COMPLEX METHODS EASY SOLUTIONS
About ML Perspective
Hi! My name is Alejandro Romero, I am an Industrial Engineer and Master in Finance & Investments by profession. Since I was a child, I got passionated by finance and statistics.
Never believed on the time-series approach for stock prices as the latter ones are purely random, I personally demonstrated that the probability of a stock price ending up above or below one week later, compare to its current level, is 50% at a 1% confidence level for all stocks in the S&P 500.
Therefore, what to do to "somehow" predict a stock quote? Simple, don't try to predict the price but the probability of it ending above or below its present level, based on its ongoing "conditions", some time later.
Thus, what do I mean when I say "conditions"? What people "think" where the stock quote came and where it is aiming at. Behavioral finance makes fundamentals and technicals to work; consequently, by using Machine Learning to represent stock behaviors, this probability can be estimated.
I decided to change the way we, professionals, analyze data. We constrain ourselves by the traditional approach of time-series, 2D graphs, among others. Stock prices, as many variables on earth, are chaotic; hence, the best approach is to predict a range where it will end up at a determined certainty. Let's see what is hidden beyond stochastic processes together with a different approach!