Fisher Stochastic Center of Gravity Indicator: What the Data Shows

What Is the Fisher Stochastic Center of Gravity?

The Fisher Stochastic Center of Gravity is a composite oscillator that fuses three separate signal-processing tools developed by John Ehlers: the Fisher Transform, which normalizes price data and amplifies turning-point signals; the Stochastic oscillator, which tracks where price sits in its recent range; and the Center of Gravity, a leading oscillator built from weighted averages of closing prices. The idea is that each tool identifies cycles independently, and combining them reduces noise.

You will find it on trading platforms under various names — sometimes labeled "Fisher Stoch CoG" or similar. The appeal is clear: three frameworks that each purport to anticipate reversals, merged into one signal line. Whether that combination holds up in out-of-sample testing is a different question.

The Fisher Transform Component Has the Strongest Forex Record in Our Database

Across 660,005 out-of-sample backtests covering 903 assets and 382 indicators, the plain Fisher Transform ranked first for Forex — topping 17 currency pairs. That is the widest single-indicator margin over its nearest competitor in any asset class in our database. Tested timeframes were 1-Hour, 4-Hour, Daily, and Weekly.

That result matters when you evaluate the composite. The Fisher Transform component is not decoration — it carries a documented edge in Forex specifically. Whether wrapping it inside a stochastic and Center of Gravity layer preserves, amplifies, or erodes that edge depends on your specific asset and timeframe. You can browse Forex results by asset here.

What the Broader Numbers Say About Composite Indicators

Only 26% of all indicator and asset combinations in our database beat buy-and-hold after realistic transaction costs. The median best Sharpe ratio across all 903 assets was 0.62 — useful, but not dramatic. Adding components to an indicator does not automatically increase edge; it adds parameters that can overfit the historical data and then fail on new price action.

A composite like the Fisher Stochastic Center of Gravity has more internal parameters than any of its three source indicators alone. That is neither a mark against it nor a guarantee — it is a reason to demand out-of-sample evidence on your specific instrument before trading it.

High Win Rates in Composite Oscillators Are a Known Trap

Our data shows a repeating pattern: oscillators that generate smooth, clean-looking signals tend to post high apparent win rates — but rarely beat a simple buy-and-hold after costs. The Money Flow Index averaged a 72.2% win rate across assets yet beat buy-and-hold in only 9% of cases. The CCI showed the same shape: a 71.0% win rate against just 9% beating buy-and-hold.

Composite oscillators that blend multiple smoothed inputs are especially prone to this profile. A signal that looks clean and confident on a chart is not the same as a signal that beats doing nothing. If you see a Fisher Stochastic Center of Gravity strategy marketed on the basis of its win rate, treat that as a warning sign, not a selling point.

How to Evaluate It — and What We Tested

We tested across 1-Hour, 4-Hour, Daily, and Weekly timeframes. We did not test the Fisher Stochastic Center of Gravity as a single combined indicator — our database covers the Fisher Transform individually (where its Forex record is documented above) and other components separately. If you want to know whether the composite holds up on a specific currency pair or asset, you need out-of-sample results on that instrument.

If you are trading Forex, the plain Fisher Transform has the clearest backtest record of any indicator in that asset class in our data. Starting there and testing any composite variant against it is a more principled approach than adopting the composite on faith. See the full list of 382 tested indicators here.

All results on this site are from hypothetical backtests with realistic transaction cost assumptions. They are not real trading results, do not account for execution risk beyond the modeled costs, and are not financial advice. Past backtest performance does not guarantee future results.