The interesting thing I got out of this analysis is that, if you have a slight edge of 1%, having the constant percentage betting strategy is much better, if you have a large (100,000) number of bets. Having a log scale would be nice to see approximately where the two strategies returns diverge.
This got me thinking. One thing that is not discussed is that in real life trading one does not know what percentage advantage one has. Many successful traders rely on subconscious processes for part of their trading strategy that they have no way of examining, but seems to work(sometimes). If the only way to find out what your expected return is(your edge), is to bet and see what happens (maybe this is really the reason one needs "skin in the game") then ramping up your betting when you are winning is a really good idea. When you are losing money it is likely your expected return is negative and you should start scaling back your bets until you find an edge again.
It would be interesting to run this code with variable rates of return over time, including negative ones, where one scales the bet size not on your net capital but on (the percentage win on the last n bets)*(capital).
I'm sure this is all in some book written in the 18th century as people have been trading in markets for a long time.
What a lot of traders do is use 50% of the Kelly limit to cover this risk. At worst by staying under the Kelly limit you reduce your return, while if you exceed it you will blow up at some point.
I thought what I was saying was quite a bit different. If one is using the Kelly Criterion, one needs to know what the probability of winning and odds paid for a win. Traders generally don't know these at all and only can find them out by making the trade and seeing what happens.
Of course when the Kelly Criterion is known and constant, one can make the optimal bets and get rich, but those situations don't exist in real life (unless there is some kind of monopoly or external force being used to make people take the other (loosing side) of the bet). The iterative thinking of the the Kelly Criterion must be part of a traders mindset, but markets never understood well enough to where this formula can be strictly applied.
A bit strange to see Taleb talk about a casino situation to explain his thinking. Elsewhere he mocks such "casino odds" view of the world as very unrealistic an bemoans that such a view will cause one grief if you use those ideas with "skin in the game".
ps. I've only read "Anti-Fragile" and some of his blog essays.
This got me thinking. One thing that is not discussed is that in real life trading one does not know what percentage advantage one has. Many successful traders rely on subconscious processes for part of their trading strategy that they have no way of examining, but seems to work(sometimes). If the only way to find out what your expected return is(your edge), is to bet and see what happens (maybe this is really the reason one needs "skin in the game") then ramping up your betting when you are winning is a really good idea. When you are losing money it is likely your expected return is negative and you should start scaling back your bets until you find an edge again.
It would be interesting to run this code with variable rates of return over time, including negative ones, where one scales the bet size not on your net capital but on (the percentage win on the last n bets)*(capital).
I'm sure this is all in some book written in the 18th century as people have been trading in markets for a long time.