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Investment thesis
This article will help explain our various ongoing research for the most likely identification of near-term capital gain prospects and their capital loss risk potentials.
We employ behavioral analysis to identify prospects of gain and loss for individual securities within predictable time horizons of months rather than the several years normally used previously in 20and-Century ratings.
If you are new to this analysis, please temporarily explore this brief explanation.
Behavioral analysis
Changes in communication, competitive techniques, information technology, computing and data technology, as well as medical and other scientific technologies have all contributed to the necessary evolution in the way the assessment of titles must be conducted,
Most prevalent among evolving technologies is the effect on the speed of change and the shortening of the time during which the effects of progress are felt.
Advances in communications and information technology have transformed the way stock markets work and, as a result, the behavior of major investors. Stock prices now move normally for periods of a year elapsed at rates within ranges that are generally several times that of the trend growth of the underlying stock.
Meaning that for part of the time of year, their prices pull back and consume time investments that cause trend rates of “growth” to be much lower than what their best, shorter up periods provide.
Advances in information technology are encouraging investment professionals (market-making [MM] community) to protect the capital they must put at risk to do their job. These actions cause equity and derivatives markets to become more integrated than they were for most of the 20th century.
We therefore study what the behavior of the pros causes in the markets for price-changing “insurance” derivatives, to understand the extent to which it is reasonable to believe that the prices of specific stocks and ETFs can evolve, both upwards and downwards, over the coming months. .
This analysis has been conducted daily without significant change for over a decade on over 3,500 widely held and actively traded stocks and ETFs. The resulting price range predictions provide an actuarial history (unmatched elsewhere in the investment community) of subsequent market prices, as a testament to the strength or weakness of the predictions made previously.
Short-term price gains are most important for investors who are now beginning to build portfolio wealth and exploring how best to do so, or for investors who have realized that retirement plans established years ago sooner will likely not be achieved at current rates of investment wealth accumulation.
Active investing, where capital is constantly put to work in the best current situations to generate profits over predictable time horizons, is the strategy most likely to produce what is needed now, at least risk. But active investing needs guidance on what to do, when to do it, and how hard.
Conclusion
Standard “fundamental analysis” fails to provide adequate value comparisons in its price/earnings calculations because the ratios bear no relation to the actual risk dimensions.
Accepting “volatility” (measured by the standard deviation of earnings from an earnings trend) as a risk cannot separate the beneficial from the harmful effects of these deviations.
By having trained observers determine the extent of price fluctuation protections necessary to maintain market continuity as the definition of price risk and price reward, and their balance with each other other as Risk-reward ratio creates a much clearer and more useful tool for comparing investment alternatives.
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