But in theory you can get arbitrarily close to 0.5. I think.
The win chance does get closer to 0.5 with more steps, but it seems it cannot be made arbitrary close to 0.5.
I am so glad that I asked you the question. Thanks a lot.
Yeah, hence the "I think.
". I'm not sure where it converges.
I was thinking of using the following strategy to split any single bet into a pair of more effective bets:
Suppose we have H and want to gain G.
We could make a single bet to attempt to do that
The payout multiplier would need to be (G+H)/H
The probability of success would be 0.99H/(G+H)
So we would bet H with chance 99H/(G+H) and if we win we end up with H*(G+H)/H = G+H and we've gained G.
Alternatively,
Define A = sqrt(G(G+H)) - G
Define B = H-A
Define P = (A+G)/A
Define C = 99/P = 99A/(A+G)
Then we can make an equivalent pair of bets:
bet A at chance C and if it loses bet B at chance C. The payout multiplier is P for both bets.
If the first bet wins, we have (H-A) left that we didn't risk, and get A*P = A+G back, so we end up with G+H
If the 2nd bet wins, we have lost A in the first bet, and get B*P
BP = (H-A)(A+G)/A
= (HA - AA + HG - AG)/A
= (H.sqrt(G(G+H)) - HG - G(G+H) + 2G.sqrt(G(G+H)) - GG + HG - G.sqrt(G(G+H)) + GG)/A
= (H.sqrt(G(G+H)) - G(G+H) + 2G.sqrt(G(G+H)) - G.sqrt(G(G+H)))/A
= (H.sqrt(G(G+H)) - G(G+H) + G.sqrt(G(G+H)))/A
= ((G+H)sqrt(G(G+H)) - G(G+H))/A
= ((G+H)(sqrt(G(G+H)) - G))/A
= (G+H)A/A
= G+H
So whether we win the first or 2nd bet, we end up with G+H, as required.
And we have a (1-C)(1-C)/1e4 probability of success.
Can we use that recursively, to split 1 bet into 2, then 2 into 4 into 8, etc. indefinitely? And if so, what does that do to the overall success rate?