Our Methodology

One of main thrusts of our approach is state-of-the art dynamic cycle analysis to estimate turning points in time for financial markets. We employ the latest scientific advances in time-frequency analysis to identify most recent cycle periods, amplitudes and phases, as cycles themselves vary over time (Hurst principle of variability). Cycles attributes may oscillate over time due to the influence of larger cycles or some cycles even may change for longer periods of time due to some fundamental factors. Our dynamic time-frequency cycle analysis attempts to detect these variations in near real-time. We also use traditional cycle analysis approaches such as Hurst methodology and methods based on centered moving averages (CMAs) and sometimes even T-theory. For price level projections and reversal points we use multiple methods. From the cycle methods we employ forward line of demarcation (FLD) and converged CMA to obtain price projections and potentially reversal levels. These two methods provide fairly similar levels.

Another benefit of our approach is Elliott Wave (EW) analysis integrated with Fibonacci levels as waves exhibit certain typical Fibonacci relationships. This method is used for estimate price projection and reversal levels, often supplemented by traditional technical analysis methods such as price channels and support/resistance levels, positive/negative divergences in momentum indicators, etc. Our EW analysis is strengthened by our cycle analysis to track most viable EW counts (one of disadvantages of EW theory is that there are many candidate count candidates and, thus prone to the subjectivity of the analysts).

Incidentally, our price level predictions using cycles methods and EW analysis most often rhyme very nicely. Using confirmations from multiple methods of technical analysis in our approach significantly improve the level of confidence in trading and investing, as well as the success rate.