No saved results · Entries · 2026-09-22
Would a limit order at Point D (or a 50% pullback) beat the confirmation entry?
What this means
This tested resting a buy limit at Point D or at a 50% pullback instead of buying at confirmation. Nothing from the original run was saved, and it used a hindsight zigzag. A later, separate study (transcript only) found a limit at D did no better than random entries on 1h (−0.02R) and worse on 4h (−0.25R), but that cannot be checked. Nothing firm can be concluded; a proper test would place the limit orders inside TradingView's own bar-by-bar engine and save the logs.
The explanation is our best reading; the data shows the result but not the cause directly.
By timeframe
| Timeframe | Verdict | n | Result |
|---|---|---|---|
| 15-minute | Not tested: not tested yet: no 15-minute price data; needs 15m prices or a TradingView run; skipped anyway: original not reproducible (see tradingview_runs.md) | ||
| 1-hour | Not tested: not tested: fillable with 1h prices (2023-11+), but skipped: original has no saved output (console only, look-ahead zigzag); not reproducible; HAV limit-at-D figures exist only in a transcript | ||
| 4-hour | Not tested: not tested: fillable with prices, but skipped: original has no saved output (console only, look-ahead zigzag); not reproducible | ||
| Daily | Not tested: not tested: fillable with daily prices, but skipped: original has no saved output (console only, look-ahead zigzag); not reproducible | ||
- Hypothesis
- A buy limit at D, at D+15% or at a 50% pullback improves R-multiple, win rate and expectancy.
- Method
- Own Python sim, yfinance 1h; variants: limit at D, keep original stop distance, target = confirmation price, RSI/S3 filters.
- Result
- No saved output (console only). In the later HAV study (transcript only) a limit order at the HAV D level was -0.02R vs random on 1h and -0.25R on 4h.
- How much to trust it
- Low: hindsight zigzag; nothing saved
- Did it change the live rule?
- No.
Scripts and data for this study will be linked here when the research code is published on GitHub.
Education and research only. Not financial advice. Backtests use today's index members (survivorship bias).