Market Making

Build market-making strategies with inventory management and quote optimization

Overview

The MarketMakerStrategy provides a complete market-making implementation with:

• Automated quote generation and management
• Inventory-based price skewing
• Position limits and risk controls
• Multi-level quoting support

MarketMakerConfig

Configure your market-making strategy with MarketMakerConfig:

#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct MarketMakerConfig {
    /// Base spread in ticks
    pub base_spread_ticks: i64,
    /// Spread skew based on inventory (-1 to +1)
    pub inventory_skew_factor: f64,
    /// Maximum inventory (position limit)
    pub max_inventory: i64,
    /// Order size per level
    pub order_size: u32,
    /// Number of levels to quote
    pub num_levels: usize,
    /// Minimum edge required (in ticks)
    pub min_edge_ticks: i64,
    /// Cancel distance from BBO (in ticks)
    pub cancel_distance_ticks: i64,
    /// Tick size
    pub tick_size: i64,
    /// Refresh interval (in nanoseconds)
    pub refresh_interval_ns: i64,
}

Location: nano-strategy/src/market_maker.rs:12-32

Default Configuration

impl Default for MarketMakerConfig {
    fn default() -> Self {
        Self {
            base_spread_ticks: 2,
            inventory_skew_factor: 0.5,
            max_inventory: 50,
            order_size: 5,
            num_levels: 3,
            min_edge_ticks: 1,
            cancel_distance_ticks: 10,
            tick_size: 25,
            refresh_interval_ns: 100_000_000, // 100ms
        }
    }
}

Location: nano-strategy/src/market_maker.rs:34-48

Creating a Market Maker

use nano_strategy::{MarketMakerStrategy, MarketMakerConfig};

// Create custom configuration
let config = MarketMakerConfig {
    base_spread_ticks: 3,
    inventory_skew_factor: 0.6,
    max_inventory: 100,
    order_size: 10,
    num_levels: 5,
    min_edge_ticks: 1,
    cancel_distance_ticks: 15,
    tick_size: 25,
    refresh_interval_ns: 50_000_000, // 50ms
};

// Create the strategy
let mut strategy = MarketMakerStrategy::new(
    "my_market_maker",
    instrument_id,
    config,
    12.5, // tick value
);

Inventory Skewing

The market maker automatically adjusts quote prices based on inventory to reduce risk:

/// Calculate skewed quote prices based on inventory
fn calculate_quotes(&self, mid: Price) -> (Price, Price) {
    let position = self.base.position();
    let max_inv = self.config.max_inventory as f64;

    // Calculate inventory skew (-1 to +1)
    let inv_ratio = if max_inv > 0.0 {
        (position as f64 / max_inv).clamp(-1.0, 1.0)
    } else {
        0.0
    };

    // Skew quotes to reduce inventory
    // Positive inventory -> lower bid, higher ask
    let skew_ticks = (inv_ratio
        * self.config.inventory_skew_factor
        * self.config.base_spread_ticks as f64) as i64;

    let half_spread = self.config.base_spread_ticks * self.config.tick_size / 2;

    let bid_price =
        Price::from_raw(mid.raw() - half_spread - skew_ticks * self.config.tick_size);
    let ask_price =
        Price::from_raw(mid.raw() + half_spread - skew_ticks * self.config.tick_size);

    (bid_price, ask_price)
}

Location: nano-strategy/src/market_maker.rs:196-222

How Inventory Skewing Works

1. Neutral Position (inventory = 0)

   • Quotes are symmetric around mid price
   • Bid: mid - half_spread
   • Ask: mid + half_spread

2. Long Position (inventory > 0)

   • Bid is lowered (less aggressive buying)
   • Ask is lowered (more aggressive selling)
   • Encourages reducing inventory

3. Short Position (inventory < 0)

   • Bid is raised (more aggressive buying)
   • Ask is raised (less aggressive selling)
   • Encourages covering short

Example

// Configuration
let config = MarketMakerConfig {
    base_spread_ticks: 2,
    inventory_skew_factor: 0.5,
    max_inventory: 100,
    tick_size: 25,
    ..Default::default()
};

// With inventory = +50 (half of max)
let mid = Price::from_raw(50000);
let (bid, ask) = strategy.calculate_quotes(mid);

// inv_ratio = 50 / 100 = 0.5
// skew_ticks = 0.5 * 0.5 * 2 = 0.5 ticks
// bid = 50000 - 25 - (0.5 * 25) = 49962
// ask = 50000 + 25 - (0.5 * 25) = 50012

Quote Management

The QuoteManager tracks all active orders:

#[derive(Debug, Default)]
pub struct QuoteManager {
    /// Active bid orders
    bid_orders: HashMap<OrderId, (Price, Quantity)>,
    /// Active ask orders
    ask_orders: HashMap<OrderId, (Price, Quantity)>,
    /// Next order ID
    next_order_id: u64,
    /// Orders pending acknowledgment
    pending_acks: HashMap<OrderId, Side>,
}

Location: nano-strategy/src/market_maker.rs:51-61

Key Methods

impl QuoteManager {
    /// Generate next order ID
    pub fn next_order_id(&mut self) -> OrderId;

    /// Record a submitted order
    pub fn on_order_submit(
        &mut self,
        order_id: OrderId,
        side: Side,
        price: Price,
        quantity: Quantity,
    );

    /// Handle order acknowledgment
    pub fn on_order_ack(&mut self, order_id: OrderId);

    /// Handle order rejection
    pub fn on_order_reject(&mut self, order_id: OrderId);

    /// Handle order fill
    pub fn on_fill(&mut self, order_id: OrderId, fill_qty: Quantity);

    /// Handle order cancellation
    pub fn on_cancel(&mut self, order_id: OrderId);

    /// Get total bid quantity
    pub fn total_bid_quantity(&self) -> Quantity;

    /// Get total ask quantity
    pub fn total_ask_quantity(&self) -> Quantity;
}

Location: nano-strategy/src/market_maker.rs:63-164

Multi-Level Quoting

Generate quotes at multiple price levels:

fn generate_quotes(&mut self, book: &dyn OrderBook, current_time: Timestamp) -> Vec<Order> {
    let mut orders = Vec::new();

    let mid = match book.mid_price() {
        Some(m) => m,
        None => return orders,
    };

    // Check position limits
    let position = self.base.position();
    let can_buy = position < self.config.max_inventory;
    let can_sell = position > -self.config.max_inventory;

    let (bid_price, ask_price) = self.calculate_quotes(mid);

    // Generate bid orders
    if can_buy {
        for level in 0..self.config.num_levels {
            let price =
                Price::from_raw(bid_price.raw() - (level as i64 * self.config.tick_size));

            let order_id = self.quotes.next_order_id();
            let quantity = Quantity::new(self.config.order_size);

            let order = Order::new_limit(
                order_id,
                self.instrument_id,
                Side::Buy,
                price,
                quantity,
                TimeInForce::GTC,
            );

            self.quotes.on_order_submit(order_id, Side::Buy, price, quantity);
            orders.push(order);
        }
    }

    // Generate ask orders (similar logic)
    // ...

    orders
}

Location: nano-strategy/src/market_maker.rs:254-322

Level Spacing

With num_levels = 3 and tick_size = 25:

Level 0: bid_price - 0 ticks
Level 1: bid_price - 1 tick (25 units)
Level 2: bid_price - 2 ticks (50 units)

Position Limits

The strategy respects position limits:

// Check position limits
let position = self.base.position();
let can_buy = position < self.config.max_inventory;
let can_sell = position > -self.config.max_inventory;

// Only quote on sides where we can trade
if can_buy {
    // Generate bid orders
}

if can_sell {
    // Generate ask orders
}

Location: nano-strategy/src/market_maker.rs:266-269

Quote Refreshing

Quotes are refreshed periodically:

/// Check if quotes need to be refreshed
fn should_refresh_quotes(&self, current_time: Timestamp) -> bool {
    current_time.as_nanos() - self.last_quote_time.as_nanos() 
        >= self.config.refresh_interval_ns
}

fn on_market_data(&mut self, book: &dyn OrderBook) -> Vec<Order> {
    // Update base strategy
    self.base.on_market_data(book);

    if !self.is_ready() {
        return Vec::new();
    }

    let current_time = book.timestamp();

    // Check if we need to refresh quotes
    if self.should_refresh_quotes(current_time) {
        return self.generate_quotes(book, current_time);
    }

    Vec::new()
}

Location: nano-strategy/src/market_maker.rs:224-227, 348-366

Canceling Stale Quotes

Orders too far from the best bid/offer are cancelled:

fn generate_cancels(&self, book: &dyn OrderBook) -> Vec<OrderId> {
    let mut cancels = Vec::new();

    if let (Some((best_bid, _)), Some((best_ask, _))) = (book.best_bid(), book.best_ask()) {
        // Cancel bids too far from BBO
        for (id, (price, _)) in &self.quotes.bid_orders {
            let distance = (best_bid.raw() - price.raw()) / self.config.tick_size;
            if distance > self.config.cancel_distance_ticks {
                cancels.push(*id);
            }
        }

        // Cancel asks too far from BBO
        for (id, (price, _)) in &self.quotes.ask_orders {
            let distance = (price.raw() - best_ask.raw()) / self.config.tick_size;
            if distance > self.config.cancel_distance_ticks {
                cancels.push(*id);
            }
        }
    }

    cancels
}

Location: nano-strategy/src/market_maker.rs:229-252

Complete Example

use nano_strategy::{MarketMakerStrategy, MarketMakerConfig};
use nano_core::traits::Strategy;

// Configure the market maker
let config = MarketMakerConfig {
    base_spread_ticks: 2,
    inventory_skew_factor: 0.5,
    max_inventory: 100,
    order_size: 10,
    num_levels: 3,
    min_edge_ticks: 1,
    cancel_distance_ticks: 10,
    tick_size: 25,
    refresh_interval_ns: 100_000_000,
};

// Create the strategy
let mut mm = MarketMakerStrategy::new(
    "btc_market_maker",
    1, // instrument_id
    config,
    12.5, // tick_value
);

// In your trading loop
loop {
    // Get market data
    let orders = mm.on_market_data(&book);

    // Submit generated orders
    for order in orders {
        execution_handler.submit_order(order)?;
    }

    // Handle fills
    if let Some(fill) = execution_handler.next_fill() {
        mm.on_fill(&fill);
    }

    // Monitor position and P&L
    println!("Position: {}, P&L: ${:.2}", mm.position(), mm.pnl());
}

Monitoring

Access strategy state:

// Get current position
let position = strategy.position();

// Get P&L
let pnl = strategy.pnl();

// Get fair value estimate
let fair_value = strategy.fair_value();

// Get quote manager
let quotes = strategy.quotes();
let total_bid_qty = quotes.total_bid_quantity();
let total_ask_qty = quotes.total_ask_quantity();
let num_bids = quotes.bid_order_ids().len();
let num_asks = quotes.ask_order_ids().len();

Best Practices

1. Start with wider spreads - Use base_spread_ticks >= 2 to ensure profitability

2. Tune inventory skewing - Adjust inventory_skew_factor based on market volatility:

   • Higher volatility → stronger skewing (0.7-1.0)
   • Lower volatility → gentler skewing (0.3-0.5)

3. Set appropriate position limits - Don’t exceed your risk tolerance:

   max_inventory: calculate_max_position(capital, risk_per_contract)
   

4. Monitor fill rates - If fills are too low, tighten spreads or increase levels

5. Use appropriate refresh intervals - Balance between:

   • Faster updates (50-100ms) for active markets
   • Slower updates (200-500ms) for less liquid markets

Next Steps

Signal Generation

Add ML-based signals to your market maker

RL Strategies

Train RL agents for optimal market making