msr

Frank A. Peluso
President & CEO

Arma virumque cano, Trojae qui primus ab oris Italiam fato profugus Laviniaque venit Litora -- multum ille et terris jactatus et alto Vi superum, saevae memorem Junonis ob iram,memorem Junonis ob iram, Multa quoque et bello passus, dum conderet urbem Inferretque deos Latio -- genus unde Latinum Albanique patres atque altae moenia Romae.

	Total	Annualized
	Return	Return
1 Year
MSR	5.52%
SP500	5.49%

5 Years
MSR	98.30%	14.70%
SP500	82.90%	12.80%

10 Years
MSR	166.80%	10.30%
SP500	77.50%	5.90%

15 Years
MSR	699.80%	14.90%
SP500	347.10%	10.50%

20 Years
MSR	1626.30%	15.30%
SP500	833.40%	11.80%

25 Years
MSR	5100.30%	17.10%
SP500	1898.90%	12.70%

30 Years
MSR	17092.00%	18.70%
SP500	3758.90%	12.90%

35 Years
MSR	23571.50%	16.90%
SP500	3722.40%	10.90%

37 Years
MSR	36211.30%	17.30%
SP500	5099.10%	11.30%

The Market Systems Research portfolios have out-performed the S&P500 in 33 of 36 consecutive two-year time periods.

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Since 1970, the basic MSR test portfolios have remained 100% long, with stocks upgraded automatically at six month intervals.

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The Market Systems Research Stock Selection portfolios are composed of institutional quality issues with relatively high capitalization. Since 1975, the stocks have been selected automatically from the S&P 500 list (excluding utilities).

Process - Unique Features - Methodology

The MSR mathematical model is based on computer studies, which have been interpreted to indicate that the price patterns of individual stocks are affected statistically by a series of short-term, intermediate-term and long-term cycles, whose frequencies have been approximately determined. This study anticipated the field of Chaos Theory by a number of years.

The creator of the system, Frank A. Peluso, is a recipient of a graduate fellowship in mathematical physics at Princeton University. Mr. Peluso has related individual stock price patterns to the type of solutions of differential equations often employed in physics, but which appear to have a wide area of application.

After twenty years of published research, the results were reviewed by Professor Paul Zarowin, professor of mathematics at New York University, and found to have a high degree of statistical significance.

The model uses proprietary indicators, which act as filters to help isolate the positions and magnitudes of individual price cycles. The superposition of this data is then projected into the future and Selection Ratings are assigned to each stock based upon their estimated likelihood of price performance during the next six month to one year time period.