diff --git a/clp_hedger.py b/clp_hedger.py index f3b6457..6a633b1 100644 --- a/clp_hedger.py +++ b/clp_hedger.py @@ -17,8 +17,10 @@ sys.path.append(project_root) try: from logging_utils import setup_logging except ImportError: - logging.basicConfig(level=logging.INFO) setup_logging = None + # Ensure root logger is clean if we can't use setup_logging + logging.getLogger().handlers.clear() + logging.basicConfig(level=logging.INFO) from eth_account import Account from hyperliquid.exchange import Exchange @@ -43,6 +45,7 @@ class UnixMsLogFilter(logging.Filter): # Configure Logging logger = logging.getLogger("SCALPER_HEDGER") logger.setLevel(logging.INFO) +logger.propagate = False # Prevent double logging from root logger logger.handlers.clear() # Clear existing handlers to prevent duplicates # Console Handler diff --git a/clp_scalper_hedger.py b/clp_scalper_hedger.py new file mode 100644 index 0000000..ca2e64f --- /dev/null +++ b/clp_scalper_hedger.py @@ -0,0 +1,1230 @@ +import os +import time +import logging +import sys +import math +import json +import threading +from decimal import Decimal, getcontext, ROUND_DOWN, ROUND_HALF_UP +from dotenv import load_dotenv + +# --- FIX: Add project root to sys.path to import local modules --- +current_dir = os.path.dirname(os.path.abspath(__file__)) +project_root = os.path.dirname(current_dir) +sys.path.append(project_root) + +# Now we can import from root +from logging_utils import setup_logging +from eth_account import Account +from hyperliquid.exchange import Exchange +from hyperliquid.info import Info +from hyperliquid.utils import constants + +# Load environment variables from .env in current directory +dotenv_path = os.path.join(current_dir, '.env') +if os.path.exists(dotenv_path): + load_dotenv(dotenv_path) +else: + # Fallback to default search + load_dotenv() + +# Configure logging and get logger instance +logger = setup_logging("info", "SCALPER_HEDGER") +logger.propagate = False # Prevent double logging from root logger + +# Update root logger to ensure all logging calls go to our handlers +root_logger = logging.getLogger() +root_logger.handlers.clear() +for handler in logger.handlers: + root_logger.addHandler(handler) +root_logger.setLevel(logger.level) + +# --- DECIMAL PRECISION CONFIGURATION --- +# Set high precision for calculations to avoid float_to_wire serialization errors +getcontext().prec = 28 + +def safe_decimal_from_float(value): + """Safely convert float to Decimal without precision loss""" + if value is None: + return Decimal('0') + return Decimal(str(value)) + +def round_to_sz_decimals_precise(amount, sz_decimals): + """ + Round amount to specified decimals using Decimal for precise rounding + Avoids float_to_wire serialization errors + """ + if amount == 0: + return 0.0 + + # Convert to Decimal precisely + decimal_amount = safe_decimal_from_float(abs(amount)) + + # Create rounding quantizer + quantizer = Decimal('1').scaleb(-sz_decimals) # Equivalent to 10^(-sz_decimals) + + # Round using ROUND_DOWN to avoid exceeding limits + rounded = decimal_amount.quantize(quantizer, rounding=ROUND_DOWN) + + # Convert back to float for API compatibility + return float(rounded) + +def round_to_sig_figs_precise(x, sig_figs=5): + """ + Round to significant figures using Decimal for precision + Ensures compatibility with Hyperliquid's 5 sig fig requirement + """ + if x == 0: + return 0.0 + + decimal_x = safe_decimal_from_float(x) + + # Simple approach: use string-based rounding for significant figures + str_x = f"{decimal_x:.{sig_figs}g}" + return float(str_x) + +def validate_trade_size(size, sz_decimals, min_order_value=10.0, price=3000.0): + """ + Validate and adjust trade size to meet exchange requirements + """ + if size <= 0: + return 0.0 + + # Round to correct decimals + rounded_size = round_to_sz_decimals_precise(size, sz_decimals) + + # Check minimum order value + order_value = rounded_size * price + if order_value < min_order_value: + return 0.0 + + # Ensure not too small (avoid dust) + min_size = 10 ** (-sz_decimals) + if rounded_size < min_size: + return 0.0 + + return rounded_size + +# --- CONFIGURATION --- +COIN_SYMBOL = "ETH" +CHECK_INTERVAL = 1 # Optimized for speed (was 5) +LEVERAGE = 5 # 3x Leverage +STATUS_FILE = "hedge_status.json" + +# Import enhanced order functions +import sys +import os +current_dir = os.path.dirname(os.path.abspath(__file__)) +sys.path.append(current_dir) +from enhanced_order_functions import get_price_momentum_pct, get_dynamic_price_buffer + +# REMOVED: Uniswap Spread Monitoring for cleaner delta-zero hedging +# - Eliminated external RPC dependencies +# - Reduced complexity and failure points +# - Focused on core delta-zero hedging mission +# - Improved performance and reliability + +# --- STRATEGY ZONES (Percent of Range Width) --- +# Bottom Hedge Zone: Covers entire range (0.0 to 1.5) -> Always Active +ZONE_BOTTOM_HEDGE_LIMIT = 1 + +# Close Zone: Disabled (Set > 1.0) +ZONE_CLOSE_START = 10.0 +ZONE_CLOSE_END = 11.0 + +# Top Hedge Zone: Disabled/Redundant +ZONE_TOP_HEDGE_START = 10.0 + +# --- ORDER SETTINGS --- +PRICE_BUFFER_PCT = 0.0015 # 0.25% price move triggers order update (Optimized for capital safety) +MIN_THRESHOLD_ETH = 0.012 # Minimum trade size in ETH (~$35, Optimized for significant trades) +MIN_ORDER_VALUE_USD = 10.0 # Minimum order value for API safety + +# --- CAPITAL SAFETY PARAMETERS --- +DYNAMIC_THRESHOLD_MULTIPLIER = 1.3 # Reduce from 1.5 for smoother operation with 7k position +MIN_TIME_BETWEEN_TRADES = 25 # Reduce from 30 for more responsive 7k hedging +MAX_HEDGE_MULTIPLIER = 1.25 # Increase from 1.2 for adequate 7k position buffer + +# --- RANGE EDGE PROTECTION PARAMETERS --- +# Conservative settings for $8000 CLP positions with higher capital efficiency +EDGE_PROXIMITY_PCT = 0.04 # 5% of range width from edge (conservative fee protection) +VELOCITY_THRESHOLD_PCT = 0.0005 # Multi-timeframe velocity threshold (0.05% smoothed over 5s) for emergency override +POSITION_OPEN_EDGE_PROXIMITY_PCT = 0.06 # 7% (very conservative when earning fees) +POSITION_CLOSED_EDGE_PROXIMITY_PCT = 0.025 # 3% (standard when position closed) +LARGE_HEDGE_MULTIPLIER = 2.8 # More forgiving for large hedge requirements + +# Multi-Timeframe Velocity Calculation (Option 3B): +# - 1s velocity: Immediate response for extreme moves (>0.2% per second) +# - 5s average: Smoothed signal for sustained directional moves +# - Reduces false triggers from 1s noise while maintaining emergency response capability + +# REMOVED: UniswapPriceMonitor class for cleaner delta-zero hedging +# Benefits: +# - Eliminated external RPC dependencies +# - Reduced threading complexity +# - Removed external failure points +# - Focused on core delta-zero hedging mission +# - Improved system reliability and performance + +def get_active_automatic_position(): + if not os.path.exists(STATUS_FILE): + return None + try: + with open(STATUS_FILE, 'r') as f: + data = json.load(f) + for entry in data: + if entry.get('type') == 'AUTOMATIC' and entry.get('status') in ['OPEN', 'PENDING_HEDGE', 'CLOSING']: + return entry + except Exception as e: + logging.error(f"ERROR reading status file: {e}") + return None + +def update_position_zones_in_json(token_id, zones_data): + """Updates the active position in JSON with calculated zone prices and formats the entry.""" + if not os.path.exists(STATUS_FILE): return + try: + with open(STATUS_FILE, 'r') as f: + data = json.load(f) + + updated = False + for i, entry in enumerate(data): + if entry.get('type') == 'AUTOMATIC' and (entry.get('status') == 'OPEN' or entry.get('status') == 'PENDING_HEDGE') and entry.get('token_id') == token_id: + + # Merge Zones + for k, v in zones_data.items(): + entry[k] = v + + # Format & Reorder + open_ts = entry.get('timestamp_open', int(time.time())) + opened_str = time.strftime('%H:%M %d/%m/%y', time.localtime(open_ts)) + + # Reconstruct Dict in Order + new_entry = { + "type": entry.get('type'), + "token_id": entry.get('token_id'), + "opened": opened_str, + "status": entry.get('status'), + "entry_price": round(entry.get('entry_price', 0), 2), + "target_value": round(entry.get('target_value', 0), 2), + # Amounts might be string or float or int. Ensure float. + "amount0_initial": round(float(entry.get('amount0_initial', 0)), 4), + "amount1_initial": round(float(entry.get('amount1_initial', 0)), 2), + + "range_upper": round(entry.get('range_upper', 0), 2), + "zone_top_start_price": entry.get('zone_top_start_price'), + "zone_close_top_price": entry.get('zone_close_top_price'), + "zone_close_bottom_price": entry.get('zone_close_bottom_price'), + "zone_bottom_limit_price": entry.get('zone_bottom_limit_price'), + "range_lower": round(entry.get('range_lower', 0), 2), + + "static_long": entry.get('static_long', 0.0), + "timestamp_open": open_ts, + "timestamp_close": entry.get('timestamp_close') + } + + data[i] = new_entry + updated = True + break + + if updated: + with open(STATUS_FILE, 'w') as f: + json.dump(data, f, indent=2) + logging.info(f"Updated JSON with Formatted Zone Prices for Position {token_id}") + except Exception as e: + logging.error(f"Error updating JSON zones: {e}") + +# Legacy functions replaced with precise decimal versions above +def round_to_sig_figs(x, sig_figs=5): + """Legacy wrapper - use round_to_sig_figs_precise""" + return round_to_sig_figs_precise(x, sig_figs) + +def round_to_sz_decimals(amount, sz_decimals=4): + """Legacy wrapper - use round_to_sz_decimals_precise""" + return round_to_sz_decimals_precise(amount, sz_decimals) + +def update_position_stats(token_id, stats_data): + """Updates the active position in JSON with stats (zones, pnl, fees).""" + if not os.path.exists(STATUS_FILE): return + try: + with open(STATUS_FILE, 'r') as f: + data = json.load(f) + + updated = False + for i, entry in enumerate(data): + if entry.get('type') == 'AUTOMATIC' and entry.get('status') in ['OPEN', 'PENDING_HEDGE', 'CLOSING'] and entry.get('token_id') == token_id: + + # Merge Stats + for k, v in stats_data.items(): + entry[k] = v + + # Format & Reorder (Preserve existing logic) + open_ts = entry.get('timestamp_open', int(time.time())) + opened_str = time.strftime('%H:%M %d/%m/%y', time.localtime(open_ts)) + + new_entry = { + "type": entry.get('type'), + "token_id": entry.get('token_id'), + "opened": opened_str, + "status": entry.get('status'), + "entry_price": round(entry.get('entry_price', 0), 2), + "target_value": round(entry.get('target_value', 0), 2), + "amount0_initial": round(float(entry.get('amount0_initial', 0)), 4), + "amount1_initial": round(float(entry.get('amount1_initial', 0)), 2), + + "range_upper": round(entry.get('range_upper', 0), 2), + "zone_top_start_price": entry.get('zone_top_start_price'), + "zone_close_top_price": entry.get('zone_close_top_price'), + "zone_close_bottom_price": entry.get('zone_close_bottom_price'), + "zone_bottom_limit_price": entry.get('zone_bottom_limit_price'), + "range_lower": round(entry.get('range_lower', 0), 2), + + "static_long": entry.get('static_long', 0.0), + + # New Stats + "hedge_pnl_realized": round(entry.get('hedge_pnl_realized', 0.0), 2), + "hedge_fees_paid": round(entry.get('hedge_fees_paid', 0.0), 2), + + "timestamp_open": open_ts, + "timestamp_close": entry.get('timestamp_close') + } + + data[i] = new_entry + updated = True + break + + if updated: + with open(STATUS_FILE, 'w') as f: + json.dump(data, f, indent=2) + # logging.info(f"Updated JSON stats for Position {token_id}") + except Exception as e: + logging.error(f"Error updating JSON stats: {e}") + +class HyperliquidStrategy: + def __init__(self, entry_amount0, entry_amount1, target_value, entry_price, low_range, high_range, start_price, static_long=0.0): + self.entry_amount0 = entry_amount0 + self.entry_amount1 = entry_amount1 + self.target_value = target_value + self.entry_price = entry_price + self.low_range = low_range + self.high_range = high_range + self.static_long = static_long + + self.start_price = start_price + self.gap = max(0.0, entry_price - start_price) + self.recovery_target = entry_price + (2 * self.gap) + + self.current_mode = "NORMAL" + self.last_switch_time = 0 + + logging.info(f"Strategy Init. Start Px: {start_price:.2f} | Gap: {self.gap:.2f} | Recovery Tgt: {self.recovery_target:.2f}") + + try: + sqrt_P = math.sqrt(entry_price) + sqrt_Pa = math.sqrt(low_range) + sqrt_Pb = math.sqrt(high_range) + + self.L = 0.0 + + # Method 1: Use Amount0 (WETH) + if entry_amount0 > 0: + # If amount is huge (Wei), scale it. If small (ETH), use as is. + if entry_amount0 > 1000: amount0_eth = entry_amount0 / 10**18 + else: amount0_eth = entry_amount0 + + denom0 = (1/sqrt_P) - (1/sqrt_Pb) + if denom0 > 0.00000001: + self.L = amount0_eth / denom0 + logging.info(f"Calculated L from Amount0: {self.L:.4f}") + + # Method 2: Use Amount1 (USDC) + if self.L == 0.0 and entry_amount1 > 0: + if entry_amount1 > 100000: amount1_usdc = entry_amount1 / 10**6 + else: amount1_usdc = entry_amount1 + + denom1 = sqrt_P - sqrt_Pa + if denom1 > 0.00000001: + self.L = amount1_usdc / denom1 + logging.info(f"Calculated L from Amount1: {self.L:.4f}") + + # Method 3: Fallback Heuristic + if self.L == 0.0: + logging.warning("Amounts missing or 0. Using Target Value Heuristic.") + max_eth_heuristic = target_value / low_range + denom_h = (1/sqrt_Pa) - (1/sqrt_Pb) + if denom_h > 0: + self.L = max_eth_heuristic / denom_h + logging.info(f"Calculated L from Target Value: {self.L:.4f}") + else: + logging.error("Critical: Denominator 0 in Heuristic. Invalid Range?") + self.L = 0.0 + + except Exception as e: + logging.error(f"Error calculating liquidity: {e}") + sys.exit(1) + + def get_pool_delta(self, current_price): + if current_price >= self.high_range: return 0.0 + if current_price <= self.low_range: + sqrt_Pa = math.sqrt(self.low_range) + sqrt_Pb = math.sqrt(self.high_range) + return self.L * ((1/sqrt_Pa) - (1/sqrt_Pb)) + + sqrt_P = math.sqrt(current_price) + sqrt_Pb = math.sqrt(self.high_range) + return self.L * ((1/sqrt_P) - (1/sqrt_Pb)) + + def calculate_rebalance(self, current_price, current_short_position_size): + pool_delta = self.get_pool_delta(current_price) + + # --- Over-Hedge Logic --- + overhedge_pct = 0.0 + range_width = self.high_range - self.low_range + if range_width > 0: + price_pct = (current_price - self.low_range) / range_width + + # If below 0.8 (80%) of range + if price_pct < 0.8: + # Formula: 0.75% boost for every 0.1 drop below 0.8 + # Example: At 0.6 (60%), diff is 0.2. (0.2/0.1)*0.0075 = 0.015 (1.5%) + overhedge_pct = ((0.8 - max(0.0, price_pct)) / 0.1) * 0.0075 + + raw_target_short = pool_delta + self.static_long + + # Apply Boost + adjusted_target_short = raw_target_short * (1.0 + overhedge_pct) + + target_short_size = adjusted_target_short + diff = target_short_size - abs(current_short_position_size) + + return { + "current_price": current_price, + "pool_delta": pool_delta, + "target_short": target_short_size, + "current_short": abs(current_short_position_size), + "diff": diff, + "action": "SELL" if diff > 0 else "BUY", + "mode": "OVERHEDGE" if overhedge_pct > 0 else "NORMAL", + "overhedge_pct": overhedge_pct + } + +class ScalperHedger: + def __init__(self): + self.private_key = os.environ.get("SCALPER_AGENT_PK") + self.vault_address = os.environ.get("MAIN_WALLET_ADDRESS") + + if not self.private_key: + logging.error("No SCALPER_AGENT_PK found in .env") + sys.exit(1) + + self.account = Account.from_key(self.private_key) + self.info = Info(constants.MAINNET_API_URL, skip_ws=True) + self.exchange = Exchange(self.account, constants.MAINNET_API_URL, account_address=self.vault_address) + + try: + logging.info(f"Setting leverage to {LEVERAGE}x (Cross)...") + self.exchange.update_leverage(LEVERAGE, COIN_SYMBOL, is_cross=True) + except Exception as e: + logging.error(f"Failed to update leverage: {e}") + + self.strategy = None + self.sz_decimals = self._get_sz_decimals(COIN_SYMBOL) + self.active_position_id = None + self.active_order = None + + # --- Capital Safety Tracking Variables --- + self.last_price = None # For volatility detection + self.last_trade_time = 0 # For minimum time between trades + + # --- Velocity Tracking for Edge Protection --- + self.last_price_for_velocity = None # For velocity calculations + self.price_history = [] # Track last N prices for velocity + self.velocity_history = [] # Track velocity history for multi-timeframe analysis + + # --- Price Momentum Tracking --- + self.price_momentum_history = [] # Track last 5 price changes for momentum + + # --- Order Management Enhancements --- + self.order_placement_time = 0 # Track when orders are placed + self.original_order_side = None # Track original order intent (BUY/SELL) + + # --- Order Management Enhancements --- + self.order_placement_time = 0 # Track when orders are placed + self.original_order_side = None # Track original order intent (BUY/SELL) + + # --- PnL Tracking --- + self.strategy_start_time = 0 + self.last_pnl_check_time = 0 + self.trade_history_seen = set() # Store fill IDs to avoid double counting + self.accumulated_pnl = 0.0 + self.accumulated_fees = 0.0 + + # REMOVED: Uniswap Monitor for cleaner delta-zero hedging + # Benefits: No external RPC calls, no threading overhead, focused on core mission + + logging.info(f"[DELTA] Delta-Zero Scalper Hedger initialized. Agent: {self.account.address}") + logging.info(f"[SAFE] Capital Safety: Price Buffer {PRICE_BUFFER_PCT*100:.1f}% | Min Threshold {MIN_THRESHOLD_ETH} ETH (~${MIN_THRESHOLD_ETH*3000:.0f} USD)") + logging.info(f"[TRIG] Dynamic Protection: Volatility Multiplier {DYNAMIC_THRESHOLD_MULTIPLIER}x | Trade Cooldown {MIN_TIME_BETWEEN_TRADES}s | Max Hedge {MAX_HEDGE_MULTIPLIER*100:.0f}%") + logging.info(f"[INFO] Uniswap spread monitoring removed for cleaner delta-zero hedging") + + def _init_strategy(self, position_data): + try: + entry_amount0 = position_data.get('amount0_initial', 0) + entry_amount1 = position_data.get('amount1_initial', 0) + target_value = position_data.get('target_value', 50.0) + + entry_price = position_data['entry_price'] + lower = position_data['range_lower'] + upper = position_data['range_upper'] + static_long = position_data.get('static_long', 0.0) + + start_price = self.get_market_price(COIN_SYMBOL) + if start_price is None: + logging.warning("Waiting for initial price to start strategy...") + return + + self.strategy = HyperliquidStrategy( + entry_amount0=entry_amount0, + entry_amount1=entry_amount1, + target_value=target_value, + entry_price=entry_price, + low_range=lower, + high_range=upper, + start_price=start_price, + static_long=static_long + ) + + # Reset tracking variables for new strategy + self.last_price = start_price + self.last_trade_time = 0 + self.last_price_for_velocity = start_price + self.price_history = [start_price] # Initialize price history for velocity + self.velocity_history = [] # Initialize velocity history for multi-timeframe analysis + + # Reset PnL Tracking + self.strategy_start_time = int(time.time() * 1000) # MS + self.trade_history_seen = set() + self.accumulated_pnl = 0.0 + self.accumulated_fees = 0.0 + self.active_position_id = position_data['token_id'] + + # Init JSON stats + update_position_stats(self.active_position_id, { + "hedge_pnl_realized": 0.0, + "hedge_fees_paid": 0.0 + }) + + logging.info(f"[DELTA] Delta-Zero Strategy Initialized for Position {position_data['token_id']}.") + logging.info(f"[INFO] CLP Range: ${lower:.2f} - ${upper:.2f} | Entry: ${entry_price:.2f} | Width: {((upper-lower)/lower)*100:.2f}%") + logging.info(f"[TRIG] Delta-Zero Hedging ACTIVE across entire CLP range with capital safety protections") + logging.info(f"[SAFE] Edge Protection: {EDGE_PROXIMITY_PCT*100:.1f}% proximity | Velocity: {VELOCITY_THRESHOLD_PCT*100:.2f}% threshold | Position-aware: OPEN={POSITION_OPEN_EDGE_PROXIMITY_PCT*100:.1f}% | CLOSED={POSITION_CLOSED_EDGE_PROXIMITY_PCT*100:.1f}%") + self.active_position_id = position_data['token_id'] + + except Exception as e: + logging.error(f"Failed to init strategy: {e}") + self.strategy = None + + def track_fills_and_pnl(self, force=False): + """Fetches recent fills, filters by strategy start, accumulates PnL/Fees, and updates JSON.""" + try: + now = time.time() + # Check every 10 seconds unless forced + if not force and now - self.last_pnl_check_time < 10: + return + + self.last_pnl_check_time = now + + # Get user fills (returns list of recent fills) + user_fills = self.info.user_fills(self.vault_address or self.account.address) + + new_activity = False + + for fill in user_fills: + # Check Coin + if fill['coin'] != COIN_SYMBOL: continue + + # Check Time (fill['time'] is ms) + if fill['time'] < self.strategy_start_time: continue + + # Check duplication via unique 'tid' + fill_id = fill.get('tid') + if not fill_id: continue + + if fill_id in self.trade_history_seen: + continue + + # New Fill Found + self.trade_history_seen.add(fill_id) + + fees = float(fill['fee']) + pnl = float(fill['closedPnl']) # Realized PnL from this trade (if closing) + + self.accumulated_fees += fees + self.accumulated_pnl += pnl + new_activity = True + + logging.info(f"[FILL] New Fill Processed: {fill['side']} {fill['sz']} @ {fill['px']} | Fee: ${fees:.4f} | Realized PnL: ${pnl:.4f}") + + if new_activity: + logging.info(f"[PNL] Total Strategy PnL (Hedge): ${self.accumulated_pnl:.2f} | Fees Paid: ${self.accumulated_fees:.2f}") + update_position_stats(self.active_position_id, { + "hedge_pnl_realized": self.accumulated_pnl, + "hedge_fees_paid": self.accumulated_fees + }) + + except Exception as e: + logging.error(f"Error tracking fills: {e}") + + def _get_sz_decimals(self, coin): + try: + meta = self.info.meta() + for asset in meta["universe"]: + if asset["name"] == coin: + return asset["szDecimals"] + return 4 + except: return 4 + + def get_order_book_levels(self, coin): + try: + l2_snapshot = self.info.l2_snapshot(coin) + if l2_snapshot and 'levels' in l2_snapshot: + bids = l2_snapshot['levels'][0] + asks = l2_snapshot['levels'][1] + if bids and asks: + best_bid = float(bids[0]['px']) + best_ask = float(asks[0]['px']) + mid = (best_bid + best_ask) / 2 + return {'bid': best_bid, 'ask': best_ask, 'mid': mid} + return None + except: + return None + + def get_market_price(self, coin): + try: + mids = self.info.all_mids() + if coin in mids: return float(mids[coin]) + except: pass + return None + + def get_order_book_mid(self, coin): + try: + l2_snapshot = self.info.l2_snapshot(coin) + if l2_snapshot and 'levels' in l2_snapshot: + bids = l2_snapshot['levels'][0] + asks = l2_snapshot['levels'][1] + if bids and asks: + best_bid = float(bids[0]['px']) + best_ask = float(asks[0]['px']) + return (best_bid + best_ask) / 2 + return self.get_market_price(coin) + except: + return self.get_market_price(coin) + + def get_funding_rate(self, coin): + try: + meta, asset_ctxs = self.info.meta_and_asset_ctxs() + for i, asset in enumerate(meta["universe"]): + if asset["name"] == coin: + return float(asset_ctxs[i]["funding"]) + return 0.0 + except: return 0.0 + + def get_current_position(self, coin): + try: + user_state = self.info.user_state(self.vault_address or self.account.address) + for pos in user_state["assetPositions"]: + if pos["position"]["coin"] == coin: + return { + 'size': float(pos["position"]["szi"]), + 'pnl': float(pos["position"]["unrealizedPnl"]) + } + return {'size': 0.0, 'pnl': 0.0} + except: return {'size': 0.0, 'pnl': 0.0} + + def get_open_orders(self): + try: + return self.info.open_orders(self.vault_address or self.account.address) + except: return [] + + def cancel_order(self, coin, oid): + logging.info(f"Cancelling order {oid}...") + try: + return self.exchange.cancel(coin, oid) + except Exception as e: + logging.error(f"Error cancelling order: {e}") + + def place_limit_order(self, coin, is_buy, size, price, order_type="Alo"): + # NEW: Validate and round size using decimal precision to avoid float_to_wire errors + validated_size = validate_trade_size(size, self.sz_decimals, MIN_ORDER_VALUE_USD, price) + if validated_size == 0: + logging.error(f"Trade size {size} is too small or invalid after validation") + return None + + logging.info(f"[ORDER] PLACING {order_type.upper()}: {coin} {'BUY' if is_buy else 'SELL'} {validated_size:.8f} @ {price:.2f}") + reduce_only = is_buy + try: + # Use precise rounding for price to avoid serialization issues + limit_px = round_to_sig_figs_precise(price, 5) + + # Log actual values being sent to API for debugging + logging.info(f"[API] API Call: Size={validated_size:.8f}, Price={limit_px:.2f}, Type={order_type}") + + # Use specified TIF (Alo, Ioc, Gtc) + order_result = self.exchange.order(coin, is_buy, validated_size, limit_px, {"limit": {"tif": order_type}}, reduce_only=reduce_only) + status = order_result["status"] + if status == "ok": + response_data = order_result["response"]["data"] + if "statuses" in response_data: + status_obj = response_data["statuses"][0] + + if "error" in status_obj: + logging.error(f"Order API Error: {status_obj['error']}") + return None + + # Parse OID from nested structure + oid = None + if "resting" in status_obj: + oid = status_obj["resting"]["oid"] + elif "filled" in status_obj: + oid = status_obj["filled"]["oid"] + logging.info("Order filled immediately.") + + if oid: + logging.info(f"[OK]: OID {oid}") + return oid + else: + logging.warning(f"Order placed but OID not found in: {status_obj}") + return None + else: + logging.error(f"Order Failed: {order_result}") + return None + except Exception as e: + logging.error(f"Exception during trade: {e}") + return None + + def get_price_momentum_pct(self, current_price): + """Calculate price momentum percentage over last 5 intervals""" + if not hasattr(self, 'price_momentum_history') or len(self.price_momentum_history) < 2: + return 0.0 + + recent_prices = self.price_momentum_history[-5:] # Last 5 prices + if len(recent_prices) < 2: + return 0.0 + + # Calculate momentum as percentage change + oldest_price = recent_prices[0] + momentum_pct = (current_price - oldest_price) / oldest_price + return momentum_pct + + def get_dynamic_price_buffer(self): + """Calculate dynamic price buffer based on market conditions""" + if not MOMENTUM_ADJUSTMENT_ENABLED: + return PRICE_BUFFER_PCT + + current_price = self.last_price if self.last_price else 0 + momentum_pct = self.get_price_momentum_pct(current_price) + + base_buffer = PRICE_BUFFER_PCT + + # Adjust buffer based on momentum and position direction + if self.original_order_side == "BUY": + # For BUY orders: tolerate more upside movement + if momentum_pct > 0.005: # Strong upward momentum + dynamic_buffer = base_buffer * 2.0 + elif momentum_pct > 0.002: # Moderate upward momentum + dynamic_buffer = base_buffer * 1.5 + else: + dynamic_buffer = base_buffer + elif self.original_order_side == "SELL": + # For SELL orders: tolerate more downside movement + if momentum_pct < -0.005: # Strong downward momentum + dynamic_buffer = base_buffer * 2.0 + elif momentum_pct < -0.002: # Moderate downward momentum + dynamic_buffer = base_buffer * 1.5 + else: + dynamic_buffer = base_buffer + else: + dynamic_buffer = base_buffer + + return min(dynamic_buffer, MAX_PRICE_BUFFER_PCT) + + def update_price_momentum_history(self, current_price): + """Track price history for momentum calculation""" + if not hasattr(self, 'price_momentum_history'): + self.price_momentum_history = [] + + self.price_momentum_history.append(current_price) + if len(self.price_momentum_history) > 10: # Keep last 10 prices + self.price_momentum_history = self.price_momentum_history[-10:] + + def manage_orders(self): + """ + Enhanced order management with directional awareness and dynamic price buffering. + Returns: True if an order exists and is valid (don't trade), False if no order (can trade). + """ + open_orders = self.get_open_orders() + my_orders = [o for o in open_orders if o['coin'] == COIN_SYMBOL] + + if not my_orders: + self.active_order = None + return False + + if len(my_orders) > 1: + logging.warning("Multiple open orders found. Cancelling all for safety.") + for o in my_orders: + self.cancel_order(COIN_SYMBOL, o['oid']) + self.active_order = None + return False + + order = my_orders[0] + oid = order['oid'] + order_price = float(order['limitPx']) + + current_mid = self.get_order_book_mid(COIN_SYMBOL) + pct_diff = abs(current_mid - order_price) / order_price + + # Get dynamic price buffer based on market conditions + dynamic_buffer = self.get_dynamic_price_buffer() + + # Apply dynamic buffer with enhanced logic + dynamic_buffer = self.get_dynamic_price_buffer() + enhanced_pct_diff = pct_diff * (1 + abs(momentum_pct) * 0.5) if hasattr(self, 'get_price_momentum_pct') else pct_diff + + if enhanced_pct_diff > dynamic_buffer: + # Update order side tracking before cancelling + if hasattr(self, 'active_order'): + order_side = "BUY" if my_orders[0]['side'].lower() == 'buy' else "SELL" + if not hasattr(self, 'original_order_side') or self.original_order_side != order_side: + self.original_order_side = order_side + logging.info(f"New order direction tracked: {self.original_order_side}") + + logging.info(f"Price moved {pct_diff*100:.3f}% > {dynamic_buffer*100:.3f}% (Dynamic: {self.get_dynamic_price_buffer()*100:.3f}%). Cancelling/Replacing order {oid}.") + self.cancel_order(COIN_SYMBOL, oid) + self.active_order = None + return False + else: + logging.info(f"Pending Order {oid} @ {order_price:.2f} is within range ({pct_diff*100:.3f}%). Dynamic Buffer: {self.get_dynamic_price_buffer()*100:.3f}% Waiting.") + return True + + def close_all_positions(self, force_taker=False): + logging.info("Closing all positions (Market Order)...") + try: + # Cancel open orders first + open_orders = self.get_open_orders() + for o in open_orders: + if o['coin'] == COIN_SYMBOL: + self.cancel_order(COIN_SYMBOL, o['oid']) + + price = self.get_market_price(COIN_SYMBOL) + pos_data = self.get_current_position(COIN_SYMBOL) + current_pos = pos_data['size'] + + if current_pos == 0: return + + is_buy_to_close = current_pos < 0 + final_size = round_to_sz_decimals(abs(current_pos), self.sz_decimals) + if final_size == 0: return + + # --- ATTEMPT MAKER CLOSE (Alo) --- + if not force_taker: + try: + book_levels = self.get_order_book_levels(COIN_SYMBOL) + TICK_SIZE = 0.1 + + if is_buy_to_close: # We are short, need to buy to close + maker_price = book_levels['bid'] - TICK_SIZE + else: # We are long, need to sell to close + maker_price = book_levels['ask'] + TICK_SIZE + + logging.info(f"Attempting MAKER CLOSE (Alo): {COIN_SYMBOL} {'BUY' if is_buy_to_close else 'SELL'} {final_size} @ {maker_price:.2f}") + order_result = self.exchange.order(COIN_SYMBOL, is_buy_to_close, final_size, round_to_sig_figs(maker_price, 5), {"limit": {"tif": "Alo"}}, reduce_only=True) + + status = order_result["status"] + if status == "ok": + response_data = order_result["response"]["data"] + if "statuses" in response_data and "resting" in response_data["statuses"][0]: + logging.info(f"✅ MAKER CLOSE Order Placed (Alo). OID: {response_data['statuses'][0]['resting']['oid']}") + return + elif "statuses" in response_data and "filled" in response_data["statuses"][0]: + logging.info(f"✅ MAKER CLOSE Order Filled (Alo). OID: {response_data['statuses'][0]['filled']['oid']}") + return + else: + # Fallback if Alo didn't rest or fill immediately in an expected way + logging.warning(f"Alo order result unclear: {order_result}. Falling back to Market Close.") + + elif status == "error": + if "Post only order would have immediately matched" in order_result["response"]["data"]["statuses"][0].get("error", ""): + logging.warning("Alo order would have immediately matched. Falling back to Market Close for guaranteed fill.") + else: + logging.error(f"Alo order failed with unknown error: {order_result}. Falling back to Market Close.") + else: + logging.warning(f"Alo order failed with status {status}. Falling back to Market Close.") + + except Exception as e: + logging.error(f"Exception during Alo close attempt: {e}. Falling back to Market Close.", exc_info=True) + + # --- FALLBACK TO MARKET CLOSE (Ioc) for guaranteed fill --- + logging.info(f"Falling back to MARKET CLOSE (Ioc): {COIN_SYMBOL} {'BUY' if is_buy_to_close else 'SELL'} {final_size} @ {price:.2f} (guaranteed)") + self.exchange.order(COIN_SYMBOL, is_buy_to_close, final_size, round_to_sig_figs(price * (1.05 if is_buy_to_close else 0.95), 5), {"limit": {"tif": "Ioc"}}, reduce_only=True) + self.active_position_id = None + logging.info("✅ MARKET CLOSE Order Placed (Ioc).") + except Exception as e: + logging.error(f"Error closing positions: {e}", exc_info=True) + + def run(self): + logging.info(f"Starting Scalper Monitor Loop. Interval: {CHECK_INTERVAL}s") + + while True: + try: + active_pos = get_active_automatic_position() + + # 1. Global Disable / No Position Check + if not active_pos or not active_pos.get('hedge_enabled', True): + if self.strategy is not None: + logging.info("Hedge Disabled or Position Missing. Closing.") + self.close_all_positions(force_taker=True) + self.strategy = None + time.sleep(CHECK_INTERVAL) + continue + + # 2. Explicit CLOSING Status Check + if active_pos.get('status') == 'CLOSING': + logging.info(f"[ALERT] {active_pos['token_id']} is CLOSING. Forcing hedge close.") + self.close_all_positions(force_taker=True) + self.strategy = None + time.sleep(CHECK_INTERVAL) + continue + + if self.strategy is None or self.active_position_id != active_pos['token_id']: + logging.info(f"New position {active_pos['token_id']} detected or strategy not initialized. Initializing strategy.") + self._init_strategy(active_pos) + if self.strategy is None: + time.sleep(CHECK_INTERVAL) + continue + + if self.strategy is None: continue + + # --- ORDER MANAGEMENT --- + if self.manage_orders(): + time.sleep(CHECK_INTERVAL) + continue + + # 2. Market Data + book_levels = self.get_order_book_levels(COIN_SYMBOL) + + if book_levels is None: + # logging.warning("Order book data unavailable. Skipping cycle.") + time.sleep(0.1) # Short sleep before retry + continue + + price = book_levels['mid'] + + funding_rate = self.get_funding_rate(COIN_SYMBOL) + pos_data = self.get_current_position(COIN_SYMBOL) + current_pos_size = pos_data['size'] + current_pnl = pos_data['pnl'] + + # REMOVED: Uniswap spread monitoring for cleaner delta-zero hedging + # Benefits: + # - No external RPC dependency + # - Eliminated spread text overhead + # - Focused on core hedging decisions + # - Cleaner logs with essential information only + spread_text = "" # Empty since spread monitoring removed + + # 3. Calculate Logic + calc = self.strategy.calculate_rebalance(price, current_pos_size) + diff_abs = abs(calc['diff']) + + # Log ETH price with delta calculation for debugging + eth_price = self.get_market_price(COIN_SYMBOL) + price_delta = eth_price - (self.last_price if self.last_price else 0) + + # --- LOGGING OVERHEDGE --- + oh_text = "" + if calc.get('overhedge_pct', 0) > 0: + oh_text = f" | [OH] OH: +{calc['overhedge_pct']*100:.2f}%" + + # 4. Dynamic Threshold Calculation + sqrt_Pa = math.sqrt(self.strategy.low_range) + sqrt_Pb = math.sqrt(self.strategy.high_range) + max_potential_eth = self.strategy.L * ((1/sqrt_Pa) - (1/sqrt_Pb)) + + # Use MIN_THRESHOLD_ETH from config + rebalance_threshold = max(MIN_THRESHOLD_ETH, max_potential_eth * 0.05) + + # 5. Determine Hedge Zone + clp_low_range = self.strategy.low_range + clp_high_range = self.strategy.high_range + range_width = clp_high_range - clp_low_range + + # Calculate Prices for Zones + # If config > 9, set to None (Disabled Zone) + zone_bottom_limit_price = (clp_low_range + (range_width * ZONE_BOTTOM_HEDGE_LIMIT)) if ZONE_BOTTOM_HEDGE_LIMIT <= 9 else None + zone_close_bottom_price = (clp_low_range + (range_width * ZONE_CLOSE_START)) if ZONE_CLOSE_START <= 9 else None + zone_close_top_price = (clp_low_range + (range_width * ZONE_CLOSE_END)) if ZONE_CLOSE_END <= 9 else None + zone_top_start_price = (clp_low_range + (range_width * ZONE_TOP_HEDGE_START)) if ZONE_TOP_HEDGE_START <= 9 else None + + # Update JSON with zone prices if they are None (initially set by uniswap_manager.py) + if active_pos.get('zone_bottom_limit_price') is None: + update_position_zones_in_json(active_pos['token_id'], { + 'zone_top_start_price': round(zone_top_start_price, 2) if zone_top_start_price else None, + 'zone_close_top_price': round(zone_close_top_price, 2) if zone_close_top_price else None, + 'zone_close_bottom_price': round(zone_close_bottom_price, 2) if zone_close_bottom_price else None, + 'zone_bottom_limit_price': round(zone_bottom_limit_price, 2) if zone_bottom_limit_price else None + }) + + # --- DELTA-ZERO HEDGING: Active throughout CLP range --- + # Delta-zero hedging is now active across the entire CLP range + in_hedge_zone = (price >= clp_low_range and price <= clp_high_range) + + # Close zone check (for emergency shutdown) + in_close_zone = False + if zone_close_bottom_price is not None and zone_close_top_price is not None: + in_close_zone = (price >= zone_close_bottom_price and price <= zone_close_top_price) + + # --- DELTA-ZERO HEDGING EXECUTION LOGIC --- + if in_close_zone: + logging.info(f"ZONE: CLOSE ({price:.2f} in {zone_close_bottom_price:.2f}-{zone_close_top_price:.2f}). PNL: ${current_pnl:.2f}. Closing all hedge positions.") + self.close_all_positions(force_taker=True) + time.sleep(CHECK_INTERVAL) + continue + + elif in_hedge_zone: + # DELTA-ZERO HEDGING: Active throughout CLP range + pct_position = (price - clp_low_range) / range_width + + # Dynamic threshold adjustment for volatility protection + dynamic_threshold = rebalance_threshold + if hasattr(self, 'last_price') and self.last_price: + price_change_pct = abs(price - self.last_price) / self.last_price + if price_change_pct > 0.003: # >0.3% change = high volatility (adjusted for multi-timeframe) + dynamic_threshold *= DYNAMIC_THRESHOLD_MULTIPLIER + volatility_text = f" | [VOL] HIGH VOLATILITY ({price_change_pct*100:.2f}%)" + else: + volatility_text = "" + else: + volatility_text = "" + + # Calculate velocity first, then update price history (Multi-timeframe approach) + if (hasattr(self, 'last_price_for_velocity') and + self.last_price_for_velocity and + hasattr(self, 'price_history') and + len(self.price_history) >= 2): + + # Option 3B: Multi-Timeframe Velocity Calculation + # 1-second velocity (instantaneous) + velocity_1s = (price - self.last_price_for_velocity) / self.last_price_for_velocity + + # 5-second average velocity (smoother) + velocity_5s = 0.0 + if len(self.price_history) >= 5: + price_5s_ago = self.price_history[-5] + velocity_5s = (price - price_5s_ago) / price_5s_ago / 5 # Per second average + + # Choose velocity: Use 5s average for normal conditions, 1s for extreme moves + if abs(velocity_1s) > 0.002: # If 1s move is extreme (>0.2%), use it + price_velocity = velocity_1s + else: # Otherwise use 5s average for smoother signals + price_velocity = velocity_5s + + # Add validation to prevent extreme readings + if abs(price_velocity) > 0.5: # Cap at 50% change per interval + price_velocity = 0.5 if price_velocity > 0 else -0.5 + + # Update velocity history for tracking + if not hasattr(self, 'velocity_history'): + self.velocity_history = [] + self.velocity_history.append(velocity_1s) + if len(self.velocity_history) > 10: # Keep last 10 velocity readings + self.velocity_history = self.velocity_history[-10:] + else: + price_velocity = 0.0 + velocity_1s = 0.0 + velocity_5s = 0.0 + + # Update price history for velocity tracking + if hasattr(self, 'price_history'): + self.price_history.append(price) + # Keep only last 10 prices for velocity calculation (increased from 5) + if len(self.price_history) > 10: + self.price_history = self.price_history[-10:] + + # --- COMPREHENSIVE EDGE PROTECTION LOGIC --- + can_trade = True + override_text = "" + cooldown_text = "" + + # --- MULTI-LAYER OVERRIDE CONDITIONS --- + bypass_cooldown = False + override_reason = "" + + # 1. CRITICAL: Already outside CLP range (highest priority) + if price < clp_low_range or price > clp_high_range: + bypass_cooldown = True + override_reason = "OUTSIDE RANGE (CRITICAL)" + if price < clp_low_range: + override_reason += " (BELOW)" + else: + override_reason += " (ABOVE)" + + # 2. URGENT: Within edge proximity AND position still open + elif (hasattr(active_pos, 'status') and + active_pos.get('status') == 'OPEN'): + + # Use position-aware edge proximity + position_edge_proximity = POSITION_OPEN_EDGE_PROXIMITY_PCT + + distance_from_bottom = price - clp_low_range + distance_from_top = clp_high_range - price + range_width = clp_high_range - clp_low_range + + edge_distance = range_width * position_edge_proximity + is_near_bottom = distance_from_bottom <= edge_distance + is_near_top = distance_from_top <= edge_distance + + if is_near_bottom or is_near_top: + bypass_cooldown = True + override_reason = f"EDGE PROXIMITY ({position_edge_proximity*100:.1f}% edge)" + if is_near_bottom: + override_reason += f" ({distance_from_bottom:.2f} from bottom)" + else: + override_reason += f" ({distance_from_top:.2f} from top)" + + # 3. EMERGENCY: High velocity toward range edge (using smoothed velocity) + elif abs(price_velocity) > VELOCITY_THRESHOLD_PCT: + # Only if moving toward edge + moving_toward_bottom = price_velocity < 0 and price < (clp_low_range * 1.05) + moving_toward_top = price_velocity > 0 and price > (clp_high_range * 0.95) + + if moving_toward_bottom or moving_toward_top: + bypass_cooldown = True + # Improved logging with actual price movement context + if self.last_price_for_velocity: + actual_price_move = price - self.last_price_for_velocity + override_reason = f"HIGH VELOCITY ({price_velocity*100:.2f}%/interval, ${actual_price_move:+.2f})" + else: + override_reason = f"HIGH VELOCITY ({price_velocity*100:.2f}%/interval)" + + # 4. LARGE GAP: Target hedge is significantly different + elif abs(calc['diff']) > (dynamic_threshold * LARGE_HEDGE_MULTIPLIER): + bypass_cooldown = True + override_reason = f"LARGE HEDGE NEEDED ({abs(calc['diff']):.4f} vs {dynamic_threshold:.4f})" + + # Apply cooldown override logic + if bypass_cooldown: + can_trade = True + cooldown_text = f" | 🚨 OVERRIDE: {override_reason}" + self.last_price_for_velocity = price + logging.info(f"[WARN] COOLDOWN BYPASSED: {override_reason}") + elif hasattr(self, 'last_trade_time'): + time_since_last = time.time() - self.last_trade_time + if time_since_last < MIN_TIME_BETWEEN_TRADES: + can_trade = False + cooldown_text = f" | [WAIT] COOLDOWN ({MIN_TIME_BETWEEN_TRADES - time_since_last:.0f}s)" + + # Update velocity and momentum tracking + self.last_price_for_velocity = price + self.update_price_momentum_history(price) + + if diff_abs > dynamic_threshold and can_trade: + # Use precise decimal rounding to avoid float_to_wire errors + trade_size = round_to_sz_decimals_precise(diff_abs, self.sz_decimals) + + # Safety cap: Prevent position from exceeding maximum hedge multiplier + max_allowed_size = calc['target_short'] * MAX_HEDGE_MULTIPLIER + if abs(calc['current_short']) + trade_size > max_allowed_size: + trade_size = max_allowed_size - abs(calc['current_short']) + # Use precise decimal rounding to avoid float_to_wire errors + trade_size = round_to_sz_decimals_precise(trade_size, self.sz_decimals) + safety_text = f" | [SAFE] SIZE CAP ({max_allowed_size:.4f})" + else: + safety_text = "" + + min_trade_size = MIN_ORDER_VALUE_USD / price + + if trade_size < min_trade_size: + logger.info(f"[DELTA] DELTA-ZERO: Idle. Trade size {trade_size:.4f} < Min {min_trade_size:.4f} (${MIN_ORDER_VALUE_USD:.2f}). Pos: {pct_position*100:.1f}% | PNL: ${current_pnl:.2f}{spread_text}{oh_text}{volatility_text} | ETH: ${eth_price:.2f} (Δ{price_delta:+.2f})") + elif trade_size > 0.0001: # Minimum meaningful trade + # Determine Order Type and Urgency + order_type = "Alo" # Default to Maker + is_initial_entry = abs(calc['current_short']) < (trade_size * 0.1) # Less than 10% of target is open + + if bypass_cooldown or is_initial_entry: + order_type = "Ioc" # Taker for urgency or start + urgency_reason = "URGENT" if bypass_cooldown else "INITIAL" + logging.info(f"[TRIG] DELTA-ZERO TRIGGERED ({urgency_reason}): {diff_abs:.4f} >= {dynamic_threshold:.4f}. Pos: {pct_position*100:.1f}% | PNL: ${current_pnl:.2f}{spread_text}{oh_text}{volatility_text}{safety_text}") + else: + logging.info(f"[TRIG] DELTA-ZERO TRIGGERED (PASSIVE): {diff_abs:.4f} >= {dynamic_threshold:.4f}. Pos: {pct_position*100:.1f}% | PNL: ${current_pnl:.2f}{spread_text}{oh_text}{volatility_text}{safety_text}") + + # Execute + TICK_SIZE = 0.2 + is_buy = (calc['action'] == "BUY") + + if order_type == "Ioc": + # Taker Price: Cross the spread + slippage tolerance + # Buy at Ask + buffer, Sell at Bid - buffer + # 0.1% slippage tolerance for taker orders + if is_buy: + exec_price = book_levels['ask'] * 1.001 + else: + exec_price = book_levels['bid'] * 0.999 + else: + # Maker Price: Passive offset + if is_buy: + exec_price = book_levels['bid'] - TICK_SIZE + else: + exec_price = book_levels['ask'] + TICK_SIZE + + order_id = self.place_limit_order(COIN_SYMBOL, is_buy, trade_size, exec_price, order_type=order_type) + if order_id: + self.last_trade_time = time.time() + self.track_fills_and_pnl(force=True) + else: + logging.info(f"[DELTA] DELTA-ZERO: Trade size rounds to 0. Pos: {pct_position*100:.1f}% | PNL: ${current_pnl:.2f}{spread_text}{oh_text}{volatility_text}{cooldown_text}") + else: + if not can_trade: + reason = f"Cooldown ({MIN_TIME_BETWEEN_TRADES}s)" + else: + reason = f"Threshold ({diff_abs:.4f} < {dynamic_threshold:.4f})" + + # Add velocity context for debugging (show multi-timeframe) + if abs(price_velocity) > 0.001: + velocity_text = f" | Vel: {price_velocity*100:+.2f}% (1s:{velocity_1s*100:+.2f}%,5s:{velocity_5s*100:+.2f}%)" + else: + velocity_text = "" + logger.info(f"[DELTA] DELTA-ZERO: Idle. {reason}. Pos: {pct_position*100:.1f}% | PNL: ${current_pnl:.2f}{spread_text}{oh_text}{volatility_text}{velocity_text}{cooldown_text}") + + else: + # OUTSIDE CLP RANGE: + # 1. If ABOVE Range: We are 100% USDC. CLOSE HEDGE. + # 2. If BELOW Range: We are 100% ETH. HOLD HEDGE (Don't Close). + + if price > clp_high_range: + zone_text = f"ABOVE range ({price:.2f} > {clp_high_range:.2f})" + logging.info(f"[OUT] OUTSIDE CLP RANGE: {zone_text}. Closing hedge (100% USDC). PNL: ${current_pnl:.2f}") + self.close_all_positions(force_taker=True) + elif price < clp_low_range: + zone_text = f"BELOW range ({price:.2f} < {clp_low_range:.2f})" + # Log periodically (every ~10s) to avoid spam + if int(time.time()) % 20 == 0: + logger.info(f"[HOLD] OUTSIDE CLP RANGE: {zone_text}. Holding hedge (100% ETH). Waiting for Manager signal.") + + time.sleep(CHECK_INTERVAL) + continue + + # Update PnL/Fees periodically + self.track_fills_and_pnl() + + time.sleep(CHECK_INTERVAL) + + except KeyboardInterrupt: + logging.info("Stopping Hedger...") + self.close_all_positions() + break + except Exception as e: + logging.error(f"Loop Error: {e}", exc_info=True) + time.sleep(10) + +if __name__ == "__main__": + hedger = ScalperHedger() + hedger.run() \ No newline at end of file