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Bot Configuration Parameters

Understanding bot configuration parameters is essential for optimizing your trading strategy. This guide covers all parameters for both single-symbol and multi-symbol configurations.
Multi-symbol configs give you more control and allow per-symbol customization. Single-symbol configs are simpler but less flexible.

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Core Strategy Parameters

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Grid Configuration

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nr_clusters
number
default:"4"
Number of grid clusters - How many layers of orders to place on each side
  • Conservative: 2-3 clusters (fewer, safer positions)
  • Moderate: 4 clusters (balanced approach)
  • Aggressive: 5+ clusters (more positions, more risk)
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outer_distance
number
default:"0.04"
Outer grid distance - How far from current price to place the furthest orders (as decimal)
  • 0.03 = 3% from current price
  • 0.04 = 4% from current price (recommended)
  • 0.05 = 5% from current price
Wider grids (0.04-0.05) work better in volatile markets
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ratio_power
number
default:"1.6"
Grid distribution power - Controls how grid orders are spaced
  • 1.0 = Linear spacing (equal distance between orders)
  • 1.2-1.4 = Slight geometric spacing
  • 1.6 = Strong geometric spacing (more orders near price)
Higher values concentrate more orders near the current price.
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first_level_distance
number
default:"0.0025"
First order distance - Distance to the first grid order (as decimal)
  • 0.002 = 0.2% from price (tight)
  • 0.0025 = 0.25% from price (recommended)
  • 0.003 = 0.3% from price (wider)

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Grid Clustering Algorithms

The Vortex DCA strategy supports intelligent grid placement using three different clustering algorithms. Each algorithm determines where to place your grid levels based on different market analysis methods.
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clustering_enabled
boolean
default:"false"
Enable clustering - Activate intelligent grid placement algorithmsWhen disabled, uses traditional geometric grid distribution.
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clustering_algo
string
default:"LINEAR"
Clustering algorithm - Choose how grid levels are calculatedAvailable options:
  • LINEAR - Evenly-spaced geometric distribution (default)
  • PEAKS_TROUGHS_HIGHLOW - Historical support/resistance levels
  • KMEANS - Statistical price clustering zones

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LINEAR (Default)

Traditional geometric grid distribution with equal spacing controlled by ratio_power. Best for:
  • Stable market conditions
  • Beginners learning grid trading
  • Assets with predictable volatility
Configuration: 
{
  "clustering_enabled": true,
  "clustering_algo": "LINEAR"
}
Characteristics:
  • No historical data required
  • Fast computation
  • Predictable, symmetric grid placement

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PEAKS_TROUGHS_HIGHLOW

Analyzes historical price data to identify swing highs and lows, placing grid levels at proven support and resistance zones where price historically reversed. Best for:
  • Range-bound markets
  • Assets with clear support/resistance levels
  • Technical analysis-focused trading
  • Markets with strong price memory
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clustering_period
string
default:"1M"
Historical lookback period - How far back to analyze price dataOptions: 1W, 1M, 3M, 6M, 1Y
  • 1W-1M = Responsive to recent market structure (altcoins)
  • 3M-6M = Balanced, medium-term S/R levels
  • 1Y = Long-term view (Bitcoin, major assets)
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clustering_timeframe
string
default:"5m"
Candle timeframe - Resolution of historical dataOptions: 1m, 5m, 15m, 1h, 4h, 1d
  • 1m-5m = High precision, large datasets (liquid pairs)
  • 15m-1h = Balanced precision and performance
  • 4h-1d = Macro view, lighter data requirements
Configuration Example: 
{
  "clustering_enabled": true,
  "clustering_algo": "PEAKS_TROUGHS_HIGHLOW",
  "clustering_period": "3M",
  "clustering_timeframe": "1m",
  "nr_clusters": 4
}
Use 3M with 1m timeframe for BTC - captures recent swing points with high precision

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KMEANS

Uses K-Means machine learning algorithm to identify natural price consolidation zones where price historically spent the most time. Grid levels are placed at cluster centroids. Best for:
  • Volatile markets with consolidation zones
  • Assets that range-trade before breakouts
  • Finding hidden liquidity zones
  • Statistical/ML-based trading approaches
Configuration Example: 
{
  "clustering_enabled": true,
  "clustering_algo": "KMEANS",
  "clustering_period": "1W",
  "clustering_timeframe": "5m",
  "nr_clusters": 6
}
How it works:
  1. Collects closing prices from historical period
  2. Uses K-Means to cluster prices into nr_clusters groups
  3. Places grid levels at each cluster centroid
  4. Levels naturally concentrate where price consolidated
K-Means works best with shorter periods (1W-1M) for recent consolidation zones

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Choosing the Right Algorithm

  • You’re new to grid trading
  • Market conditions are stable and predictable
  • You want consistent, geometric grid distribution
  • Historical patterns aren’t reliable for the asset
  • Asset shows clear support/resistance levels
  • You trust technical analysis
  • Market is range-bound with defined levels
  • You want grids at proven reversal zones
  • Asset is highly volatile with consolidation zones
  • You want to find hidden liquidity areas
  • Traditional S/R isn’t obvious visually
  • You trust statistical/ML approaches
All clustering algorithms respect your outer_distance and ratio_power settings. Historical data is fetched once per grid refresh (default: 3 minutes). If data fetch fails, automatically falls back to LINEAR.

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Position Management

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wallet_exposure
number
default:"0.1"
Wallet exposure per symbol - Percentage of wallet to allocate per symbol
  • 0.05 = 5% per symbol (conservative)
  • 0.1 = 10% per symbol (recommended)
  • 0.15 = 15% per symbol (aggressive)
With 6 symbols at 10% each = 60% total exposure. Keep total under 100%!
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initial_entry_size
number
default:"0.01"
Initial entry size - Size of first grid order as fraction of exposure
  • 0.005 = 0.5% of exposure
  • 0.01 = 1% of exposure (recommended)
  • 0.02 = 2% of exposure (larger first orders)
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qty_multiplier
number
default:"2"
Quantity multiplier - How much each successive grid order increases
  • 1.5 = Each order 50% larger than previous
  • 2 = Each order doubles in size (recommended)
  • 3 = Each order triples in size (aggressive DCA)

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Take Profit Settings

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minimum_tp
number
default:"0.0022"
Minimum take profit - Minimum profit percentage to close positions
  • 0.0015 = 0.15% profit (tight)
  • 0.0022 = 0.22% profit (recommended)
  • 0.003 = 0.3% profit (wider)
Lower values = more frequent but smaller profits
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refresh_threshold
number
default:"0.05"
Grid refresh threshold - Price movement % needed to refresh grid
  • 0.03 = Refresh at 3% movement
  • 0.05 = Refresh at 5% movement (recommended)
  • 0.08 = Refresh at 8% movement
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grid_refresh_interval
number
default:"180"
Grid refresh interval - Seconds between grid recalculations
  • 120 = 2 minutes (frequent updates)
  • 180 = 3 minutes (recommended)
  • 300 = 5 minutes (less frequent)

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Risk Management

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Liquidation Protection

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liquidation_safeguard
boolean
default:"true"
Enable liquidation safeguard - Prevents orders too close to liquidation price
Highly recommended - Always keep this enabled
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liquidation_safeguard_pct_dist
number
default:"5"
Liquidation distance % - Minimum distance from liquidation price
  • 5 = Orders must be 5% away from liquidation (recommended)
  • 10 = Extra safe, 10% buffer
  • 3 = Risky, only 3% buffer
Never set below 5% - risk of liquidation increases significantly

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Virtual Chunking (Position Recovery)

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virtual_chunking_enabled
boolean
default:"false"
Enable virtual chunking - Advanced position recovery for underwater positionsWhen enabled, splits large losing positions into smaller “chunks” for gradual recovery.
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virtual_chunking_threshold_pct
number
default:"3"
Chunking threshold - Unrealized loss % that triggers chunking
  • 2 = Activate at 2% loss (aggressive recovery)
  • 3 = Activate at 3% loss (recommended)
  • 5 = Activate at 5% loss (conservative)
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virtual_chunking_chunk_count
number
default:"5"
Number of chunks - How many pieces to split position intoMore chunks = more granular recovery but slower
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virtual_chunking_profit_target
number
default:"0.001"
Chunk profit target - Profit % for each chunk exit
  • 0.0008 = 0.08% profit per chunk (tight)
  • 0.001 = 0.1% profit per chunk (recommended)
  • 0.0015 = 0.15% profit per chunk

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Trading Modes

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long_mode
boolean
default:"true"
Enable long trades - Allow bot to open long (buy) positions
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short_mode
boolean
default:"true"
Enable short trades - Allow bot to open short (sell) positions
Enable both for balanced trading. Markets trend up and down!
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vortex_always_both_sides
boolean
default:"true"
Always maintain both sides - Keep grids on both long and short simultaneouslyRecommended: true for maximum opportunity capture

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BloFin-Specific Settings

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round_min_qty_blofin
boolean
default:"true"
Round to minimum quantity - Automatically round order sizes to BloFin’s minimum
Always enable this for BloFin to avoid order rejections
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startup_cleanup_all_symbols
boolean
default:"true"
Cleanup on startup - Cancel all existing orders when bot startsRecommended: true to start with clean state

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Multi-Symbol Configuration

Multi-symbol configs allow you to customize parameters per symbol in the symbol_config section.

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Example Multi-Symbol Config

{
  "symbols": ["DOGEUSDT", "ADAUSDT", "SUIUSDT"],
  "symbol_config": {
    "DOGEUSDT": {
      "wallet_exposure": 0.1,
      "minimum_tp": 0.0025
    },
    "ADAUSDT": {
      "wallet_exposure": 0.08,
      "minimum_tp": 0.002
    },
    "SUIUSDT": {
      "wallet_exposure": 0.12,
      "minimum_tp": 0.003
    }
  }
}

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Per-Symbol Parameters

You can override these parameters per symbol:
  • wallet_exposure - Different allocation per coin
  • minimum_tp - Different profit targets per coin
  • nr_clusters - More/fewer grids per coin
  • outer_distance - Wider/tighter grids per coin
Use higher exposure for stable coins (BTC, ETH) and lower for altcoins

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Advanced Parameters

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allow_add_smaller
boolean
default:"false"
Allow smaller additions - Permit adding to positions with smaller ordersUsually false - maintains consistent DCA scaling
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min_distance
number
default:"0.0025"
Minimum order distance - Closest two orders can be to each otherPrevents orders from clustering too tightly
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desired_distance
number
default:"0.05"
Desired grid spread - Target total distance for gridWorks with outer_distance to size the grid
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no_entry_above
number
default:"null"
No entry above price - Don’t open positions above this priceSet to limit entries in overextended markets. Example: 50000 for BTC
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no_entry_below
number
default:"null"
No entry below price - Don’t open positions below this priceSet a floor to avoid catching falling knives. Example: 30000 for BTC

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Configuration Tips

Use smaller exposure (5-8%), fewer clusters (2-3), and tighter grids (0.02-0.03) when learning
Increase exposure and clusters only after observing performance for several days
Use 4-6 different symbols to spread risk. Avoid correlated pairs (e.g., all memecoins)
Check bot performance daily. Adjust minimum_tp and outer_distance based on volatility
Always use liquidation_safeguard: true with liquidation_safeguard_pct_dist: 5 minimum

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Preset Configurations

Quant Dash provides pre-built configurations for different risk levels:

Conservative

  • 2-3 clusters
  • 5-8% exposure
  • Tight grids
  • Lower leverage

Moderate

  • 4 clusters
  • 10% exposure
  • Balanced grids
  • Standard leverage

Aggressive

  • 5+ clusters
  • 12-15% exposure
  • Wide grids
  • Higher leverage

View Presets

See all available presets in the Quick Start Guide
Always test with small amounts first. Start with 1-2 symbols at low exposure, monitor for 24-48 hours, then scale up gradually.