We agree that payouts have to be limited in the future to stop exponential growth. It might help if, in the future, payouts were better aligned with actual fund performance. A short term solution of refocusing efforts on Signals is a red herring. It simply does not face the issue at hand. In the mean time an overall proration scheme has a negative effect on attracting unique models. In recent history all models went through “an inflationary phase” to borrow a term in astrophysics. What the team should prefer to do is replicate that experience for all relative newcomers, because its exciting for the newcomer and it is also healthier for the Hedge Fund. A way to do that is introduce an individual stake dependent cutoff factor. The problem of duplicating accounts to try to get around the individual stake limitation factor can be easily fixed by introducing another correction factor which is simply a function of the maximum correlation of a submission to any other prediction submitted in a round, i.e., (1-\max C_{ij}). Then the payout would be

\mathrm{payout}_i = \frac{ \mathrm{Stake}_i}{1+\frac{15\times \mathrm{Stake}_i}{300\mathrm{K\ NMR}}} \mathrm{Corr}_i \times \left(1-\max C_{ij}\right).

As a replacement for MMC, a payout system using the above payout formula would encourage more unique models by giving new modelers an exponential boost that is not gamable. What is also nice about this is that it is more deterministic and much easier to calculate than MMC.