The best indicator for Netflix (NFLX)
We backtested 20 indicators across daily, weekly and hourly charts on real Netflix (NFLX) history. Here's what actually worked — risk-adjusted, out-of-sample, with costs.
Rate of Change
On the weekly chart, this is the strongest risk-adjusted edge we found for Netflix (NFLX) over ~24.1 years — beating buy-and-hold by 1.2% CAGR.
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 | Rate of Change ✓ | Weekly | 32.2% | 0.88 | -53.8% | 56.2% | 64 | 1.2% |
| 2 | Donchian Breakout ✓ | Weekly | 34.4% | 0.94 | -52.5% | 78.6% | 14 | 3.4% |
| 3 | RSI Trend (>50) ✓ | Weekly | 30.1% | 0.84 | -56.2% | 53.3% | 45 | -0.9% |
| 4 | EMA 20/50 Cross ✓ | Daily | 28.9% | 0.83 | -63.5% | 48.1% | 54 | -2.4% |
| 5 | RSI Trend (>50) ✓ | Daily | 27.9% | 0.82 | -68.0% | 41.8% | 275 | -3.4% |
| 6 | Bollinger Breakout ✓ | Weekly | 23.6% | 0.8 | -51.0% | 72.7% | 22 | -7.4% |
| 7 | EMA-10 Trend ✓ | Weekly | 27.5% | 0.8 | -61.8% | 49.0% | 100 | -3.5% |
| 8 | Rate of Change ✓ | Daily | 25.3% | 0.78 | -53.1% | 43.1% | 362 | -6.0% |
| 9 | ADX / DMI ✓ | Weekly | 24.7% | 0.75 | -65.3% | 51.2% | 41 | -6.4% |
| 10 | Donchian Midline ✓ | Weekly | 25.0% | 0.75 | -62.4% | 48.4% | 64 | -6.0% |
| 11 | SMA 50/200 Cross ✓ | Daily | 28.4% | 0.81 | -59.6% | 69.2% | 13 | -2.9% |
| 12 | MACD ✓ | Weekly | 21.8% | 0.7 | -62.3% | 54.7% | 53 | -9.2% |
| 13 | EMA 50/200 Cross ✓ | Daily | 26.8% | 0.78 | -58.4% | 66.7% | 12 | -4.5% |
| 14 | EMA-10 Trend ✓ | Daily | 18.2% | 0.62 | -70.6% | 46.8% | 509 | -13.1% |
✓ = held up out-of-sample. Hypothetical, costs included. See methodology.
For Netflix (NFLX), Rate of Change on the weekly 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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