Add docs on choosing data and bars processing #2195
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cjdsellers
approved these changes
Jan 8, 2025
| :::tip | ||
| For some trading strategies, it can be practical to start development with bar data to validate core trading ideas. | ||
| If the strategy looks promising, but is more sensitive to precise execution timing (e.g., requires fills at specific prices | ||
| between OHLC levels, or uses tight take-profit/stop-loss levels), you can then invest in higher granularity data |
cjdsellers
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cjdsellers
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Jan 8, 2025
| - Uses bar structure to estimate likely price path: | ||
| - If Open is closer to High: processes as `Open → High → Low → Close` | ||
| - If Open is closer to Low: processes as `Open → Low → High → Close` | ||
| - Testing shows this approach achieves 75-85% accuracy in predicting correct High/Low sequence (compared to statistical 50% accuracy with fixed ordering) |
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If we start quoting research and stats, it might be worth adding some citations if possible?
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Mhm, good point - reality is - it is my own script, testing 1-year of data with this heuristics:
Current fixed OHLC approach = 50% correct
- 50% correct simulations
- 50% incorrect simulations
Proposed heuristic approach = 85% correct
- 70% of bars have significant directional bias (>35% of bar range difference between open-close)
- Remaining 30% split roughly 50/50
- Net result: ~85% accurate simulations (70% + half of the remaining 30%)
- Only ~15% potentially incorrect simulations
If you are OK with it, I can formulate the reasoning behind and add it to the note of these docs.
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Yes, I think that's great - even if we link to a gist or markdown you can provide for the above 👍
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I am making a note and it will be added tommorrow 👍
Pushkarm029
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Jan 15, 2025
- Order of OHLC in bar processing - Choosing data: cost vs. accuracy
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Docs were update on both topics - as I promised.