|9/15/2012||Algorithm||TBD||10% performance based fee with watermarks||Medium|
Prospectus for the 412 Investments– returns:
What is the time period? 12/24/2014 to 3/26/2018
What percent total percent gain? 102.77%
What percent gain annually? 24.26%
What is the biggest period’s drawdown ? -7.2% loss
What gain does the system make in theory? 34%
What percent should be charged? 1%
Low risk loan rate annual? 7.13%
What annual gain if combined with the 7.13% loan? 15.69%
biggest day-to-day drawdown? -19.31% (during “brexit” on 1/20/2016)
There have been over 1000 tests run on the 412 Investments system in back-tests.
It has shown better than market returns in real-time, real money investments and in computed back tests (looking backwards in time) and in forward tests (with money that is not real being traded virtually and the results being tracked.)
Attached is a prospectus of all three sets of returns, starting with the most reliable: forward time financial returns with real money.
This is part of investments set up in three accounts, each doing a close approximation to real-time computerized trading of the stocks picked by the system.
2014-2015 3.74%returns (Compare to Nasdaq: 4806 to 4707, -2% loss)
2015-2016 18.17% returns (Compare to Nasdaq: 4707 to 4933, 4.8% gain)
2016-2017 35.53% returns (Compare to Nasdaq: 4933 to 6629, 34% gain)
2017-2018 0% returns (Compare to Nasdaq: 6629 to 6889, 4% gain)
No investment of stocks, to my knowledge, always returns a positive gain, every day, over the course of years.
The 412 Investment system is a computerized system designed to return average returns higher than the market without increasing risk. It is a stock picker based on fundamental data. It was developed using market data from 2000 – 2012 and verified in the last 6 years as continuing to beat the market.
Technically speaking, it was developed using a genetic program, a neural net, and a set of data points to identify those which give the closest correlation to market gains. After several models were developed, we used various testing methods such as Bayesian analysis and monte-carlo simulations to verify that it is “robust”, that is, that the results are not a fluke of random data.
The results are front and center, and updated regularly. My goal is to be transparent and show live results as they happen for each system that is supported, its risks, returns, and value gained.
All stock market investment involves risk of losing some or all of the money invested.
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