Three Divergent Strategies


PROJECT 304 is a collaborative research and investment team founded to study the behavior of financial markets and to create systematic strategies to participate in those markets.  We are active in three non-correlated strategies:
 
  • Angel Investing of early stage companies as part of highly respected groups such as Heartland Angels.  These are long-term commitments that require a great deal of investigation and due diligence.  This is a highly interesting area and we publish a magazine covering this unique world.  www.ChicagoVentureMagazine.com 

  • Short-term trading of  non-discretionary automated models using statistical testing and walk-forward analysis to participate in the Financial Futures markets.  This area requires the largest commitment in time and creativity.   

  • Traditional participation in the Stock and Bond markets on a medium-term time frame, using constantly-evolving strategies that often employ margin to boost the yield of an otherwise low performing but highly secure asset class. 
 
Project 304 research is proprietary, but from time to time we publish an article or essay on a specific subject.  See white papers at our Market Theory Site:  http://home.comcast.net/~countertrender/Countertrender.html

Two experimental indicators are featured on this page. Both are typical of our work. Both use the same logic to accomplish a different task. View the sample charts below. The rationale and code for these indicators is available on a white paper linked to this site.


PROJECT 304 BANDS - Expected price range based on trend, at user-set standard deviation

PROJECT 304 TRAILING STOP - The trailing stop uses that same information to exit a trade


 
View the theory, math and code for these indicators in the paper :
THE STOP LOSS—A Statistical Approach
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See more articles at the site:
COUNTERTRENDER - Market Theory by John Jonelis
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Project 304 is responsible for over 300 unique technical indicators and models, including REVELATION, a proprietary suite of automated trading algorithms that returned an average of 60% return per year at 25% margin for 15 years without a losing year.   

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