Also another thing is that the optimal bet size for the 60% system is 25% while for the 40% is 10%. So the 40% system would have a less volatile equity curve?
A. Don't believe everything you hear. B. Theory can work for you or against you. A 40% winrate means that 4 out of 10 trades will be winners and 6 will be losers. What if you get all six at the beginning, in a row? Out of 20 trades, 12 will be losers. What if you get all twelve in a row? Even if you survive financially, what will this do to your self-confidence? Theory can sound inviting, but eventually one has to click the button.
Actually the first system has less volatility, if I understand the meaning of "volatility" correctly. Var(A) == .6*1 + .4*1 - .2*.2 == 0.96 Var(B) == .4*4 + .6*1 - .2*.2 == 2.16
Yep, thats why I think people don't use Kelly criterion. I thought about it and I wouldn't want 1 bad trade to take out 25% of my account. It boils down to what is your maximum tolerable drawdown. For me worst case scenario would be 5 losing trades in a row and I would tolerate losing maximum 10% of account. So I wouldnt risk the 20 or 25% like kelly suggests.;-) But maybe on a small "fun" account".;-)
I just compared volatility of both of them and the 60% is less volatile! (I risked 10% for both systems so the comparison could be accurate)
Lol. I think I know where the 2% rule comes from now. ;-) Losing 2% on 5 trades in a row equals roughly 10%.
Yep. Came to the same conclusion. It's because it has higher win-rate right? So the higher the win-rate your system has, the smaller the size of consecutive losses?
I pretty much scalp Indexes, currencies and energies, and I average down on each trade, so my losing percentages have to be extremely low to do so. What is not specified in two methods are the "mean" drawdown is, meaning what the average expected drawdown to be. And also what the breakeven percentages are, so if system is 40% winners, what is the 60%, are they all losers or mixture of losers and breakeven trades. Of course all may have different definition of what a winner is as well. You can have a very good method where there's 30% winners of 1:1, 50% breakevens and 20% losers and clean up by averaging down on each trade. On breakevens you could be adding at every two ticks against position and exiting them at original entry tick plus one tick, so if trade when against the position seven ticks, could have added on three trades, so breakeven trade gives +7, +5, +3, +1 . Of course the Math goes into hyper-drive of "what ifs" trading this way, and backtesting has to be deep and lengthy to provide a better edge.