Funding Rate Arbitrage

What it does

When your agent uses it

• Writing a funding-rate-driven perp strategy on Superior Trade — anything described as funding harvest
• Funding arbitrage
• Funding rate carry
• Negative funding

Example prompts

• “fundingrate”
• “/funding-rate-arbitrage”

Requirements

• Python 3

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

1. 1Spot pair instead of perp. BTC/USDC returns no funding rate — the column will be all zeros and zero trades fire. Always use BTC/USDC:USDC.
2. 2Non-Hyperliquid exchange. This works on Hyperliquid because dp.get_pair_dataframe(candle_type="funding_rate") is wired up for HL. Other…
3. 3No fallback for missing data. The try/except plus the dataframe.empty check matters — if funding history isn't downloaded yet, the…
4. 4Misreading the unit. funding_rate is per-hour (HL funds hourly). Annualizing as * 365 instead of * 24 * 365 is off by 24×.
5. 5Treating Sharpe 1.52 as a forward predictor. The audit window (Jan-May 2026) had unusually negative funding episodes during BTC's…

What it can do on your machine

Read from SKILL.md and the folder at commit 9d41db5. It shows what the files ask for, not the result of running them.

• Tool permissions

  Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

  From allowed-tools in the SKILL.md frontmatter.

• Runs code

  No scripts in the folder and no shell commands in SKILL.md (its code samples are python and json).

  From the folder's file list and the shell code blocks in SKILL.md.

• Network

  Links to these hosts (documentation or services it may open):

  • freqtrade.io
  • hyperliquid.gitbook.io

  From URLs in SKILL.md, links to its own repository left out.

• Credentials

  Names no API keys, tokens, secrets or passwords.

  From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Funding Rate Arbitrage loads about 1.9k tokens when it runs. Until then it costs about 96 tokens; SKILL.md has 537 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~96

When it runs · the whole SKILL.md, loaded when a task matches

~1.9k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from Superior-Trade/superior-skills at commit 9d41db5, republished under its MIT licence (© Superior-Trade). 537 words, ~1,921 tokens.

name

funding-rate-arbitrage

description

Use when writing a funding-rate-driven perp strategy on Superior Trade — anything described as funding harvest, funding arbitrage, funding rate carry, negative funding, paid to long, paid to short, basis trade. The strategy reads Hyperliquid hourly funding via `dp.get_pair_dataframe(candle_type="funding_rate")`, which is automatically downloaded for backtests.

metadata.version

0.1.0

metadata.updated

2026-05-07

funding = self.dp.get_pair_dataframe(
    pair=metadata["pair"],
    timeframe="1h",          # Hyperliquid funds hourly
    candle_type="funding_rate",
)

from freqtrade.strategy import IStrategy
from datetime import datetime
import pandas as pd
import talib.abstract as ta


class FundingHarvestStrategy(IStrategy):
    minimal_roi = {"0": 100.0}   # let funding work; no profit-target exit
    stoploss = -0.05
    trailing_stop = False
    timeframe = "1h"
    process_only_new_candles = True
    startup_candle_count = 30
    can_short = False

    def populate_indicators(self, dataframe: pd.DataFrame, metadata: dict) -> pd.DataFrame:
        # Hyperliquid funds hourly — request 1h funding-rate candles.
        try:
            funding = self.dp.get_pair_dataframe(
                pair=metadata["pair"],
                timeframe="1h",
                candle_type="funding_rate",
            )
        except Exception:
            funding = pd.DataFrame()

        if not funding.empty and "open" in funding.columns:
            f = funding[["date", "open"]].rename(columns={"open": "funding_rate"}).copy()
            dataframe = dataframe.merge(f, on="date", how="left")
            dataframe["funding_rate"] = dataframe["funding_rate"].ffill().fillna(0.0)
            # Annualize hourly funding: APR = rate * 24 * 365.
            dataframe["funding_apr"] = dataframe["funding_rate"] * 24 * 365
        else:
            dataframe["funding_rate"] = 0.0
            dataframe["funding_apr"] = 0.0

        dataframe["atr_24"] = ta.ATR(dataframe, timeperiod=24)
        return dataframe

    def populate_entry_trend(self, dataframe: pd.DataFrame, metadata: dict) -> pd.DataFrame:
        # Long when funding APR is deeply negative (shorts paying longs).
        dataframe.loc[
            (dataframe["funding_apr"] < -0.10) & (dataframe["volume"] > 0),
            "enter_long",
        ] = 1
        return dataframe

    def populate_exit_trend(self, dataframe: pd.DataFrame, metadata: dict) -> pd.DataFrame:
        # Exit when funding flips back to non-negative (no more carry).
        dataframe.loc[(dataframe["funding_apr"] >= 0.0), "exit_long"] = 1
        return dataframe

    def custom_exit(self, pair: str, trade, current_time: datetime,
                    current_rate: float, current_profit: float, **kwargs):
        # Hard timeout — the entry condition was wrong if we're still in
        # after 24h without an exit signal.
        elapsed_h = (current_time - trade.open_date_utc).total_seconds() / 3600.0
        if elapsed_h >= 24:
            return "timeout_24h"
        return None

{
  "exchange": { "name": "hyperliquid", "pair_whitelist": ["BTC/USDC:USDC"] },
  "stake_currency": "USDC",
  "stake_amount": 100,
  "timeframe": "1h",
  "max_open_trades": 1,
  "stoploss": -0.05,
  "minimal_roi": { "0": 100.0 },
  "trading_mode": "futures",
  "margin_mode": "cross",
  "entry_pricing": { "price_side": "same" },
  "exit_pricing": { "price_side": "same" },
  "pairlists": [{ "method": "StaticPairList" }]
}

© Superior-Trade, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/funding-rate-arbitrage of Superior-Trade/superior-skills.

Open the folder on GitHubat commit 9d41db5