Discussion of article "Modeling time series using custom symbols according to specified distribution laws"
Very interesting article, thanks to the author.
The material may be useful for modelling various market processes when developing analytical and trading systems.
Я не сталкивался с такой проблемой. Все созданные пользовательские символы и открытые графики сохраняются после перезагрузки MT5. Возможно, вам стоит обновить вашу версию MT5.
Я не сталкивался с такой проблемой. Все созданные пользовательские символы и открытые графики сохраняются после перезагрузки MT5. Возможно, вам стоит обновить вашу версию MT5.
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In the GetCandle.mq5 script, all these lines
#include </Math/Stat/Beta.mqh> #include </Math/Stat/Binomial.mqh> #include </Math/Stat/Cauchy.mqh> #include </Math/Stat/ChiSquare.mqh> #include </Math/Stat/Exponential.mqh> #include </Math/Stat/F.mqh> #include </Math/Stat/Gamma.mqh> #include </Math/Stat/Geometric.mqh> #include </Math/Stat/Hypergeometric.mqh> #include </Math/Stat/Logistic.mqh> #include </Math/Stat/Lognormal.mqh> #include </Math/Stat/NegativeBinomial.mqh> #include </Math/Stat/NoncentralBeta.mqh> #include </Math/Stat/NoncentralChiSquare.mqh> #include </Math/Stat/NoncentralF.mqh> #include </Math/Stat/NoncentralT.mqh> #include </Math/Stat/Normal.mqh> #include </Math/Stat/Poisson.mqh> #include </Math/Stat/T.mqh> #include </Math/Stat/Uniform.mqh> #include </Math/Stat/Weibull.mqh>
can be replaced by one:
#include <Math\Stat\Stat.mqh>
New article Modeling time series using custom symbols according to specified distribution laws has been published:
The article provides an overview of the terminal's capabilities for creating and working with custom symbols, offers options for simulating a trading history using custom symbols, trend and various chart patterns.
The trend models discussed above have the specified properties only on minute timeframes. The price charts generated for these models look like linear functions on timeframes M15, M30, H1 and higher. In order to obtain a trend that changes its direction on timeframes other than M1, it is necessary to select the random trend type (TType = Random) and to specify the number of minute candles after which to make an attempt to change the trend direction.
Run the script with the following parameters: TModel = LinearAndStochastic, TType = Random, Coeff1 = 0.05, Coeff2 = 1, Coeff3 = 1, RandomTrendCoeff=0.5, CountCandle=60. The following chart on the H1 timeframe is obtained:
Author: Aleksey Zinovik