = "SL"; closed = True elif lows[i] <= tp_p: close_price = tp_p; reason = "TP"; closed = True elif z <= 0.3 and closes[i] < entry_price: close_price = closes[i]; reason = "Z-TP"; closed = True if not closed and (i - entry_bar) >= 36: close_price = closes[i]; reason = "TIME"; closed = True if closed: qty = (ORDER_USD * LEVERAGE) / entry_price pnl = qty * (close_price - entry_price) if side == "LONG" else qty * (entry_price - close_price) pnl -= qty * entry_price * TAKER_FEE + qty * close_price * TAKER_FEE deals.append({"pnl": pnl, "reason": reason, "bars": i - entry_bar}) in_trade = False cooldown_until = i + COOLDOWN continue if i < cooldown_until: continue z = z_scores[i] if abs(z) <= z_entry: continue if z_max > 0 and abs(z) > z_max: continue if natr[i] < NATR_MIN or (NATR_MAX > 0 and natr[i] > NATR_MAX): continue if CHOP_MIN > 0 and chop[i] < CHOP_MIN: continue side = "LONG" if z < -z_entry else "SHORT" entry_price = closes[i] entry_bar = i in_trade = True if in_trade: qty = (ORDER_USD * LEVERAGE) / entry_price cp = closes[-1] pnl = qty * (cp - entry_price) if side == "LONG" else qty * (entry_price - cp) pnl -= qty * entry_price * TAKER_FEE + qty * cp * TAKER_FEE deals.append({"pnl": pnl, "reason": "END", "bars": n - 1 - entry_bar}) return deals def main(): print("=" * 80) print(" STEP 2: Sweep Z Entry × Z Max × TP × SL") print(" Fixed: NATR 0.5-3.0, CHOP >= 45, CD 12 bars") print("=" * 80) # Load cached data print("\n Loading cached data...") with open("/home/app/trading-bot-bybit/backtests/data_cache_30d.json") as f: cache = json.load(f) symbols = cache["symbols"] print(f" {len(symbols)} symbols, fetched {cache['fetched_at']}") # Prep numpy arrays sym_data = {} for sym, d in symbols.items(): sym_data[sym] = { "closes": np.array(d["closes"]), "highs": np.array(d["highs"]), "lows": np.array(d["lows"]), "z": np.array(d["z"]), "natr": np.array(d["natr"]), "chop": np.array(d["chop"]), } # Filter impossible combos combos = [] for z_e, z_m, tp, sl in product(Z_ENTRIES, Z_MAXES, TP_PCTS, SL_PCTS): if z_m > 0 and z_e >= z_m: continue combos.append((z_e, z_m, tp, sl)) print(f" {len(combos)} valid combinations\n") results = [] t0 = time.time() for ci, (z_e, z_m, tp, sl) in enumerate(combos): all_deals = [] for sym, sd in sym_data.items(): deals = simulate(sd["z"], sd["natr"], sd["chop"], sd["closes"], sd["highs"], sd["lows"], z_e, z_m, tp, sl) all_deals.extend(deals) if len(all_deals) < 5: continue total_pnl = sum(d["pnl"] for d in all_deals) wins = [d for d in all_deals if d["pnl"] > 0] losses = [d for d in all_deals if d["pnl"] <= 0] wr = len(wins) / len(all_deals) * 100 gp = sum(d["pnl"] for d in wins) if wins else 0 gl = abs(sum(d["pnl"] for d in losses)) if losses else 0.001 pf = gp / gl tp_cnt = sum(1 for d in all_deals if d["reason"] == "TP") ztp_cnt = sum(1 for d in all_deals if d["reason"] == "Z-TP") sl_cnt = sum(1 for d in all_deals if d["reason"] == "SL") time_cnt = sum(1 for d in all_deals if d["reason"] == "TIME") results.append({ "z_entry": z_e, "z_max": z_m, "tp_pct": tp, "sl_pct": sl, "deals": len(all_deals), "pnl": round(total_pnl, 2), "pnl_day": round(total_pnl / DAYS, 2), "wr": round(wr, 1), "pf": round(pf, 2), "avg_win": round(gp / len(wins), 3) if wins else 0, "avg_loss": round(gl / len(losses), 3) if losses else 0, "tp": tp_cnt, "ztp": ztp_cnt, "sl": sl_cnt, "time": time_cnt, }) if (ci + 1) % 200 == 0: elapsed = time.time() - t0 print(f" ... {ci+1}/{len(combos)} ({elapsed:.0f}s)") elapsed = time.time() - t0 profitable = [r for r in results if r["pnl"] > 0] print(f"\n Done in {elapsed:.0f}s! {len(results)} valid, {len(profitable)} profitable") # ============================================================ # DISPLAY # ============================================================ header = f"{'#':>3} {'Z':>4} {'Zmax':>4} {'TP%':>5} {'SL%':>5} | {'Deals':>5} {'PnL':>8} {'$/d':>6} {'WR%':>5} {'PF':>6} {'AvgW':>7} {'AvgL':>7} | {'TP':>4} {'ZTP':>4} {'SL':>4} {'TIM':>4}" def prow(i, r): zm = r["z_max"] if r["z_max"] > 0 else 0 print(f"{i:>3} {r['z_entry']:>4.1f} {zm:>4.1f} {r['tp_pct']:>5.2f} {r['sl_pct']:>5.1f} | {r['deals']:>5} ${r['pnl']:>+7.2f} ${r['pnl_day']:>+5.2f} {r['wr']:>5.1f} {r['pf']:>6.2f} ${r['avg_win']:>6.3f} ${r['avg_loss']:>6.3f} | {r['tp']:>4} {r['ztp']:>4} {r['sl']:>4} {r['time']:>4}") # TOP 25 by PnL (min 15 deals) by_pnl = sorted([r for r in results if r["deals"] >= 15], key=lambda x: x["pnl"], reverse=True) print(f"\n{'='*110}") print(f" TOP 25 by PnL (min 15 deals, 30 days)") print(f"{'='*110}") print(header); print("-" * 110) for i, r in enumerate(by_pnl[:25]): prow(i+1, r) # TOP 25 by PF (min 15 deals) by_pf = sorted([r for r in results if r["deals"] >= 15 and r["pf"] < 100], key=lambda x: x["pf"], reverse=True) print(f"\n{'='*110}") print(f" TOP 25 by Profit Factor (min 15 deals)") print(f"{'='*110}") print(header); print("-" * 110) for i, r in enumerate(by_pf[:25]): prow(i+1, r) # BALANCED: PF > 1.2, >= 30 deals, WR > 50% balanced = sorted([r for r in results if r["pf"] > 1.2 and r["deals"] >= 30 and r["wr"] > 50], key=lambda x: x["pnl"], reverse=True) if balanced: print(f"\n{'='*110}") print(f" BALANCED (PF > 1.2, >= 30 deals, WR > 50%)") print(f"{'='*110}") print(header); print("-" * 110) for i, r in enumerate(balanced[:25]): prow(i+1, r) # Save out = "/home/app/trading-bot-bybit/backtests/results_step2_z_tp_sl.json" with open(out, "w") as f: json.dump({ "fixed": {"natr_min": NATR_MIN, "natr_max": NATR_MAX, "chop_min": CHOP_MIN, "cooldown": COOLDOWN}, "grid": {"z_entry": Z_ENTRIES, "z_max": Z_MAXES, "tp_pct": TP_PCTS, "sl_pct": SL_PCTS}, "total_combos": len(combos), "valid": len(results), "profitable": len(profitable), "results": sorted(results, key=lambda x: x["pnl"], reverse=True), }, f, indent=2) print(f"\n Saved to {out}") if __name__ == "__main__": main()