New Investment Model by Analyticom Nearly Doubled the Market Return in the Last 12 Months
Developed by Dr. Dan Geller, the Scientifically Predictable Investment Model uses the Money Anxiety Index as a predictor of investor behavior and picks rising equities with high level of confidence
SAN FRANCISCO, Aug. 10, 2021 /PRNewswire/ -- Dr. Dan Geller's Scientifically Predictable Investment Model produced a return of 64.82%, outperforming the S&P 500 by 26.9% in the 12 months ending June 2021. The model, which uses the Money Anxiety Index as a predictor of investor behavior, was launched on July 1st, 2020 by Analyticom LLC after nearly a decade of research and development. The Scientifically Predictable projection is published monthly around the 10th of each month.
The model is based on decision science, which features two modes of financial response. The instinctive response, a.k.a. System 1, and the analytical response, a.k.a System 2. Scientific research shows that money anxiety is the alternator between the instinctive and analytical decision modes. Thus, when the level of money anxiety increases, investors tend to make instinctive investment decisions that are likely to be flawed and result in a loss. Scientifically Predictable was designed to neutralize instinctive decisions by following the science.
"Investing is a science because investors' behavior is predictable and repeatable," said Dr. Dan Geller President of Analyticom, and developer of the Scientifically Predictable investment model. "The track record of Scientifically Predictable in the past 12 months is a testament to that."
The Scientifically Predictable model was designed to outperform the market. Market indices, such as the S&P 500, are static and contain the same equities continually, thus unable to take profit when some equities are at the top. On the other hand, Scientifically Predictable features 5 top ETF that are projected to increase in the next 30-90 days, and when they do, they are sold at a profit and replaced with a new set of top 5 ETF for another cycle of profit taking.
The Scientifically Predictable Top Five ETF is a monthly projection of price and return with the highest level of statistical confidence. The projection features the price increase of each of the five ETF for the coming 30 days, as well as the projected rate of return. Additionally, each ETF price projection contains an upper and lower level limit, which indicates how high or how low the price can go in the event of an unusual economic of financial event.
The monthly projection contains all the statistical analysis pertaining to each of the featured ETF, thus no additional research and analysis are needed. Additionally, repositioning of the ETF is done only once a month, and in some cases, when the price and return trend continues, no repositioning needs to take place. The average repositioning is about 30 minutes each month. Scientifically Predictable is available for monthly subscription and can be canceled at any time. A video featuring the scientific framework of the model is provided on the home page.
About Analyticom LLC
Analyticom LLC is a behavioral economics and finance firm focusing on developing predictive models for financial behavior. The company is a pioneer in developing a scientifically predictable model for the equity market based on the level of money anxiety. The Scientifically Predictable model projects the rate and return of ETF based on a predictor that is featured in the study "Dynamics of Yield Gravity and the Money Anxiety Index" and has been peer reviewed and published in the Journal of Applied Business and Economics.
Disclaimer
The authors of these documents are not brokers, dealers or registered investment advisors. The information contained in all featured documents are opinions only and are not intended as a solicitation, an offer, a recommendation to buy, hold, or sell any securities, products, service, investment or participate in any particular trading scheme in any jurisdiction
Contact:
Dr. Dan Geller
415-891-3093
[email protected]
SOURCE Analyticom
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