...all trading teachers should have to go through a mandatory third-party vetting of their P&Ls over a multi-year timeframe, to show that consistency in day trading is nearly impossible with such a large distribution of data.
Trading teacher A teaches a trading method that, if followed, produces consistent profits over a 5-year period, but trading teacher A's P&L over that period is negative and analysis of trades shows that this teacher does not trade the method s/he teaches.
Trading teacher B teaches a trading method that is missing some important pieces and if one attempts to follow it according to the pieces described produces consistent losses over a 5-year period; yet trading teacher B's P&L over that period is extremely positive and analysis of trades shows that this teacher trades in a way that bears no resemblance to the method s/he teaches.
Whose trading method will be more likely to produce a profitable student?
By the way, consistency in day trading is astonishingly possible. The consensus seems to be that at least 95% of day traders lose money over time. That's about as consistent as you can get in an environment of uncertainty.
The main reason why day traders lose despite studying (and often even understanding) profitable trading methods is purely psychological. Price movement in the markets is not totally random; the distribution of certain repeating price behavior patterns is random. This fact allows for consistently profitable trading over time, but our natural tendencies to search for certainty and perfection sabotages us in a environment where favorable overall odds inherent in series' of trades require us to accept "failures" on a regular basis:
Louis Menand's review of Philip Tetlock’s book makes the point that in "more than a hundred studies that have pitted experts against statistical or actuarial formulas, ... the people either do no better than the formulas or do worse". Menand suggests that the experts' downfall "is exactly the trouble that all human beings have: we fall in love with our hunches, and we really, really hate to be wrong". Tetlock puts it like this (p. 40): "the refusal to accept the inevitability of error -- to acknowledge that some phenomena are irreducibly probabilistic -- can be harmful."
Tetlock illustrates this point with an anecdote about an experiment that "pitted the predictive abilities of a classroom of Yale undergraduates against those of a single Norwegian rat". The experiment involves predicting the availability of food in one arm of a T-shaped maze.The rat wins, by learning quickly that it should always head for the arm in which food is more commonly available -- betting on the maximum-likelihood outcome -- while the undergrads place their bets in more complicated ways, perhaps trying to find patterns in the sequence of trials.
Tetlock suggests that humans perform worse in this experiment because we have a higher-order, more abstract intelligence than rats do: "Human performance suffers [relative to the rat] because we are, deep down, deterministic thinkers with an aversion to probabilistic strategies... We insist on looking for order in random sequences."
The students looked for patterns of left-right placement, and ended up scoring only fifty-two per cent, an F. The rat, having no reputation to begin with, was not embarrassed about being wrong two out of every five tries. But Yale students, who do have reputations, searched for a hidden order in the sequence. They couldn’t deal with forty-per-cent error, so they ended up with almost fifty-per-cent error.
