That's correct. If W is large (say $1mn), I believe betting $1,000 on R16 maximizes the expected log of liferoll in your one-spin example.
Goal: Max E[log(W + B_1)]
Candidate solution:
Bet $1000 on R16.
B_1 = $36,000 with probability 4/37
B_1 = $0 with probability 33/37
E[log(W + B_1) =
(4/37)*log(1,000,000 + 36,000) + (33/37)*log(1,000,000) = (4/37)*13.851 + (33/37)*13.816 = 13.819
You can check other allocations to see if they offer a higher expected return than this. My intuition is that they will not, for large enough W. I expect $1mn is large enough, but could be wrong.
Thank you very much for the explanation. I ran my numerical solution, and it fully agrees with yours. I am convinced now. Below are the top 20 strategies. The concept of the "liferoll" does indeed add another dimension to this game. I am moving on to crafting the "progressive risk" solution now.
Code:
LifeRoll: $1,000,000
BankRoll: $1,000
R16 R14 RC RN BC BN Log(BankRoll + LifeRoll)
100.0 0.0 0.0 0.0 0.0 0.0 13.8193340330
99.9 0.1 0.0 0.0 0.0 0.0 13.8193331951
99.8 0.2 0.0 0.0 0.0 0.0 13.8193323570
99.7 0.3 0.0 0.0 0.0 0.0 13.8193315187
99.9 0.0 0.1 0.0 0.0 0.0 13.8193315120
99.9 0.0 0.0 0.0 0.0 0.1 13.8193312492
99.6 0.4 0.0 0.0 0.0 0.0 13.8193306802
99.8 0.1 0.1 0.0 0.0 0.0 13.8193306740
99.8 0.1 0.0 0.0 0.0 0.1 13.8193304112
99.9 0.0 0.0 0.0 0.0 0.0 13.8193302763
99.5 0.5 0.0 0.0 0.0 0.0 13.8193298414
99.7 0.2 0.1 0.0 0.0 0.0 13.8193298358
99.7 0.2 0.0 0.0 0.0 0.1 13.8193295730
99.8 0.1 0.0 0.0 0.0 0.0 13.8193294383
99.4 0.6 0.0 0.0 0.0 0.0 13.8193290023
99.6 0.3 0.1 0.0 0.0 0.0 13.8193289973
99.8 0.0 0.2 0.0 0.0 0.0 13.8193289909
99.6 0.3 0.0 0.0 0.0 0.1 13.8193287346
99.8 0.0 0.1 0.0 0.0 0.1 13.8193287281
99.7 0.2 0.0 0.0 0.0 0.0 13.8193286001
