A few years ago, I developed a simulator based on approximations to normal using the Kolmogorov-Smirnov test. It performed relatively well in bullish markets but struggled to detect changes in trends.
My personal thesis is that most abrupt trend changes come from more social factors (i.e. not because the numerical trendline crossed the projected SMA line or whatever), and as a result, it is very difficult to predict future trends and price data from a purely quantitative viewpoint. I think the formula that will truly make it will be the one that can incorporate social "data" into the mix, which is very difficult to do, but I'd argue not totally impossible. Probably would be rather elementary (in relative terms) using today's capabilities, but you have to build for the future - what is going to exist in 10 years is different from today. Whoever makes a formula or calculation that can somehow quantify and build upon social data, which really should be somewhat possible using todays technology, is on the right path to creating something that will change the world of price prediction calculations.