Here to share an interesting article about the proof of the Gaussian correlation inequality conjecture. Beyond the GCI’s geometric implications, Richards said a variation on the inequality could help statisticians better predict the ranges in which variables like stock prices fluctuate over time.Wondering how much the said technique is effective in real world stock price prediction or really useful in some sense.
For prices, all of it is BS except this: “We can work for a long time on a problem and suddenly an angel—[which] stands here poetically for the mysteries of our neurons—brings a good idea.” Now multiply this by 10.000 and then subtract 9.990.
Since it requires that the probabilities involved fall in a Gaussian distribution and it's been definitively shown that securities prices do not follow a Gaussian distribution, then the answer is no. In any event, he "just" proved a conjecture that has been around for some time. Obviously the proof was a monumental task, but you don't need a proof to use a conjecture.
Probably useful. https://www.quantamagazine.org/20170328-statistician-proves-gaussian-correlation-inequality/