Fees Optimizations

Freqtrade × Hyperliquid: Fee Optimization

When to use

• A user asks why their backtest PnL doesn't match live PnL.
• A user designs a tight-target scalp / market-making / grid strategy and you want to flag fee-as-a-fraction-of-edge concerns before they deploy.
• A user explicitly asks about maker vs taker, post-only, fee tiers, builder code, or slippage.
• Any time you're about to suggest an order_types/entry_pricing/exit_pricing block, anchor it to this skill's recommendations.

What you're actually paying

Fees on a Superior Trade Hyperliquid deployment have three layers, each tunable:

1. Hyperliquid exchange fees (the floor)

Hyperliquid's perp fees as of writing (verify against https://hyperliquid.gitbook.io/hyperliquid-docs/trading/fees for current numbers):

Spot is typically slightly lower; HLP/staking discounts can shave another 0.001-0.005%.

The big takeaway: maker is ~4.5× cheaper than taker. A round-trip taker trade pays ~9 bp; a round-trip maker trade pays ~2 bp. On a 0.6% scalp target, taker fees consume 15% of gross PnL before slippage.

2. Builder code fee (Superior's cut)

Every order on Superior-managed Hyperliquid deployments goes through a builder code, which adds a separate fee that goes to Superior. Default is 5 bp on volume traded, taker or maker. Verify the actual rate for the user's account in the Superior dashboard.

This fee is always paid regardless of order type. It can't be optimized away with maker/post-only — it scales with notional volume traded. The only knob is reducing turnover (fewer trades, larger size, longer holds).

3. Slippage (the variable cost)

Slippage = the difference between the price your strategy assumed and the price you actually filled at. On Hyperliquid:

• Liquid majors (BTC, ETH, SOL): typically 0–2 bp on $10K notional with tight spread.
• Mid-cap perps: 5-20 bp on $10K notional.
• Thin alts / new listings: can be 50+ bp on a single market order.

Slippage is always taker-flavored for market orders and near-zero for filled limit orders. Backtest engine uses last-trade price assumption, which understates real-world slippage on illiquid pairs.

The four knobs Freqtrade exposes

Knob 1: order_types — limit vs market

{
  "order_types": {
    "entry": "limit",
    "exit": "limit",
    "stoploss": "market",
    "stoploss_on_exchange": false
  }
}

Knob 2: entry_pricing / exit_pricing — where on the book

{
  "entry_pricing": {
    "price_side": "same",
    "use_order_book": true,
    "order_book_top": 1,
    "price_last_balance": 0.0,
    "check_depth_of_market": { "enabled": false }
  },
  "exit_pricing": {
    "price_side": "same",
    "use_order_book": true,
    "order_book_top": 1
  }
}

Default for cost-sensitive strategies: price_side: "same", use_order_book: true, order_book_top: 1, price_last_balance: 0.0. This posts at the best bid (long) / best ask (short), maker-only unless the market crosses you.

Knob 3: unfilledtimeout — how patient is the maker?

{
  "unfilledtimeout": {
    "entry": 10,
    "exit": 10,
    "exit_timeout_count": 0,
    "unit": "minutes"
  }
}

A limit order sitting on the book is great until the market walks away. unfilledtimeout is when Freqtrade gives up and re-prices (or cancels). For a 5m strategy, entry: 5 minutes is sane — give the limit one bar to fill, then chase. For a daily DCA, entry: 60+ is fine.

exit_timeout_count: 3 means: after 3 timeout cycles on the exit, fall back to a market order. Good for ensuring the exit eventually happens.

Knob 4: stake_amount — fewer, bigger trades

The builder code fee scales with notional volume. Two trades at $1000 each pay the same builder fee as four trades at $500 each. If your strategy works at higher position size, prefer fewer larger trades to reduce per-trade fixed cost.

This isn't a Freqtrade knob per se, but an engineering choice: lower-frequency strategies amortize per-trade fees better.

Recommended starting block (cost-sensitive)

For any strategy where fees matter (scalping, grid, frequent entries), start here:

{
  "order_types": {
    "entry": "limit",
    "exit": "limit",
    "stoploss": "market",
    "stoploss_on_exchange": false,
    "trailing_stop_loss": "market"
  },
  "entry_pricing": {
    "price_side": "same",
    "use_order_book": true,
    "order_book_top": 1,
    "price_last_balance": 0.0
  },
  "exit_pricing": {
    "price_side": "same",
    "use_order_book": true,
    "order_book_top": 1,
    "price_last_balance": 0.0
  },
  "unfilledtimeout": {
    "entry": 10,
    "exit": 10,
    "exit_timeout_count": 3,
    "unit": "minutes"
  }
}

For a "fill at any cost" deployment (e.g. funding harvest where missing the entry costs more than the spread), use price_side: "other" and entry: "market".

Fee budget rule of thumb

Before recommending any tight-target strategy, compute the edge-to-fee ratio:

edge_to_fee = (avg_per_trade_pnl_bp) / (round_trip_fee_bp + slippage_bp)

Where:

• round_trip_fee_bp ≈ 9 bp (taker, both sides) or 2 bp (maker, both sides) on top of HL native fees
• Plus builder code fee × 2 (entry + exit) — typically 10 bp round trip
• Plus slippage estimate (1 bp majors, 5-20 bp mid-cap)

So realistic round-trip cost on majors ≈ 12-15 bp (taker) or 5-8 bp (maker).

The Scalp template's 0.6% target / 0.4% stop with default taker pricing has edge_to_fee ≈ 4.6× on win, but the 33% win rate from the reference backtest means it's a net loser. Forcing maker-only would help significantly.

Common pitfalls

1. Defaulting to entry: "market" because limits "might not fill". A maker limit that fills 70% of the time at 1 bp beats a market that fills 100% of the time at 5 bp on most strategies. Pair limit entries with a sane unfilledtimeout and accept some signals will be skipped.
2. Backtest assumes price_side: "same" will always fill. The Freqtrade backtester treats limit orders as filled at the bar's price — it does NOT simulate queue priority or partial fills. Live behavior on illiquid pairs is worse. Always slippage-stress your backtest by re-running with entry: "market" to see worst-case PnL.
3. Forgetting stoploss_on_exchange: false is the default and correct. Setting true puts the stop on the exchange (avoids gap risk) BUT only fires on next candle close on Freqtrade's polling cadence. The agent wallet model on Superior already handles this; leave it false.
4. Stacking trailing_stop with exit_pricing.price_side: "same". The trail emits a sell signal; combined with same-side maker pricing, the limit sits on the bid waiting for a buyer that may never come. For trailing exits, force exit_pricing.price_side: "other" OR rely on stoploss: "market".
5. Ignoring builder code fee in projections. A "0% fee crypto exchange" Twitter post is useless if Superior's builder code is 5 bp. The 5 bp is on the user's gross volume, not net PnL.

When you don't optimize fees

For low-turnover strategies (DCA weekly, funding harvest with avg holding > 8h), fee optimization is secondary to correctness. A 10 bp round-trip cost amortized over a week-long hold is a 0.014% APR drag — invisible. Spend the optimization budget on entry quality instead.

Source-of-truth checks

When the user reports unexpected fee outcomes, verify in this order:

1. Hyperliquid fee tier: https://app.hyperliquid.xyz/portfolio shows current 14-day volume tier.
2. Builder code rate: Superior dashboard, deployment detail page, fees section.
3. Slippage on filled orders: Compare order_filled_avg_price to bar close in the Freqtrade trade log. Persistent > 5 bp slippage on majors means the order_book pricing is wrong.
4. Maker vs taker ratio: Hyperliquid trade history shows maker: true/false per fill. Aim for > 70% maker in production for cost-sensitive strategies.

Sources

• Hyperliquid fees — https://hyperliquid.gitbook.io/hyperliquid-docs/trading/fees
• Freqtrade configuration reference — https://www.freqtrade.io/en/stable/configuration/#understand-order_types
• Freqtrade pricing — https://www.freqtrade.io/en/stable/configuration/#understand-entry_pricing-and-exit_pricing