The report, while a fun thought exercise for any aspiring academic, is not a novel insight, and is obviously untrue for most definitions of market efficiency.
If we are going to play the academic one-upmanship game, a more general result that "best" or "multiple" N-player Nash Equilibria for N > 2 is already NP-hard. The implication of an efficient market would be if every player had a polynomial-time algorithm to solve the NP-hard problem, ergo P=NP.
Yeah, even with unbounded computational power, Nash equilibria are communication-hard; i.e., you need exponentially many bits for an n-player game to converge to an equilibrium, even when all players have unbounded computational power.
If we are going to play the academic one-upmanship game, a more general result that "best" or "multiple" N-player Nash Equilibria for N > 2 is already NP-hard. The implication of an efficient market would be if every player had a polynomial-time algorithm to solve the NP-hard problem, ergo P=NP.
[1] https://people.csail.mit.edu/costis/simplified.pdf
[2] https://www.quantamagazine.org/in-game-theory-no-clear-path-...
[3] https://arxiv.org/abs/1104.3760#:~:text=Unlike%20general%20N....