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, out-of-sample, with costs.
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.
Order-Flow Reversion
On the daily chart, this is the strongest risk-adjusted edge we found for Pyth over ~3.8 years — beating buy-and-hold by 80.3% 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 | Order-Flow Reversion ✓ | Daily | 36.5% | 0.72 | -50.7% | 58.8% | 17 | 80.3% |
| 2 | Connors RSI ✓ | Daily | 35.9% | 0.71 | -60.2% | 58.2% | 55 | 79.7% |
| 3 | Keltner Mean-Reversion ✓ | Daily | 31.5% | 0.83 | -44.6% | 75.0% | 12 | 75.3% |
| 4 | Connors RSI-2 ✓ | Daily | 28.4% | 0.64 | -55.6% | 57.7% | 52 | 72.2% |
| 5 | Bollinger Mean-Reversion ✓ | Daily | 23.1% | 0.58 | -63.6% | 61.1% | 18 | 66.9% |
| 6 | Fibonacci Bands ✓ | Daily | 23.1% | 0.58 | -63.6% | 61.1% | 18 | 66.9% |
| 7 | Schaff Trend Cycle | Daily | 21.7% | 0.54 | -40.6% | 48.4% | 31 | 65.6% |
| 8 | Fisher Center-of-Gravity ✓ | Daily | 16.8% | 0.51 | -72.2% | 48.9% | 90 | 60.6% |
| 9 | Detrended Price Osc. | Daily | 11.6% | 0.48 | -67.8% | 52.9% | 102 | 55.5% |
| 10 | VWAP Bands ✓ | Daily | 11.5% | 0.45 | -54.9% | 57.1% | 21 | 55.3% |
| 11 | Demand Index | Daily | -5.3% | 0.28 | -70.4% | 45.5% | 33 | 38.5% |
| 12 | Bullish Harami | Daily | 0.6% | 0.24 | -49.6% | 34.4% | 90 | 44.5% |
| 13 | Morning Star | Daily | 1.7% | 0.21 | -54.2% | 51.9% | 27 | 45.6% |
| 14 | FRAMA 10/30 Cross | Weekly | 10.6% | 0.45 | -53.3% | 40.0% | 10 | 73.9% |
✓ = 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, Order-Flow Reversion 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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