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My thoughts on Van Tharp's R multiple concept are:
1 - establish or choose your risk tolerance (RT), say 1% of account size (AS)
2- calculate the max risk amount, RT x AS; this will be the 1R value
3 - determine the risk amount for the trade based on your entry target and stop placement
4 - determine the position size for the trade = Max Risk Amt (1R) from (2) / trade risk amt from (3)
5 - after the trade is closed, determine the trade reward to trade risk ratio. This is the R multiple for that trade
6 - average this ratio across your trades to get the expectancy
The expectancy will only be valid if you consistently use the same RT percent for the trades.
fat tail
how do you calculate exp, based on w% and r-m?
"And the mathematics?
There is little valid mathematics in the books of Van K Tharp. If you are really intested in the subject you should start with "The Mathematics of Money Management" by Ralph Vince. Not an easy read though, but very important. I am slowly digging through this, interrupted again and again by other priorities.
*) not known by many traders: Let us assume two trading systems:
system 1: winning percentage 70%, R-Multiple = 2
system 2: winning percentage 42%, R-Multiple = 4
Both systems have the same expectancy of 1.1R (which is excellent, 0R stands for break-even). However, the first system has a better Sharpe Ratio, so you can actually trade it with a larger position sizing, without increasing your actual risk (measured in terms of max. drawdown). "
The form of expectancy that I believe that most people are familiar with seems to be:
Classic Exp = [Pr W ] x [Avg W] - [Pr L] x [Avg L], where Pr L = 1 - Pr W
To get expectancy in terms of R Multiples my thoughts are:
1 - you must have a consistent (constant) risk tolerance, RT
2 - The 1R value = RT x AS, where AS = account size
3 - You must establish a position size consistent with your 1R value. First determine your trade risk, TR = ABS[Entry level - Protective Stop Level]. So the position size, PS = 1R / TR
4 - After the trade is closed, determine the reward (RWD) and compute the R Multiple (RM) for that trade, RM = RWD / 1R. Obviously, if the trade was a loss, the RM value will be negative value.
5 - Finally the expectancy in terms of RM is simply the average of the RM values.
Notice that the RM expectancy determination does not involve using any of the values from the Classic expectancy form above. Also, for the RM expectancy to be valid, you must use the same RT for all trades. If you vary RT for your trades, then you must use some other form of expectancy determination to judge the effectiveness of your trading strategy. One nice aspect of using RM expectancy to judge the effectiveness of your trading strategy is that it is independent of the account size.
The expectancy is the average outcome per trade. Let us take the system 1 with a winning percentage of 70% and a R-Multiple of 2. Out of 100 trades you would expect 70 trades with a winning amount of 2R and 30 trades with a losing amount of R. Therefore the expectancy can be calculated as
E = (70 * 2 * R - 30 * R)/100 = 0.7 * 2 * R - 0.3 * R = 1.1 * R
This is the raw expectancy.
The real results are also affected by commission and slippage, therefore the net expectancy is lower than this amount.
The impact of commissions and slippage can be dramatic for scalpers, but barely affects swing traders or investors.
thanks, i have calculated first with random at 50% and then with my measures of %80
i have enclosed the new excell v2 with a yellow shadow area, where i have added the rewor, risk, and expectancy exp2, but i do not know if i did it right and why there s a difference between exp, and exp2
to clarify a little, in both strategy 3L and 4L, i split in two: fix and trail, in fix i let the stop loss at -3 always and the other i close it before when it become a loser trail it the stop to -2,-1 and be