@Disagree
I've built a few backtest models. Some with very impressive returns until retail brokerage fees were included.
With brokerage, in a ranging or choppy market, many near break-even trades became losers which severely impacted the CAGR.
I the end I found best results using highly responsive sell triggers (Like Parabolic SARs or 4/9 MA) and less responsive buy triggers such as displaced price oscillators.
Have you use volatility filters or included brokerage in your calculations?
FLT - Machine Learning Experiment, page-5
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$17.22 |
Change
0.090(0.53%) |
Mkt cap ! $4.754B | |||
| Open | High | Low | Value | Volume |
| $17.13 | $17.59 | $17.12 | $8.528M | 491.2K |
Buyers (Bids)
| No. | Vol. | Price($) |
|---|---|---|
| 4 | 67 | $17.22 |
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| Price($) | Vol. | No. |
|---|---|---|
| $17.23 | 350 | 5 |
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