Hi, I’m Dr. Keller

As an ecocnomic professor, I teach students every day about the various laws and theories and foundational concepts to help understand how economies function.

In economics, several important formulas are used to quantify and analyze different concepts. These formulas help in understanding relationships between variables, predicting outcomes, and making more informed decisions.

My interest in economics and its theories and principles led me to a study of the Fourier Transform.

Fourier Transform is a mathematical technique used to convert a function or signal from its original domain (often time or space) into a representation in the frequency domain. It helps break down a complex signal into its constituent sinusoidal components (sine and cosine waves), showing how much of each frequency is present in the original signal.

As a avid stock trader, I wondered if the Fourier Transform could be used as a signal for trading stocks.

What I discovered was that the Fourier Transform can be used in stock price prediction to analyze and identify underlying patterns in the data.

Specifically the price, but also time is a critical component – and price from several timeframes are collected and analyzed.

By applying Fourier Transform to stock market data, I was able to decompose the data into its component frequencies and examine how they contribute to an overall pattern.

The results tell me two primary things – a stock is a strong buy or a stong avoid or short trend.

The basics here is that it helps me to identify trends, cycles, and other patterns in the data that may not be apparent by simply looking at the raw stock prices.

One common approach used by others who try to using Fourier Transform for stock price prediction is to decompose the data into different frequency bands and then use each band to make a separate prediction.

Fine….this is nothing new.

What I discovered is a properieiary method of using the frequency bands in a unique way to pick stocks that have a long-term upward potential or a strong long-term downward potential.

SpectraTrade can also identify stocks to avoid that have, or more importantly, will have or will continue a long-term negative price momentum or underlying weakness.

Take a look at my propiertiary spreadsheet I use daily for stock analysis.

By transforming a signal into the frequency domain, it helps reveal hidden periodicities, trends, or noise

This spreadsheet is a currently a manual process where I have to input daily stock prices from various time frames.

But I am hoping to raise enough capital to automate the process and create a stock scanner for my clients.

Based on the complexity of my spreadsheet, it will take a team of programmers some to interpolate my calculations into a web service. First, there will be some costs to collect price/time data from a service and then it will take time to test and validate the programmers work.

So right now, I can only manage one stock at a time.

For now, my service will be free, allowing you to analyze and track my work.

I will be listing my predictions, for free, on my website at www.SpectraTrade.com

If you want a specific stock analyized, contact me directly at SpectraTrade@mail.com, and for a small fee I will run the data.

Just a note here that everything I share or say is for learning purposes only and not investing advice. Talk to your broker or investment advisor before making any financial decisions. It’s essential to conduct your own research and consider your individual financial situation, goals, and risk tolerance before engaging in any trading or investment activities. Always remember that past performance is not indicative of future results.