Forecasting Stocks like Species This is a powerful, user-friendly, and well-documented program capable of making price forecasts with improved accuracy further into the future. Its uniqueness is a science-based approach that treats stocks like species and the stock market as an ecosystem. But it does not offer pushbutton solutions. Every user will not necessarily obtain the same answer, and some users will perform better than others. However, everyone will improve with time. As with a quality musical instrument: the more you practice, the better the results.
There are many techniques to forecast the short-term future of stock prices (moving averages, the momentum method, point-&-figure charts, etc.), but none that attempt to understand the longer-term future of stocks. Here we offer such a method by exploiting the law of natural growth in competition, otherwise known as Darwinian competition or simply survival of the fittest.
Originally developed to study the evolution of species populations the approach involves the S-shaped pattern (S-Curve) followed by a rabbits population as it passes from the very first pair of rabbits on the grass range to the final maximum number of rabbits the range can feed. The approach has been extensively used for product sales in the marketplace but also for a multitude of other human endeavors; see for example, the groundbreaking book Predictions by Theodore Modis, Simon & Schuster, New York, 1992.
To use this approach in the stock market we must shift our attention away from stock prices because prices are not physical variables, they do not constitute limited resources and consequently they do not obey the law of growth in competition. Instead we must study the evolution of the share volume and share value exchanged. Once their evolution has been understood and forecasted their ratio will give us the stock-price forecast. A detailed discussion can be found in the book by Theodore Modis, An S- Shaped Trail to Wall Street, Growth Dynamics, Switzerland, 1998.
The program allows you to forecast all the stocks listed in the NYSE and the NASDAQ as often as you want. You can use monthly, quarterly, or semiannual data. The price forecasts are given with estimated errors defining the 90% confidence level.
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