Trading Research Share Report
Batch second_pass_20260311 · Last updated 2026-03-11T09:42:39Z
Executive summary
- This batch is an early research readout rather than a final strategy verdict.
- The least bad average segment was Breakout on 1h data at -1.86%.
- The weakest average segment was Momentum on 30m data at -16.13%.
- The best run that actually traded was Mean Reversion · ETH · 1h · lookback 6 / hold 4 with total return 3.38%.
- Interpret these as research signals about direction and quality, not as production-ready trading systems.
Best trading run in this batch: Mean Reversion · ETH · 1h · lookback 6 / hold 4
Assets covered
3
BTC, ETH, SOL
Total experiment runs
54
Research batch
Best observed return
3.38%
Including all runs
Scope and assumptions
Exchange: binance
Fee: 10.0 bps
Slippage: 5.0 bps
This report summarizes research tests on BTC, ETH, and SOL using 15m, 30m, 1h data, with 4h available as higher-timeframe context. The goal is not to prove a strategy works, but to learn which directions deserve deeper study.
Average return by strategy and timeframe
Mean Reversion / 15m
-2.89%
Mean Reversion / 1h
-6.25%
Mean Reversion / 30m
-13.97%
Current research conclusions
This batch was used to decide whether more selective signals and larger timeframes improved the baseline results.
- 5m baseline strategies currently look weak under the present cost assumptions.
- 15m results are generally less bad than 5m results in the current baseline suite.
- Breakout currently appears less bad than momentum and mean reversion in the first pass.
- These are baseline findings, not final conclusions.
Show detailed conclusions and decision trail
- This pass moved away from raw zero-threshold signals and toward more selective entries.
- The strongest average strategy/timeframe bucket was Breakout on 1h at -1.86%.
- The weakest average bucket was Momentum on 30m at -16.13%.
- Across timeframes, 15m held up best on average at -4.49%, while 30m was weakest at -11.29%.
- We now have genuinely positive runs, led by Mean Reversion · ETH · 1h · lookback 6 / hold 4 at 3.38%. That is a real improvement over the first pass.
- The decision to move forward now comes from selective evidence rather than broad optimism: a few setups are starting to survive trading costs.
- The next direction should emphasize the most promising lanes rather than another broad sweep: 1h breakout and higher-threshold mean reversion deserve more attention than raw momentum.
- This decision trail matters because the project is intentionally trying to learn honestly from negative as well as positive evidence.
Top 10 runs
Best-performing runs in this batch, still subject to the current assumptions and sample window.
| Run | Trades | Total Return | Drawdown | Win Rate | Profit Factor |
|---|
| Mean Reversion · ETH · 1h · lookback 6 / hold 4 | 26 | 3.38% | -7.84% | 50.00% | 1.221 |
| Mean Reversion · SOL · 15m · lookback 6 / hold 4 | 10 | 2.73% | -1.73% | 70.00% | 2.451 |
| Breakout · BTC · 1h · range 12 / hold 3 | 9 | 1.66% | -3.39% | 33.33% | 1.465 |
| Mean Reversion · BTC · 15m · lookback 6 / hold 4 | 9 | 1.42% | -1.00% | 55.56% | 2.038 |
| Breakout · BTC · 1h · range 24 / hold 6 | 7 | 0.98% | -2.02% | 57.14% | 1.352 |
| Breakout · BTC · 30m · range 24 / hold 6 | 11 | -0.07% | -4.69% | 27.27% | 0.988 |
| Momentum · BTC · 15m · lookback 6 / hold 6 | 15 | -0.37% | -1.79% | 40.00% | 0.917 |
| Breakout · ETH · 1h · range 12 / hold 3 | 6 | -0.75% | -2.76% | 50.00% | 0.816 |
| Mean Reversion · ETH · 15m · lookback 6 / hold 4 | 9 | -0.95% | -1.38% | 44.44% | 0.607 |
| Breakout · BTC · 30m · range 12 / hold 3 | 15 | -1.06% | -4.37% | 40.00% | 0.854 |
Bottom 10 runs
Weakest runs in this batch. These are useful because they show what clearly did not work in this pass.
| Run | Trades | Total Return | Drawdown | Win Rate | Profit Factor |
|---|
| Momentum · SOL · 30m · lookback 3 / hold 3 | 76 | -21.60% | -22.63% | 28.95% | 0.493 |
| Mean Reversion · BTC · 30m · lookback 3 / hold 2 | 92 | -19.62% | -20.63% | 32.61% | 0.421 |
| Mean Reversion · SOL · 30m · lookback 3 / hold 2 | 101 | -19.17% | -21.84% | 31.68% | 0.530 |
| Momentum · ETH · 30m · lookback 3 / hold 3 | 80 | -18.51% | -19.15% | 32.50% | 0.505 |
| Mean Reversion · ETH · 30m · lookback 3 / hold 2 | 94 | -18.04% | -18.32% | 35.11% | 0.512 |
| Momentum · SOL · 30m · lookback 6 / hold 6 | 40 | -15.97% | -15.97% | 30.00% | 0.452 |
| Mean Reversion · ETH · 30m · lookback 6 / hold 4 | 43 | -14.82% | -15.63% | 37.21% | 0.443 |
| Momentum · ETH · 30m · lookback 6 / hold 6 | 40 | -14.28% | -14.58% | 27.50% | 0.514 |
| Momentum · BTC · 30m · lookback 3 / hold 3 | 71 | -13.80% | -13.83% | 33.80% | 0.503 |
| Momentum · SOL · 1h · lookback 6 / hold 6 | 24 | -13.03% | -13.81% | 37.50% | 0.442 |
How to read this report
This batch evaluates three strategy families across 15m, 30m, 1h, with 4h data reserved for context/regime use.
- Data basis / timeframe: the actual experiments in this report are based on 15m, 30m, 1h bar data, with 4h available as higher-timeframe context.
- Momentum means buying after a recent upward move and testing whether that move continues.
- Mean Reversion means buying after a sufficiently large adverse move and testing whether price snaps back.
- Breakout means buying when price clears a recent range by more than a minimum amount, on the assumption that the move may be starting a new leg.
- lookback <number> is how many bars backward the strategy looks when measuring the recent move or condition.
- hold <number> is how many bars the position is held after entry before exit in this simplified backtest.
- Trades is the number of completed trades the strategy actually took during the tested period.
- Total Return is the cumulative strategy result across the full tested period, after the current fee and slippage assumptions.
- Drawdown is the worst peak-to-trough decline of the strategy equity during the run.
- Win Rate is the fraction of completed trades that were profitable.
- Profit Factor is gross profit divided by gross loss; above 1 is generally better, below 1 means losses outweighed gains.
- Thresholds were added because the first-pass raw strategies traded too often and were too easily overwhelmed by costs.
- Fees and slippage are included in all runs, so results reflect friction rather than idealized fills.