I have 2 independent data sets (1. 300 rows and 2.3000 rows) with 6 months trades observations for 50 traders. In both datasets I have: trader id, stock title, buy/sell volume, date of trade, sector of stock
My goal is to detect possible outliers (suspicious trades) in this two datasets.
- What algorithm you would recommend for this 2 tasks and why?
- What can we use for 1 task when we have average only 5-6 trades per trader?