Power of Unconventional Mathematics in Predictive Modeling

In the contemporary financial markets, traditional mathematics have demonstrated its inadequacy. While supplying fixed formulas within a dynamic context, failures are assigned to unforeseen elements such as false signals, fundamental analysis, or unpredictable factors—terms all signifying suboptimal outcomes at a juncture where mathematical precision should be at its zenith.

The proper application of mathematics can be a real life changer; I refer specifically to unconventional mathematics, given the documented inefficacy of conventional methodologies. In an environment characterized by myriad dimensions, such as time and energy, parameters defy routine calculation. In such instances, the demand is not for a formula but for a systemic approach.

To ground this approach down to a wide population, consider the recent FOMC event that shook the market, manifesting a clear contradiction with conventional prognostications and what traders commonly term technical indicators. Conventional calculations and technical indicators proved irrelevant as market dynamics defied predictions, resulting in financial losses for traders who belatedly acknowledged that what seemed like a false signal was indeed correct, albeit misunderstood.

I feel sorry for traders who faced losses yesterday, but it is imperative to recognize that such occurrences are recurrent when one relies on erroneous calculations in pursuit of accurate outcomes.

Further in this thesis, I will share hypotheses and substantiate them with evidence, elucidating how the application of unconventional mathematics within a systematic framework, bolstered by the correlation of unconscious collective intelligence, can provide a precision predictive framework aligning projections across multiple dimensions.