Mint Selection & Ranking

This section explains how arb-assist selects and ranks tokens (mints) for arbitrage opportunities.

Core Concepts

Mint Groups

Mints are organized into transaction groups for arbitrage:

mints_to_arb = [2, 2, 3]  # 3 groups: 2 mints, 2 mints, 3 mints

This creates:

• Group 1: 2 mints per transaction

• Group 2: 2 mints per transaction

• Group 3: 3 mints per transaction

Ranking System

mints_to_rank = 20  # Keep top 20 mints in ranking

Requirements:

• mints_to_rank ≥ sum of mints_to_arb

• Higher values = more opportunities tracked

• Lower values = less memory usage

Mint Configuration

mints_to_arb

Type: array Required: Yes Description: Number of mints per transaction group

# Simple: 2 groups of 2 mints each
mints_to_arb = [2, 2]

# Complex: Multiple group sizes
mints_to_arb = [2, 2, 3, 3, 4]

# Single group
mints_to_arb = [5]

Strategies:

• [2, 2]: Standard, balanced approach

• [1, 1, 1]: Isolated trades, safer

• [3, 4, 5]: Complex routes, higher gas

mints_to_rank

Type: integer Required: Yes Description: Total number of mints to track

mints_to_rank = 10   # Minimal tracking
mints_to_rank = 20   # Standard
mints_to_rank = 50   # Comprehensive
mints_to_rank = 100  # Maximum coverage

Trade-offs:

• Higher: More opportunities, more memory

• Lower: Focused approach, less overhead

Sorting Strategies

intermint_sort_strategy

Type: object Required: Yes Description: How to rank mints against each other

intermint_sort_strategy = { 
  metric = "profit", 
  direction = "descending" 
}

Available Metrics

Financial Metrics

profit

metric = "profit"  # Total arbitrage profit

• Raw profit in lamports

• Best for maximizing returns

• May favor high-volume tokens

roi (Return on Investment)

metric = "roi"  # Profit / Gas fees ratio

• Efficiency metric

• Good for limited capital

• Favors gas-efficient trades

profit_per_arb

metric = "profit_per_arb"  # Average profit per trade

• Consistency metric

• Identifies reliable opportunities

• Smooths out outliers

Volume Metrics

total_volume

metric = "total_volume"  # Buy + Sell volume

• Market activity indicator

• High volume = more opportunities

• May include wash trading

net_volume

metric = "net_volume"  # |Buy - Sell| volume

• Directional pressure indicator

• High net = trending token

• Identifies momentum

turnover

metric = "turnover"  # Volume / Liquidity ratio

• Market efficiency metric

• High turnover = active trading

• Relative to pool size

Success Metrics

successful_arbs

metric = "successful_arbs"  # Count of profitable trades

• Reliability indicator

• High count = proven opportunity

• Ignores profit size

fails

metric = "fails"  # Failed transaction count

• Risk indicator

• Use with ascending sort

• Identifies problematic mints

Market Metrics

liquidity

metric = "liquidity"  # Total pool liquidity

• Depth indicator

• Higher = less slippage

• More stable prices

volatility

metric = "volatility"  # Price movement metric

• Opportunity indicator

• Higher = more arbitrage

• Also higher risk

pool_age

metric = "pool_age"  # Time since first seen

• Maturity indicator

• Newer = more volatile

• Older = more stable

imbalance

metric = "imbalance"  # Buy/sell pressure ratio

• Direction indicator

• High = one-sided flow

• Arbitrage opportunity

pool_sort_strategy

Type: object Required: Yes Description: How to rank pools within each mint

pool_sort_strategy = { 
  metric = "liquidity", 
  direction = "descending" 
}

Common strategies:

• liquidity: Use deepest pools first

• profit: Most profitable pools first

• volume: Most active pools first

Filter Thresholds

Multi-tier Filtering

filter_thresholds = [
  { # Tier 0: Low activity
    min_profit = 1_000_000,
    min_roi = 1.5,
    min_txns = 2,
    min_total_volume = 100_000_000,
    min_liquidity = 10_000_000,
    top_pool_num = 3
  },
  { # Tier 1: Medium activity  
    min_profit = 10_000_000,
    min_roi = 3.0,
    min_txns = 10,
    min_total_volume = 1_000_000_000,
    min_liquidity = 100_000_000,
    top_pool_num = 4
  },
  { # Tier 2: High activity
    min_profit = 100_000_000,
    min_roi = 5.0,
    min_txns = 50,
    min_total_volume = 10_000_000_000,
    min_liquidity = 1_000_000_000,
    top_pool_num = 5
  }
]

Filter Parameters

min_profit

• Type: integer (lamports)

• Minimum cumulative profit

• 1 SOL = 1_000_000_000 lamports

min_roi

• Type: float

• Minimum return on investment

• Example: 2.0 = 200% return

min_txns

• Type: integer

• Minimum successful arbitrages

• Higher = more proven

min_fails

• Type: integer

• Maximum failed transactions

• Lower = more reliable

min_net_volume

• Type: integer (lamports)

• Minimum directional volume

• Indicates trending tokens

min_total_volume

• Type: integer (lamports)

• Minimum trading volume

• Ensures adequate activity

min_imbalance_ratio

• Type: float (0.0 - 1.0)

• Minimum buy/sell imbalance

• Higher = stronger trend

max_imbalance_ratio

• Type: float (0.0 - 1.0)

• Maximum buy/sell imbalance

• Prevents one-sided markets

min_liquidity

• Type: integer (lamports)

• Minimum pool liquidity

• Ensures adequate depth

min_turnover

• Type: float

• Minimum volume/liquidity ratio

• Indicates trading activity

min_volatility

• Type: float

• Minimum price volatility

• Higher = more opportunities

max_cu_limit

• Type: integer

• Maximum compute units

• Controls transaction complexity

top_pool_num

• Type: integer (minimum 2)

• Number of pools to use

• More pools = more routes

Selection Examples

Conservative Strategy

# Focus on proven, liquid opportunities
intermint_sort_strategy = { metric = "roi", direction = "descending" }
mints_to_arb = [2, 2]
mints_to_rank = 10

filter_thresholds = [{
  min_profit = 10_000_000,
  min_roi = 3.0,
  min_txns = 20,
  min_fails = 5,
  min_liquidity = 1_000_000_000,
  top_pool_num = 3
}]

Aggressive Strategy

# Capture all opportunities
intermint_sort_strategy = { metric = "profit", direction = "descending" }
mints_to_arb = [3, 3, 4, 4]
mints_to_rank = 50

filter_thresholds = [{
  min_profit = 100_000,
  min_roi = 1.1,
  min_txns = 1,
  min_total_volume = 10_000_000,
  top_pool_num = 5
}]

Volume-Based Strategy

# Follow the money
intermint_sort_strategy = { metric = "total_volume", direction = "descending" }
pool_sort_strategy = { metric = "turnover", direction = "descending" }

filter_thresholds = [{
  min_total_volume = 10_000_000_000,
  min_turnover = 2.0,
  min_txns = 5,
  top_pool_num = 4
}]

New Token Strategy

# Target fresh opportunities
intermint_sort_strategy = { metric = "pool_age", direction = "ascending" }

filter_thresholds = [{
  min_volatility = 0.05,
  min_total_volume = 1_000_000_000,
  max_imbalance_ratio = 0.8,
  top_pool_num = 3
}]

Advanced Configuration

Tiered Mint Selection

Use different groups for different strategies:

mints_to_arb = [2, 2, 3, 3]  # 4 groups

# Group 1-2: Conservative (2 mints)
# Group 3-4: Aggressive (3 mints)

spam_levels = [
  { bundle_groups = [1, 2], ... },  # Conservative groups
]

jito_levels = [
  { bundle_groups = [3, 4], ... },  # Aggressive groups
]

Dynamic Adjustment

Combine with half-life decay:

halflife = 60000  # 1 minute decay

# Fast decay for volatile markets
halflife = 30000  # 30 seconds

# Slow decay for stable markets  
halflife = 300000  # 5 minutes

Performance Tuning

Memory Usage

Approximate memory per mint:

• Basic data: ~1 KB

• Pool data: ~10 KB per pool

• History: ~100 KB per mint

Total estimate:

Memory = mints_to_rank * (1 + 10 * avg_pools + 100) KB

CPU Usage

Processing time factors:

• Sorting: O(n log n) for n mints

• Filtering: O(n * m) for m thresholds

• Updates: Every update_interval ms

Optimization Tips

1. Reduce mints_to_rank if memory constrained

2. Increase update_interval if CPU constrained

3. Simplify sort metrics for faster processing

4. Use fewer filter tiers for quicker decisions

Troubleshooting

No Mints Selected

# Dummy mint indicates no opportunities found
mint = "11111111111111111111111111111111"

Solutions:

• Lower filter thresholds

• Check GRPC data stream

• Verify arbitrage programs

• Wait for market activity

Poor Quality Mints

If selected mints aren't profitable:

• Increase min_profit threshold

• Raise min_roi requirement

• Require more min_txns

• Check sort strategy

Missed Opportunities

If missing good trades:

• Increase mints_to_rank

• Lower filter thresholds

• Add more mint groups

• Reduce update_interval