Backtesting Arena

Backtesting Arena

Back to blog

Funding Rates as a BTC Signal: We Tested It. It Doesn't Work The Way You Would Think

High funding rates signal overheated longs — a warning. Negative funding means shorts capitulating — a buy signal. The logic seems solid. We tested it across 6.7 years of BTC data. The results were the opposite of what we expected.

Backtesting Arena·June 7, 2026·2 min read·0 views
Funding Rates as a BTC Signal: We Tested It. It Doesn't Work The Way You Would Think

A few days ago we asked ourselves: what if we used funding rates as a trading signal for BTC?

The logic seems compelling. Funding rates on perpetual futures are the cost of keeping a long position open. When they're strongly positive, longs are paying shorts — that happens when the market is overheated, with too many people betting on rising prices. When they go negative, the dynamic reverses.

From this you can derive two signals:

BUY signal: Extreme negative funding → shorts dominating → contrarian buy. Filter: Extreme positive funding → longs overheated → block existing buy signals.

Sounds reasonable. So we tested it.

The Method

Dataset: Daily BTC funding rates from September 2019 to June 2026. That's 2,462 trading days, averaged across Binance and OKX.

We computed a 30-day rolling Z-score. This normalizes the signal across market regimes — "extremely high" always means the same thing regardless of whether we're in a bull or bear market.

Z-score distribution:

  • Z > +1.5 (extreme longs): 9% of days
  • Z < −1.5 (extreme shorts): 8.3% of days
  • Neutral zone: 82.7% of days

Rare enough to be meaningful — or so we thought.

We tested two scenarios:

Scenario A — Standalone strategy: Buy when Z-score first crosses below −1.5. Sell when it returns above 0, or after 30 days.

Scenario B — Filter: Take buy signals from another strategy — but block them when Z-score is above +1.5.

The Results

Scenario A produced 93 trades over 7 years:

  • Win rate: 53.8%
  • Avg return per trade: +1.14%
  • Avg hold time: 5 days

Technically slightly positive. After fees, probably zero or negative. Not a viable strategy.

Scenario B is where it gets surprising:

ConditionAvg 30d ReturnWin Rate
Normal funding (allowed)+4.23%54.1%
High funding, Z > 1.5 (blocked)+6.95%62.3%
Very high funding, Z > 2.5+9.87%64.5%

The filter would have blocked exactly the best entry points.

Why?

Because high funding rates don't signal reversals — they accompany strong trends.

In a real bull market, funding stays elevated for weeks. The market keeps punishing short sellers while the trend continues. The mean-reversion effect we were counting on exists — but it's too weak and too delayed to be visible within a 30-day window.

High funding = the trend is running. Not an exit signal.

What We Take Away

Funding rate Z-score is not a useful signal or filter for BTC entries in this form.

One could argue: combine it with trend context. Block entries only when funding is high and momentum divergence is visible. But at that point that's essentially a momentum-divergence signal — the funding component contributes little.

We're shelving this idea for now.

The most important thing here isn't the result. It's the process: formulate an idea, build a concrete implementation, test it on real data, report honestly.

Sometimes the answer is: doesn't work. That's worth just as much as a positive result — it saves time and protects against false confidence.


Methodology: Daily funding rates (Binance + OKX average), BTC spot prices, 30-day rolling Z-score. No transaction costs modeled. Not financial advice.

Try it yourself

Run the backtest with your own parameters and time ranges.

Run backtest →
📬

Don't miss new blog posts

One short email per new post — strategies, backtests, market analysis. No spam, unsubscribe with one click anytime.

By subscribing you accept our privacy policy. We use Resend for delivery. Double opt-in confirmation required.

Comments (0)

Join free to post comments.

Sign up →

No comments yet. Be the first!