How Auto-Hedging Works: Technical Deep-Dive

This page provides a comprehensive technical explanation of the auto-hedge system, including NET position monitoring, trigger logic, cascade prevention, and hedge management.

🧮 NET Position Monitoring

Why NET Position?

Vortex DCA runs independent long and short grids simultaneously. Auto-hedge monitors the NET position (long qty - short qty) to determine which side needs protection.

Long Position:  12,000 DOGE @ $0.16800 avg
Short Position: 5,000 DOGE @ $0.17200 avg
NET Position:   7,000 LONG (12,000 - 5,000)

Separate Long/Short Monitoring

Auto-hedge monitors each side independently: LONG Side:

long_qty = 12,000
short_qty = 5,000
net_qty = long_qty - short_qty = 7,000 LONG

if net_qty > 0:  # Net LONG position exists
    # Monitor LONG side for drawdown and liquidation
    drawdown_pct = (entry_price - current_price) / entry_price
    liq_distance_pct = (current_price - long_liq_price) / current_price

SHORT Side:

long_qty = 5,000
short_qty = 12,000
net_qty = long_qty - short_qty = -7,000 SHORT

if net_qty < 0:  # Net SHORT position exists
    # Monitor SHORT side for drawdown and liquidation
    drawdown_pct = (current_price - entry_price) / entry_price
    liq_distance_pct = (short_liq_price - current_price) / current_price

This approach ensures hedges are only placed on the side that needs protection, avoiding unnecessary trades.

🎯 Trigger Conditions

Auto-hedge triggers when EITHER condition is met:

Condition A: Drawdown Threshold

Formula:

LONG:  drawdown = (entry_price - current_price) / entry_price
SHORT: drawdown = (current_price - entry_price) / entry_price

Trigger when: drawdown >= autohedge_on_drawdown_pct

Example (LONG):

Entry Price:  $0.17000
Current Price: $0.16320
Drawdown: (0.17000 - 0.16320) / 0.17000 = 0.04 (4.0%)

Config threshold: 0.04 (4%)
Result: 4.0% >= 4.0% ✅ TRIGGER!

Example (SHORT):

Entry Price:  $0.16500
Current Price: $0.17160
Drawdown: (0.17160 - 0.16500) / 0.16500 = 0.04 (4.0%)

Config threshold: 0.04 (4%)
Result: 4.0% >= 4.0% ✅ TRIGGER!

Condition B: Liquidation Distance

Formula:

LONG:  liq_distance = (current_price - liq_price) / current_price
SHORT: liq_distance = (liq_price - current_price) / current_price

Trigger when: liq_distance <= autohedge_on_liquidation_distance_pct

Example (LONG):

Current Price:     $0.17200
Liquidation Price: $0.15500
Liq Distance: (0.17200 - 0.15500) / 0.17200 = 0.0988 (9.88%)

Config threshold: 0.10 (10%)
Result: 9.88% <= 10% ✅ TRIGGER!

Example (SHORT):

Current Price:     $0.16500
Liquidation Price: $0.18400
Liq Distance: (0.18400 - 0.16500) / 0.16500 = 0.1151 (11.51%)

Config threshold: 0.10 (10%)
Result: 11.51% <= 10% ❌ No trigger

Critical Override

Special Case: When liquidation distance drops below 3%, hedge triggers immediately regardless of anti-cascade logic:

is_critical = liq_distance_pct < 0.03

if is_critical:
    # Force hedge NOW - ignore anti-cascade checks
    place_hedge_immediately()

Example:

Liquidation Distance: 2.5%
Anti-cascade: Last hedge was 10 seconds ago
Result: 🔴 CRITICAL! Place hedge anyway (override anti-cascade)

Critical override ensures emergency protection when liquidation is imminent!

🛡️ Anti-Cascade Protection

The implementation includes comprehensive cascade prevention to avoid repeated hedging of the same drawdown event.

The Cascade Problem

Without Anti-Cascade:

10,000 LONG → Trigger → Hedge 5,000 SHORT
5,000 NET → Trigger again → Hedge 2,500 SHORT
2,500 NET → Trigger again → Hedge 1,250 SHORT
...
Result: ❌ Cascades to 99%+ hedged!

With Anti-Cascade:

10,000 LONG → Trigger → Hedge 5,000 SHORT
5,000 NET → Check anti-cascade → ⏸️ SKIP (already hedged)
Result: ✅ Stays at 50% hedge ratio as configured

Safety Mechanism 1: Original Position Tracking

The bot tracks the original position size when a hedge sequence starts:

# First hedge trigger
original_qty = 10,000  # Store original position
hedge_qty = 10,000 * 0.5 = 5,000

# Second trigger (before position changes significantly)
current_net_qty = 5,000  # After first hedge
opposite_qty = 5,000     # Current hedge size

# Calculate hedge ratio against ORIGINAL, not current
hedge_ratio = opposite_qty / original_qty = 5,000 / 10,000 = 0.5 (50%)
target_ratio = 0.5 (from config)

if hedge_ratio >= target_ratio:
    # Already at target - SKIP
    return

Key Point: All hedge ratio calculations use the original position size, not the current NET position.

Safety Mechanism 2: Hedge Ratio Enforcement

Before placing a new hedge, the system checks if the target ratio is already achieved:

def check_hedge_ratio(original_qty, opposite_qty, target_ratio):
    current_ratio = opposite_qty / original_qty
    tolerance = 0.05  # 5% tolerance

    if current_ratio >= target_ratio * (1 - tolerance):
        # Already hedged enough
        return "SKIP"
    else:
        # More hedging needed
        remaining = (original_qty * target_ratio) - opposite_qty
        return remaining

Example:

Original position: 10,000 LONG
Target hedge ratio: 0.5 (50%)
Current opposite: 4,800 SHORT

Current ratio: 4,800 / 10,000 = 0.48 (48%)
Target with tolerance: 0.5 * 0.95 = 0.475 (47.5%)

Result: 48% >= 47.5% ✅ SKIP (close enough to target)

Safety Mechanism 3: Price/Quantity Movement Checks

Won’t re-hedge unless price moved 2%+ OR position changed 20%+ since last hedge:

last_hedge = {
    'price': 0.17000,
    'qty': 10000,
    'timestamp': <last_hedge_time>
}

current_price = 0.17034
current_qty = 10000

# Calculate changes
price_move_pct = abs(current_price - last_hedge['price']) / last_hedge['price']
# = abs(0.17034 - 0.17000) / 0.17000 = 0.002 (0.2%)

qty_change_pct = abs(current_qty - last_hedge['qty']) / last_hedge['qty']
# = abs(10000 - 10000) / 10000 = 0.0 (0%)

if price_move_pct < 0.02 and qty_change_pct < 0.20:
    # Not enough change - SKIP
    return

Example Scenarios: Scenario 1: Price hasn’t moved much

Last hedge: $0.17000
Current: $0.17034 (0.2% move)
Result: ⏸️ SKIP (< 2% threshold)

Scenario 2: Price moved significantly

Last hedge: $0.17000
Current: $0.16660 (2.0% move)
Result: ✅ ALLOW new hedge

Scenario 3: Position grew significantly

Last hedge: 10,000 qty
Current: 12,500 qty (25% increase)
Result: ✅ ALLOW new hedge

Safety Mechanism 4: Original Quantity Reset

The original quantity resets when position changes by 50%+:

if qty_change_pct >= 0.50:
    # Position changed significantly - start new hedge sequence
    original_qty = current_qty
    last_hedge_info = None

Example:

Original tracked: 10,000 LONG
Grid fills more: 16,000 LONG (60% increase)
Result: Reset original to 16,000, start fresh hedge sequence

🎬 Complete Hedge Cycle Example

Let’s walk through a complete auto-hedge cycle:

Initial State

Price: $0.17000
Long: 0
Short: 0
Grid: Active

Step 1: Grid Fills (Long Side)

Price drops to $0.16500
Long fills accumulate:
  - 2,000 @ $0.16900
  - 3,000 @ $0.16700
  - 5,000 @ $0.16500

Total: 10,000 LONG @ $0.16700 avg
NET: 10,000 LONG

Step 2: Further Price Drop - Drawdown Trigger

Price: $0.16032
Drawdown: (0.16700 - 0.16032) / 0.16700 = 4.0%

Config threshold: 4.0%
Result: TRIGGER! 🛡️

Log:
[DOGEUSDT] LONG 🛡️ AUTO-HEDGE TRIGGER: DRAWDOWN
   Position: 10000.0000 @ $0.16700
   Current: $0.16032 | Drawdown: 4.00%

Step 3: Calculate Hedge Size

original_qty = 10,000
target_ratio = 0.5
current_opposite_qty = 0

hedge_needed = original_qty * target_ratio - current_opposite_qty
             = 10,000 * 0.5 - 0
             = 5,000

Log:
[DOGEUSDT] LONG 🆕 Starting new hedge sequence - original qty: 10000.0000
[DOGEUSDT] LONG 📊 Hedge ratio: 0.0% (target: 50%)

Step 4: Place Hedge Order

place_order(
    symbol='DOGEUSDT',
    side='sell',
    amount=5000,
    price=None,  # MARKET order
    order_type='market',
    reduce_only=False
)

Log:
[DOGEUSDT] LONG 🛡️ PLACING HEDGE: sell 5000.0000 @ $0.16028
[DOGEUSDT] LONG ✅ HEDGE PLACED: Order #1234567890

Step 5: Hedge Fills

Hedge execution: SELL 5,000 @ $0.16025

Position state:
Long:  10,000 @ $0.16700
Short: 5,000 @ $0.16025
NET:   5,000 LONG

Step 6: Place Hedge Take Profit

hedge_entry = 0.16025
tp_target = 0.002  # 0.2%
tp_price = hedge_entry * (1 - tp_target) = 0.16025 * 0.998 = 0.15993

place_order(
    symbol='DOGEUSDT',
    side='buy',
    amount=5000,
    price=0.15993,
    order_type='limit',
    reduce_only=True,
    position_side='short'
)

Log:
[DOGEUSDT] SHORT HEDGE TP: Placing buy 5000.0000 @ $0.15993
[DOGEUSDT] SHORT HEDGE ✅ TP PLACED: Order #1234567891

Step 7: Trailing Stop Activates

Price drops to $0.15800 → Hedge profit: 1.4%

Since 1.4% greater than 0.2% TP target:
  Trailing stop activates
  Best price tracked: $0.15800

Trailing distance: 0.2%
Trigger price: $0.15800 * 1.002 = $0.15832

Log:
[DOGEUSDT] SHORT 🎯 TRAILING ACTIVATED
   Best price: $0.15800 | Trail trigger: $0.15832

Step 8: Trailing Stop Triggers

Price retraces to $0.15835 (0.22% from best)

Cancel limit TP order
Place market order to close hedge:

place_order(
    symbol='DOGEUSDT',
    side='buy',
    amount=5000,
    price=None,
    order_type='market',
    reduce_only=True,
    position_side='short'
)

Hedge closes @ $0.15835
Profit: ($0.16025 - $0.15835) * 5,000 = $95.00

Log:
[DOGEUSDT] SHORT 🎯 TRAILING STOP HIT
   Entry: $0.16025 | Exit: $0.15835 | Profit: $95.00

Step 9: Position After Hedge Close

Long:  10,000 @ $0.16700
Short: 0
NET:   10,000 LONG

Grid: Still active on both sides
Hedge sequence: Completed
Original qty tracking: Reset (ready for next cycle)

Step 10: Grid Continues Operating

Price recovers to $0.17000
Long TPs start executing:
  - 5,000 @ $0.16867 (1% TP)
  - 3,000 @ $0.16867
  - 2,000 @ $0.16867

Total grid profit: $267.00
Total hedge profit: $95.00
Combined profit: $362.00

⚙️ Order Types Used

Hedge Placement: MARKET Order

{
    "symbol": "DOGEUSDT",
    "side": "sell",  # Opposite of NET position
    "order_type": "market",  # ← Ensures immediate fill
    "amount": 5000,
    "price": None,
    "reduce_only": False,  # Opens new position
    "position_side": "short"  # Explicit side for hedge mode
}

Why MARKET:

Guarantees immediate execution
Protects against further drawdown
No risk of order not filling

Hedge Take Profit: LIMIT Order (Initial)

{
    "symbol": "DOGEUSDT",
    "side": "buy",  # Closes hedge
    "order_type": "limit",
    "amount": 5000,
    "price": 0.15993,  # 0.2% profit target
    "reduce_only": True,  # ← Only closes existing hedge
    "position_side": "short"
}

Why LIMIT:

Sets specific profit target
Remains active until hit or replaced by trailing stop

Trailing Stop: MARKET Order (When Triggered)

{
    "symbol": "DOGEUSDT",
    "side": "buy",
    "order_type": "market",  # ← Immediate close
    "amount": 5000,
    "price": None,
    "reduce_only": True,
    "position_side": "short"
}

Why MARKET:

Locks in profit immediately
Prevents profit giveback from slippage

🔧 Exchange-Specific Implementation

BloFin Parameter Conversion

The strategy uses standardized parameters, but BloFin requires specific formatting:

# Strategy calls:
place_order(
    reduce_only=True,
    position_side='short'
)

# BloFin exchange converts to:
params = {
    'reduceOnly': 'true',  # ← String, not boolean!
    'positionSide': 'short',
    'leverage': '20'
}

exchange.create_order(
    symbol='DOGEUSDT',
    type='market',
    side='buy',
    amount=5000,
    price=None,
    params=params
)

Key Differences:

reduce_only (bool) → reduceOnly (string "true"/"false")
Position side explicitly specified in params
Leverage set per order

The exchange adapter handles all parameter conversions automatically - you don’t need to worry about exchange-specific formatting!

📊 State Tracking

Auto-hedge maintains several state variables:

# Original position tracking (per symbol, per side)
self.last_hedge_info = {
    'DOGEUSDT_long': {
        'original_qty': 10000,
        'price': 0.17000,
        'qty': 10000,
        'timestamp': <datetime>
    },
    'DOGEUSDT_short': None
}

# Hedge TP order IDs (for cancellation)
self.hedge_tp_orders = {
    'DOGEUSDT_short': '1234567891'
}

# Best prices for trailing (per symbol, per side)
self.hedge_best_prices = {
    'DOGEUSDT_short': 0.15800
}

# Trailing activation status
self.hedge_trailing_active = {
    'DOGEUSDT_short': True
}

🔁 Main Loop Integration

Auto-hedge runs in the main strategy loop:

def run(self):
    while True:
        # ... (refresh grids, manage TPs, etc.)

        # AUTO-HEDGE OR LIQUIDATION SAFEGUARD
        if self.autohedge_enabled:
            # Check if hedge should trigger
            self._check_auto_hedge(symbol, positions, current_price)

            # Monitor hedge trailing stops
            self._monitor_hedge_trailing_stop(symbol, positions, current_price)
        else:
            # Traditional liquidation safeguard
            self._liquidation_safeguard_check(symbol, positions, current_price)

        # ... (continue grid operations)
        time.sleep(3)  # Check every 3 seconds

Timing:

Hedge checks run every 3 seconds (same as TP refresh)
Ensures quick response to drawdowns
Low overhead (simple calculations)

📈 Performance Characteristics

Computational Overhead

Per Check (every 3 seconds):

Calculate NET position: O(1)
Calculate drawdown: O(1)
Calculate liq distance: O(1)
Anti-cascade checks: O(1)

Total: Minimal CPU impact (less than 0.01% per symbol)

Memory Usage

Per Symbol:

Hedge state: ~500 bytes
Tracking info: ~300 bytes

Total: less than 1 KB per symbol (negligible)

Network Calls

Normal Operation: 0 API calls (monitoring only) When Hedge Triggers:

1 call: Place hedge market order
1 call: Place hedge TP limit order

When Trailing Triggers:

1 call: Cancel TP order
1 call: Place market close order

Total: 2-4 API calls per hedge cycle (infrequent)

🧪 Testing & Validation

What to Monitor

In Logs:

✅ Hedge triggers at correct thresholds
✅ Anti-cascade logic prevents repeated hedges
✅ Hedge ratios match configuration
✅ Trailing stops activate and trigger correctly
✅ Orders execute without errors

In Exchange:

✅ Hedge positions open on correct side
✅ Position sizes match expected amounts
✅ TP orders placed at correct prices
✅ Reduce-only flag working properly

Validation Checklist

Auto-Hedging Overview - Feature introduction
Configuration Guide - Parameter reference
Risk Management Best Practices - Safety guidelines

Now you understand exactly how auto-hedging works under the hood! 🔧

Get Started

Features

Bot Configuration

Risk Management

Exchange Setup

​How Auto-Hedging Works: Technical Deep-Dive

​🧮 NET Position Monitoring

​Why NET Position?

​Separate Long/Short Monitoring

​🎯 Trigger Conditions

​Condition A: Drawdown Threshold

​Condition B: Liquidation Distance

​Critical Override

​🛡️ Anti-Cascade Protection

​The Cascade Problem

​Safety Mechanism 1: Original Position Tracking

​Safety Mechanism 2: Hedge Ratio Enforcement

​Safety Mechanism 3: Price/Quantity Movement Checks

​Safety Mechanism 4: Original Quantity Reset

​🎬 Complete Hedge Cycle Example

​Initial State

​Step 1: Grid Fills (Long Side)

​Step 2: Further Price Drop - Drawdown Trigger

​Step 3: Calculate Hedge Size

​Step 4: Place Hedge Order

​Step 5: Hedge Fills

​Step 6: Place Hedge Take Profit

​Step 7: Trailing Stop Activates

​Step 8: Trailing Stop Triggers

​Step 9: Position After Hedge Close

​Step 10: Grid Continues Operating

​⚙️ Order Types Used

​Hedge Placement: MARKET Order

​Hedge Take Profit: LIMIT Order (Initial)

​Trailing Stop: MARKET Order (When Triggered)

​🔧 Exchange-Specific Implementation

​BloFin Parameter Conversion

​📊 State Tracking

​🔁 Main Loop Integration

​📈 Performance Characteristics

​Computational Overhead

​Memory Usage

​Network Calls

​🧪 Testing & Validation

​What to Monitor

​Validation Checklist

​🔗 Related Documentation

How Auto-Hedging Works: Technical Deep-Dive

🧮 NET Position Monitoring

Why NET Position?

Separate Long/Short Monitoring

🎯 Trigger Conditions

Condition A: Drawdown Threshold

Condition B: Liquidation Distance

Critical Override

🛡️ Anti-Cascade Protection

The Cascade Problem

Safety Mechanism 1: Original Position Tracking

Safety Mechanism 2: Hedge Ratio Enforcement

Safety Mechanism 3: Price/Quantity Movement Checks

Safety Mechanism 4: Original Quantity Reset

🎬 Complete Hedge Cycle Example

Initial State

Step 1: Grid Fills (Long Side)

Step 2: Further Price Drop - Drawdown Trigger

Step 3: Calculate Hedge Size

Step 4: Place Hedge Order

Step 5: Hedge Fills

Step 6: Place Hedge Take Profit

Step 7: Trailing Stop Activates

Step 8: Trailing Stop Triggers

Step 9: Position After Hedge Close

Step 10: Grid Continues Operating

⚙️ Order Types Used

Hedge Placement: MARKET Order

Hedge Take Profit: LIMIT Order (Initial)

Trailing Stop: MARKET Order (When Triggered)

🔧 Exchange-Specific Implementation

BloFin Parameter Conversion

📊 State Tracking

🔁 Main Loop Integration

📈 Performance Characteristics

Computational Overhead

Memory Usage

Network Calls

🧪 Testing & Validation

What to Monitor

Validation Checklist

🔗 Related Documentation