The question pretty much sums it all. I am a semi-professional futures trader (CL, ZT, ZS, some crypto), who uses basic technical indicators since two years and has been fairly profitable.

That said, I don’t understand the rush towards all things maths and statistics as a basic requirement to trade - if hedge fund and prop trading positions are considered.

So here’s my humble question - where exactly does complex math, statistical model making, and computer programming come into the picture? Software dev positions are explanatory, but where do the aforementioned help? Doesn’t the first rule of markets say you can’t predict prices and movements?

Or is everyone rushing towards complex solutions which could have been solved fairly easily?

Worse still - are talks of ML, RL, AI, algo, etc a “gimmick” to attract investor capital?

All thoughts would be very, very helpful.

PS - Don’t make this a discussion about TA vs Quant. I do use indicators to trade, but definitely, don’t draw discretionary trend lines or watch “heads and shoulders” or analyze moon phases to place trades. In fact, I do think TA is complete bull, but using indicators has its logical reasons.

@behumble that is a very good question. As someone who worked at a IT consultancy that built and fine tuned algorithms at banks and medium sized hedge funds I can tell you that the motivation behind hiring quants and scientists who do AI/ML etc is that “patterns can be found in data” and computers can read and analyse this data quicker than humans can ever imagine.

The desire to find patterns comes from the success of Ray Dalio who was building algorithms in the 80’s.Now he runs Bridgewater the biggest hedgefund in the world.

So FOMO has people spending millions not wanting to miss out on an edge! However some of this is justified as they is so much more data we are literally drowning in it !
The data first camp believe books that state “first rule of markets say you can’t predict prices and movements” are outdated.

I don’t believe that AI is used to attract investor capital as so many companies are using AI/ML and predictive analytics that you will need these competencies to meet the new benchmark and even have clients in the first place.

Do you think using mathematical models to find patterns are a self-fulfilling prophecy? For eg: If most short-term trading is done via math models - wouldn’t the models start to prove correct over a span of time as everyone else is doing so?

Also, what level of math is actually used? I use basic mathematics to calculate risk and capital allotments while trading but have never really felt the need for higher concepts to help. This, of course, can be attributed to the size of my trading account (low-six figures) vs that of a typical prop shop ($10mil plus.)

The maths can will get quite finite and advanced as portfolios cant hold certain assets in certain circumstances, for example say a bond looses its investment grade rating. As such when calculating risks or future strategy the algo must compute thousands of potential outcomes in order to know what to do in certain circumstances.

All tests are done objectively and they are very high thresholds to beat. A pattern needs to hold true across multiple datasets and markets.