DCA

📌 Standard Deviation DCA Strategy

Automated position building using statistical price bands

A smart accumulation algorithm that executes buy/sell orders when price deviates significantly from its mean, with flexible order sizing and LIFO profit-taking options.

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⚙️ Core Parameters

Parameter	Example	Description
Amount	5000	Target token volume
Order_size_min	50	Base order size (in tokens)
Price_Low	2	Lower price boundary
Price_High	4	Upper price boundary
Period	1d	Order triggering frequency
Window_Size	21	Candles for mean/std calculation
Buy_Threshold	3	Buy when price < (mean - 3σ)
Sell_Threshold	2	Sell when price > (mean + 2σ)

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📊 Order Sizing Modes

1. Classic

• Fixed-size orders: Order_size_min tokens per trade

2. Martingale

• Order size increases exponentially from Price_High to Price_Low

3. Logarithmic

• Calculated per:

  Order_size(n) = Order_size_min * multiplier * ln(n+1)

  Where:

  • S = Order_size_min

  • M = Multiplier (e.g., 1.05)

  • n = Trade count

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📌 Example: Buying TON with SD-DCA

Setup:

• Mean price: 3.00,σ=3.00,σ=0.20

• Buy trigger: 3.00−(3×3.00−(3×0.20) = $2.40

• Log mode: M=1.05, S=50 TON

Execution:

1. Trade #1 at $2.40:

   • Size = 50 × (1 + 1.05×ln(1)) = 50 TON

2. Trade #5 at $2.20:

   • Size = 50 × (1 + 1.05×ln(5)) = 131 TON

LIFO Selling:

• If price rebounds to $2.80 (mean + 2σ):

  • Sells most recent buy first

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🔍 Key Features

✅ Statistical edge - Buys at statistically "low" prices ✅ Flexible scaling - Choose risk profile via order sizing ✅ Auto-profit taking - LIFO selling locks gains

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🛡 Risk Controls

✔ Price boundaries prevent extreme executions ✔ Configurable σ thresholds adjust sensitivity ✔ Real-time PnL tracking

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📊 Performance Tracking

• Realized PnL per closed position

• Net average entry price

• Missed signal diagnostics

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🔥 Ideal For:

• Accumulating during market dips

• Mean-reversion strategies