Happy to say this afternoon I was able to do both and go out and get some exercise. I am now drinkng beer.
It's more like "I just got done with the audiobook of Fooled By Randomness and it explains why I am so bad at trading". Audiobook, because OP is illiterate based on his typing style. His attitude fits firmly in the "holier than thou" attitudes of people who religiously quote Sagan, Degrasse Tyson, etc. He probably weighs 400 lbs, smells of moldy fries, and makes fun of people because they read the bible. His IQ seems insanely high. Reminds me of another guy...ah yes - perhaps this guy and @lentus would get along just fine.
I disagree with the original post, history is history and therefore useless, last 30mins i consider current not history, and I use that to assume direction or short term S/R.
I agree to an extent, but in the stock market there are some edges based on variety of things, such as spotting a fake press release designed to pump a stock, which is expressed in volatile trading: some insider trading can occasionally be expressed in stock behavior; sometimes corporate buybacks may be detected, investor overreaction to certain announcement is expressed in stock pricing - and you don’t need to predict it ahead of time. Overall there may be many small edges here and there, but they may not be scalable in terms of finding edges every day, so you’re at risk of losing by seeking “edges” that aren’t there. Maybe except for Rentec - they are the biggest proof that you can make $billions on those edges and trade at big scale every day. Just like casinos are built with $billions made from randomness. And keep in mind that publicly traded companies aren’t created for the purpose of doing business randomly. If a company is stable then you may be able to trade the temporary noise/fear. Even better when the company is pretty much bankrupt and has near zero revenues. Though in principle I agree and have difficulty believing in consistently profitable day traders, although I don’t discount them either.
I studied graduate economics at The University of Chicago. I have a few items of note about Taleb. 1. He traded on the floor of the CME from 1991 to 1993. In other words; he made markets - he quoted bids and offers to floor brokers. Doesn’t get much more “day trady” than that. As any good floor trader would tell you: your edge is to buy at the bid and sell at the offer. 2. His exact words about randomness in the architecture of financial markets: “it's more random than we think, not it is all random.” 3. Chance favors preparedness.
No rational experienced trader would argue that there are protracted periods of time during a trading session where the market wanders in the noise of more or less equitable buy and sell orders. We call that “chop”. Likewise - there are times during a trading session where the weight of liquidity takers is clearly biased in a sustained manner towards buying or selling. When you see eighteen offers get lifted and go strong bid over a six minute time period - that’s not random price walking. So there are periods of randomness and there are periods of sustained price discovery in a trading session. Nassim Taleb is talented and he’s an original. He’s also notoriously vitriolic and prone to exaggerate. As with all things in life - Balance is important.
My opinion is that you are mathematically illiterate OP. This is probably why you can't maintain objectivity with regard to Nassim Taleb's book. Taleb has become some kind of mystic for non quantitative people. Taleb worshippers love saying 'fat tails' but have no clue of the complexity involved in quantitative modeling. You are using the word 'random' in a naive sense. There are much more sophisticated ideas than those of this author. Compounded distributions (this causes Kurtosis AKA 'fat tails') Non-stationary Parameters Semi-stationary Models Smart people who actually understand mathematical statistics study how the accuracy of estimates are affected by different characteristics of random processes. They understand the limitations of statistics and other mathematical theories (and what effect violations of assumptions have on the predictive power of models). Statistics is used to estimate (under a set of assumptions) theorized relationships, distributions of theorized parameters, and theorized distributions of errors that arise when modeling processes where we do not and cannot have complete information about the variability of phenomena. Every attempt to predict markets will be subject to error, and even estimating the size of the errors is problematic. However, these models have been weaponized and are being used to compete for profits in financial markets.