The best indicator for Pyth
We backtested 382 indicators across daily, weekly and hourly charts on real Pyth history. Here's what actually worked — risk-adjusted over the full backtest, with costs, and checked out-of-sample.
Where Pyth stands
Computed from our own daily OHLCV history, not quoted from a third party. Moving averages use closing prices; "52-week" is the last 252 trading sessions.
Connors RSI
On the daily chart, this is the strongest risk-adjusted edge we found for Pyth over ~4.2 years — beating buy-and-hold by 62.3% CAGR.
Pyth on the daily chart
The timeframe our backtest found best for this asset. The chart is live market data; the results above are hypothetical and historical.
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The winner on each chart
Every indicator, ranked
Ranked by Sharpe (risk-adjusted return). Hypothetical, fees included.
| # | Indicator | TF | CAGR | Sharpe | Max DD | Win | Trades | vs B&H |
|---|---|---|---|---|---|---|---|---|
| 1 | Connors RSI ✓ | Daily | 35.5% | 0.72 | -60.2% | 59.6% | 57 | 62.3% |
| 2 | Connors RSI-2 ✓ | Daily | 32.9% | 0.69 | -55.6% | 61.4% | 57 | 59.7% |
| 3 | Order-Flow Reversion ✓ | Daily | 33.2% | 0.69 | -50.7% | 61.1% | 18 | 60.0% |
| 4 | Schaff Trend Cycle ✓ | Daily | 28.4% | 0.64 | -40.6% | 51.4% | 35 | 55.3% |
| 5 | Keltner Mean-Reversion ✓ | Daily | 28.2% | 0.79 | -44.6% | 75.0% | 12 | 55.0% |
| 6 | Fisher Center-of-Gravity ✓ | Daily | 23.7% | 0.59 | -72.2% | 48.5% | 99 | 50.5% |
| 7 | Detrended Price Osc. ✓ | Daily | 20.2% | 0.57 | -67.8% | 54.5% | 110 | 47.0% |
| 8 | Bollinger Mean-Reversion ✓ | Daily | 21.3% | 0.56 | -63.6% | 63.2% | 19 | 48.1% |
| 9 | Fibonacci Bands ✓ | Daily | 21.3% | 0.56 | -63.6% | 63.2% | 19 | 48.1% |
| 10 | Elastic VW MA ✓ | Daily | 10.1% | 0.44 | -75.0% | 34.1% | 44 | 37.0% |
| 11 | CMO (21) ✓ | Daily | 10.4% | 0.44 | -75.4% | 40.5% | 37 | 37.2% |
| 12 | VWAP Bands ✓ | Daily | 10.4% | 0.43 | -54.9% | 57.1% | 21 | 37.2% |
| 13 | FRAMA 10/30 Cross ✓ | Weekly | 33.9% | 0.74 | -53.3% | 41.7% | 12 | 79.4% |
| 14 | Fractal Adaptive MA ✓ | Daily | 4.5% | 0.34 | -70.8% | 34.9% | 106 | 31.3% |
✓ = held up out-of-sample. Hypothetical, costs included. See methodology.
The question doesn't apply here. Buy-and-hold on Pyth lost money across the out-of-sample window in 195 of 195 tests, so there is no positive benchmark to lever toward — clearing a negative bar is a much weaker claim than beating a real one, and we keep the two apart rather than counting it as a win. How we compute that
For Pyth, Connors RSI on the daily timeframe gave the best balance of return and risk in our test. It beat buy-and-hold — but remember: this is a hypothetical backtest of a standard rule, not a recommendation. Markets change. See the methodology and disclaimer.
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