Discussion of article "Money Management by Vince. Implementation as a module for MQL5 Wizard"
Delighted, an incredibly well done job. Thank you for your labours.
The article Capital Management by Vince has been published. Implementation in the form of MQL5 Wizard module:
Author: Dmitrii Troshin
Thank you! Good elaboration of one of the best books!
Основные положения
For clarity, let's consider the main ideas on examples. Suppose we have some conditional system of two deals. The first trade wins 50% and the second trade loses 40%. If we do not reinvest the profit, we win 10%, and if we do reinvest, the same sequence of trades gives a loss of 10%. (P&L=Profit or Loss).
When reinvesting the profit, the winning system has turned into a losing system.
It is impossible to turn a minus system into a plus one with the help of MM. But the opposite is also true, a plus system cannot be turned into a minus system using MM.
In this example, the author does not take into account two more options:
1. Both trades are in plus. i.e. profit is equal to ( 100*1.5*1.5 - 100 ) = 125.
2. Both trades are in the minus, i.e. profit is equal to ( 100*0.6*0.6 - 100 ) = 64.
In general, the plus system remains plus.
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New article Money Management by Vince. Implementation as a module for MQL5 Wizard has been published:
The article is based on 'The Mathematics of Money Management' by Ralph Vince. It provides the description of empirical and parametric methods used for finding the optimal size of a trading lot. Also the article features implementation of trading modules for the MQL5 Wizard based on these methods.
First we find the characteristics of the distribution, i.e. the mean and the standard deviation. Then we select the "confidence interval" or the cut-off width, which is expressed in standard deviations. The 3σ interval is usually selected. Values greater than 3σ are cut off. After that the interval is divided binned and then associated values of profits/losses (PL) are found. For example, for σ=1 and m=0, the value of the associated PLs at the boundaries of the interval are m +- 3σ = +3 and -3. If we divide the interval into bins of lengths 0.1σ, then associated PLs will be -3, -2.9, -2.8 ... 0 ... 2.8, 2,9, 3. For this PL stream we find the optimal f.
Since different values of PL have different probability, then individual "associated probability" P is found for each value. After that the maximum of products is found:
HPR=(1+PL*f/maxLoss)^P, where maxLoss is the maximum loss (modulo).
Vince suggests using the cumulative probability as the associated probability. The cumulative probability is shown in orange in our graph F'(x).
Logically, the cumulative probability should be taken only for extreme values, while for other values P=F'(x)-F'(y), where x and y are values of F(x) at the boundaries of the interval.
Author: Dmitrii Troshin