Incredible research as always! I read this paper and found it very interesting, but unfortunately, I guess I have a selfish user attack for it. The high-level idea is that because your proposed update rule is multiplicative if some exchange refrains from broadcasting its transactions for some time and then releases all of them in a single large batch, this oscillating behavior will push the price down even though the average transaction volume stays the same as in the equilibrium. In this straightforward simulation for the first 1000 blocks, everyone is acting honestly, and the network is at equilibrium, however, in the second 1000 blocks, only ten agents with 10% of the total transaction volume can halve the price.
I propose to replace the suggested update formula by the additive Almgren–Chriss framework in game theory, which guarantees that the optimal execution of transaction strategy is actually to spread transactions across different blocks which in turn helps to avoid network congestion. Also, a much simpler solution in terms of Kolmogorov complexity as @vbuterin mentioned in his paper, is to use a sliding median which is more stable and predictable than the first price auction and also much more robust to selfish miner attack for the second price auction.