Return vs. Risk

Past Performance

In machine learning intelligence everything is configured as per investors appetite. The unrealized stocks leads to risk and realized settlements leads to return. The ratio of Return vs. Risk are usually 1:5.  Example : Investor seeking 3% Gain a month would be willing to take 15% risk. If investments are not liquidated the risk converts to return within an extended period of time. Within same day 68% recommendation settle, within 30 days 26% recommendation settle , over 30 days 4% the remaining 2% of investment gets to longer settlement time.

So if an investor liquidated after 30 days as an example most likely would lose 6% of investment amount and if untouched the 6% would convert to gain after few months. Remaining 94% are going to be profitable within one month as settlements happen. So mathematically investment of 100k would have 6K unsettled for extended period of time and 94K would generate profits within one month at an average of 0.56% for every settlement.

The algorithm generates breakouts which are bask tested and would give an idea to investors the potential returns from breakouts which leads to profits. All investors are enjoying a pie of it based on Available Fund and Buying Power.


Difficulty viewing then CLICK HERE

CLICK HERE to witness investors enjoying a pie of it with limitation of Funds and Buying Power. One would need 1.5 Million to exhaust all breakouts which will give identical results as back tested with an exception to brokers commission. 

Due to confidentiality reason only one investors account with trade confirmation is published. All other investors doing identical or better with software optimization. Can be proved if requested.