Below you will find the theoretical returns of one of our recent winning methodologies that was optimized using Reinforcement based Machine Learning. The back testing of this strategy is reliable due to its relatively 'straightforward' nature. Additionally, it should be noted historic performance is not necessarily a guarantee of future performance especially since the yearly win percentage is fairly volatile depending on market dynamics.

We currently have one more profitable methodology however due to its complexity, back testing is impossible. I will add its return numbers once our designated test period has ended and I'm able to optimize it with Machine Learning.

Strategy #1 Returns

Average Daily Return based on 1 year back testing: 0.43% or 110.15% for that year.

Average Daily Return based on 5 years back testing: 0.29% or 73.89% a year.

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