Scaled orders are an advanced algorithmic trading strategy designed to execute large orders efficiently while minimizing market impact and volatility. By breaking down a single large order into multiple smaller sub-orders placed at incrementally adjusted prices, traders gain precise control over execution prices and timing.
How Scaled Orders Work
A scaled order distributes a parent order across a predefined price range using one of four distribution methods:
| Distribution Type | Description | Best Use Case |
|---|---|---|
| Flat (Even Split) | Orders are evenly divided by quantity and spaced uniformly across the price range. | Neutral market outlook with expected range-bound price action. |
| Increasing | Order sizes increase at higher prices (for buys) or lower prices (for sells). | Bullish bias (buys) or Bearish bias (sells). |
| Decreasing | Order sizes decrease at higher prices (for buys) or lower prices (for sells). | Cautious entry with reducing position size. |
| Custom | User-defined distribution with manual price/quantity adjustments per sub-order. | Highly specialized trading strategies. |
👉 Master advanced order types to enhance your trading strategy
Key Parameters
- Order Count: 2-20 sub-orders (varies by platform)
- Price Range: Upper/lower bounds must contain all sub-order prices
- Total Quantity: Sum of all sub-order sizes (minimum 10x base contract size)
- Increment: Fixed price intervals between orders
Benefits of Using Scaled Orders
Reduced Market Impact
- Smaller sub-orders prevent large single orders from moving the market
- Gradual execution camouflages trading intentions
Improved Price Efficiency
- Achieves better average entry/exit prices vs. single large orders
- Automatically capitalizes on natural price fluctuations
Risk Management
- Diversifies execution across multiple price points
- Limits exposure to unfavorable price spikes
Practical Example: ETH Short Position
Scenario: Trader wants to short 1,000 ETH with current price at 1,550 USDT
Parameters:
- Total Quantity: 1,000 ETH
- Order Count: 10
- Distribution: Flat (100 ETH per order)
- Price Range: 1,600-1,780 USDT
- Increment: +20 USDT per order
Execution:
1. Order 1: 100 ETH @ 1,600
2. Order 2: 100 ETH @ 1,620
...
10. Order 10: 100 ETH @ 1,780
Average Price: 1,690 USDT👉 Discover how professional traders optimize execution
Step-by-Step Guide to Placing Scaled Orders
Access Trading Interface
- Navigate to derivatives trading page
- Select desired contract (e.g., ETHUSDT)
Configure Order Parameters
- Set price range (upper/lower bounds)
- Enter total quantity
- Choose order count (2-20)
Select Distribution Method
- Flat/Increasing/Decreasing for automated distribution
- Custom for manual price/size adjustments
Review & Submit
- Verify order details
- Confirm submission
Note: Some platforms may show immediate fill warnings if sub-order prices are better than current market.
Frequently Asked Questions
Q: What's the minimum order size for scaled orders?
A: Typically 10x the base contract minimum (e.g., 0.01 BTC for BTCUSDT when base minimum is 0.001 BTC).
Q: Can I cancel individual sub-orders?
A: Yes, most platforms allow modification/cancellation of unfilled sub-orders.
Q: How does scaled order differ from TWAP?
A: Scaled orders use fixed price increments, while TWAP executes continuously over time regardless of price.
Q: Is there extra fee for scaled orders?
A: No additional fees - standard trading fees apply per executed sub-order.
Q: What happens if price doesn't reach my range?
A: Unfilled sub-orders remain active until canceled or expired (depending on platform settings).
Q: Can I use scaled orders for market making?
A: Yes, they're effective for providing liquidity across multiple price levels.
Advanced Considerations
- Volatility Adjustment: Wider price ranges suit high-volatility assets
- Liquidity Analysis: Denser order spacing may be needed in thin markets
- Time Sensitivity: Combine with time-in-force parameters for event-based trading
For traders managing large positions or seeking optimized execution, scaled orders provide a systematic approach to minimize market impact while achieving favorable average prices. This strategy is particularly valuable in derivatives markets where precise entry/exit points significantly affect profitability.