Eric Rosenbery is President and Trader for Rosenbery Capital Management, Inc. (RCM). In 1979, Mr. Rosenbery graduated from the University of Illinois with a Bachelor of Sciences degree in Physics. Mr. Rosenbery utilized his extensive mathematical background to formulate a technical trading system designed to overcome limitations common to small account management. RCM, a Subchapter S Corporation chartered in the State of Illinois, manages individual commodity trading accounts. It has been a Commodity Trading Advisor (CTA) since 1997.

RCM seeks the maximization of long-term asset appreciation relative to risk for accounts of $10,000 and multiples thereof by employing a proprietary technical trading program designed to overcome limitations common to small account management, The program entails the buying and selling of U.S. Treasury 5 and 10-year Treasury Note futures contracts, 30-year Treasury Bond futures contracts and 30-year Treasury Bond option contracts. Futures positions may be long or short, while option positions may be long only.

After graduation, Mr. Rosenbery was a product engineer for Borg-Warner Corporation, and then chief engineer for its purchaser, Echlin Manufacturing. In addition to engineering and supervisory duties, Mr. Rosenbery was responsible for the on-site re-qualification of Echlin's Brummer OEM product line at Ford Motor Company's European manufacturing facilities in Basildon, England and Cologne, Germany. He also served as the engineering liaison to Echlin's European sales representatives located in Hamburg, Germany.

In 1985, Mr. Rosenbery began research into technical trading methods. By 1987, he was trading sector mutual funds full-time for his own account and formed Oracle Weekly Publications, Inc., which later became Rosenbery Capital Management, Inc. In 1990, Mr. Rosenbery began trading commodity futures and concentrated his research efforts on 10-year Treasury Notes and 30-year Treasury Bonds. Progenitor I was Mr. Rosenbery's first system devoted solely to capital market interest rates. Further development led to Progenitor II (Pro 2.0), which greatly increases the already-profitable performance of Progenitor I.

There are a number of options for investors to employ RCM programs.

• An individual managed account with RCM at a $10,000 minimum for Progenitor II (Pro 2.0)
• A Silver Presidential Portfolio which includes 2.0
• A Gold Presidential Portfolio which includes Pro 2.0

PRICE THEORY. RCM believes that a non-random component exists within commodity prices and that price movement can be forecasted through mathematical analysis. Confirmatory to this belief, Rosenbery has identified four primary market mechanisms that account for much of the non-random behavior. Because commodities are traded by people, prices will be affected by market psychology and occasionally dominate normal supply and demand concerns until they are eventually corrected. Classical price theory addresses the linear interaction between supply and demand but doesn't address the non-linear interaction between the rational and the semi-rational. Markets react not only to supply and demand, but also to their own reaction to supply and demand, all the while leaving numerous telltale "fingerprints" on prices. Normally dismissed as noise or selectively attributed to affirmative market fundamentals, the imbedded non-linear information in seemingly mundane prices can aid in forecasting which way a seemingly quiet market will eventually break. Through repeated human iterations, this positively-reinforced market feedback may evolve into range-bound "cyclical" markets, break-out into "trending" markets or climax in a panic. Each of these market types are of limited duration and often dissolve shortly after being identified. By being on-board at the start, with minimal lag time, these market inefficiencies can be efficiently exploited. Further, knowing the mechanisms that caused these market inefficiencies can aid in forecasting the market's eventual discounting back to equilibrium.

SYSTEM DESIGN. Imbedded non-linear price information must be extracted and converted into a usable linear form because the act of trading, in itself, is linear. For example, a trader establishes a bullish position because his sentiment level reaches a specific threshold for bullish action. A trader does not, however, establish a bullish position because he reaches an undefined level of bearishness. A linear indicator generates signals that are directly proportional to the expected market outcome. In addition to its inherent rational logic, linear indicators can be combined to create a more powerful linear composite indicator. Here, strong sentiment in one direction will overrule weak sentiment in another direction by a quantifiable amount and render a more accurate forecast. Compounding this increase in accuracy, the random noise component of each indicator is largely canceled-out. This enhanced performance is extremely important because profits begin only after transaction costs are met. This enhanced composite indicator, more powerful than the sum of its parts, forms the heart of the Advisor's trading system. This forecasting power is measured as a signal-to-noise ratio, which when implemented into a completed program, translates into the reward-to-risk ratio of actual trading. The degree of complexity in this system is well-beyond the scope of conventional fundamental analysis and owes its feasibility to the power of today's computers. Fully objective and mechanical, the system generates unambiguous buy and sell signals, allowing RCM to concentrate on market monitoring and accurate order placement.

THE SYSTEM. The system is based upon rationally-derived algorithms of market mechanisms coupled to specific aspects of trader mass-behavior. At the core of the system are four independent and quantitative indicator modules that each describe a particular market mechanism. Each reacts with opposing biases to price movement, thereby largely nulling-out random price noise when combined. The result is a highly distilled composite with a high signal-to-noise ratio. Acting upon the composite is a trade shell program that generates the actual buy and sell signals. If the composite is strongly positive, a buy signal is generated. If the composite is strongly negative, a sell signal is generated. When the composite reverses polarity, positions are exited. A trade-saving filter consisting of robust short-term indicators is used to protect against "whip-saw" price action and control the frequency of trades in a cost-effective manner. In addition to lowering overall transaction costs, the lowered trading frequency minimizes the likelihood human error in program execution that is common to active trading.

The system derives its trading decisions primarily from daily settlement prices. Of all daily prices, the settlement price offers the truest insight into the state of the market. By closely monitoring prices during the final minutes of trading, the system generates buy or sell commands that are typically executed via market-on-close (MOC) orders. This eliminates the lag time of waiting until the next day's opening. Although one may question the propriety of acting on a price that technically hasn't occurred yet, the system usually generates buy and sell price ranges that are widely separated and rarely affected by moves occurring in the minutes between order placement and the market's close. Further, because of the system's trade-saving features, there is less than a 20% likelihood of any trade activity occuring on any given trading day. Adding to the benefit of end-of-day trading, markets are usually the most liquid at the close and result in a published price from which order fill quality can be definitively monitored.