The short answer
Yes, modestly, and it is the only rule of the dozens we tested that passed. When a US500, US100 or US30 day closed in the bottom fifth of its range, buying after the close and selling before the next daily close made +0.018R a trade in 2021-24, +0.066R in year 1 and +0.100R in year 2 after costs, positive on all three indices in every period and better than buying on random days. It is a small, repeatable edge of about 40 trades a year per index, not a forecast of any single day, and past results do not guarantee future ones.
What we tested
- Markets
- US500, US100, US30 (index CFDs)
- Period
- Dec 2020 to Oct 2026 (daily bars, one-minute execution from Oct 2024)
- Internal bar strength (IBS) = (close - low) / (high - low) of the day just closed. Below 0.2: buy.
- Tested exit: the next daily close, with a protective stop of 2.5 x ATR(20). The live version exits 35 minutes before that close to avoid the overnight swap. A Friday signal enters at the next open and exits on Monday, so it never holds over a weekend.
Results
| Period | Trades | Average R | Profit factor | Long on random days | p vs random | Indices positive |
|---|---|---|---|---|---|---|
| 2021-24 | 484 | +0.018R | 1.16 | -0.008R | 0.07 | 3 of 3 |
| Year 1 | 114 | +0.066R | 1.72 | +0.005R | 0.06 | 3 of 3 |
| Year 2 | 116 | +0.100R | 2.54 | +0.013R | 0.001 | 3 of 3 |
With the live exit (35 minutes before the next daily close): +0.017R, +0.062R and +0.096R.
What it means
- Thresholds from 0.1 to 0.3 were all positive in both recent years, so the result is not one lucky setting.
- It worked in rising and falling market structure; it was weaker when structure was mixed.
- It was weak on European indices (GER40, UK100), so we apply it to US indices only.
- Two years of simulated results by risk profile, with every trade downloadable, are in the backtest report.
Limits of this test
- Simulated on one broker's prices and costs; live fills, spreads and swaps can differ.
- The edge has been strongest in the last two years and small in 2021-24; it may shrink again.
- About 40 trades a year per index: a single month says little.
Frequently asked questions
What is the internal bar strength (IBS) strategy?
IBS measures where a day closed within its range: (close - low) / (high - low). The rule buys US stock indices after a day closes in the bottom fifth of its range and sells before the next daily close.
Is the IBS strategy profitable?
In our simulated test on US500, US100 and US30 with real costs, it averaged +0.02R to +0.10R per trade in 2021-26 and was positive on all three indices in every period. Simulated results do not guarantee future results.
How every test on these pages works
- Prices: the broker's own bars from an FTMO cTrader account. Fills are simulated minute by minute on one-minute bars; when one minute touches both the stop and the target, the stop is assumed to fill first.
- Costs: the broker's bid/ask spread measured by hour of day, commission per market, and the broker's own overnight swap rates for anything held past the daily rollover.
- Periods: year 1 = 24 Oct 2024 to 23 Oct 2025, year 2 = 24 Oct 2025 to 24 Oct 2026. Daily rules also use Dec 2020 to Oct 2024 ("2021-24"). Rules are written down before testing and are not tuned on the period that judges them.
- Controls: every rule is compared with entries that have no reason behind them (random sides, random days, or the same rule at fake levels), so a result has to beat chance, not just be positive.
- R is the trade's risk (entry to stop). An average of +0.10R means the average trade made a tenth of what it risked; -0.10R means it lost a tenth.
The full results for the rules RezSync Algo trades, by market and risk profile with every trade downloadable, are in the backtest report.
Related research
Research, not financial advice. These are simulated results on historical prices: they involve no real money, are produced with hindsight of the rules, and past results do not predict future ones. Costs and fills are modelled, and your broker's prices and costs will differ. Trading leveraged products carries a high risk of losing money; test on a demo account first.