MinSizeKmeans
MAGIST-Algorithm
| MinSizeKmeans | MAGIST-Algorithm | |
|---|---|---|
| 1 | 1 | |
| 80 | 5 | |
| - | - | |
| 0.0 | 3.8 | |
| about 3 years ago | 9 months ago | |
| Python | Python | |
| GNU General Public License v3.0 only | GNU General Public License v3.0 only |
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MinSizeKmeans
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Preliminary Evidence that Retail Trades can be Identified and Counted on the Tape
Sure so basically I scraped the volume from the SEC report figure depicting 'Buy' volume by measuring pixels between ticks on the y axis. I also downloaded all regular session trades for the dates in that figure and after some rounds of data cleaning (ie one hot encoding trade condition data) I ran the trades from the first half through an implementation of kmeans clustering with minimum cluster size constraints set to cluster the trades weighted by volume into 2 groups with minimum weight of the volume scraped from the candle from the SEC report. This clustering takes a long time to run so I've only managed to process that first bar.
MAGIST-Algorithm
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AI Startup Closer than EVER to GENERAL INTELLIGENCE!
If you want to see this for yourself, please visit our GitHub Repository and website!
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