[MichaelRazum]

To be honest. I don’t believe a word about the performance using AI. Especially if the article doesn’t present the features and the NN architecture. Its always the question: would a super simple model perform the same way? And very ofter the answer is yes.

[rawoke083600]

Lol this.. I once build a model (btc) that assumes this "we can't know the direction of market so we might as well guess", after spending months reading papers and trying to be "clever"

It starts off picking a random market direction (up/down) places bid (sorry I mean makes a trade). Then based on lots of tuning/backtest decided how long to be in position and what is the stoploss.. Think in the end the most "profitable settings" where something like :

$proft_size = 0.38% $stop_loss_size = 0.35%

Win-Continue-Direction = 3 rounds (after winning/losing do we change direction) So it probably in the end was Markov-model with random-start - if we had to label it :)

Oh and for fun it would also "martingale for x rounds" :P

Worked quite well for 3-4 days and was fun implementing it while watching "Billions" on TV in the background :D

[MichaelRazum]

Actually I'm not saying that you can't be profitable. Just saying that the fancy NN, won't work like magic in a noisy environment like financial time series. For other time series with periodic and other anomalies you can apply NN and you may have an edge - BUT for that kind of environments also classical methods are working quite good.