Metatrader 5 versions of indicators ... - page 11
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Can you add alerts?
nbtrading
Here is a version with alerts added
Quantile bands - a sort of embellished version
Some basic information on quantiles :
In statistics and the theory of probability, quantiles are cutpoints dividing the range of a probability distribution into contiguous intervals with equal probabilities, or dividing the observations in a sample in the same way. There is one less quantile than the number of groups created. Thus quartiles are the three cut points that will divide a dataset into four equal-size groups (cf. depicted example). Common quantiles have special names: for instance quartile, decile (creating 10 groups: see below for more). The groups created are termed halves, thirds, quarters, etc., though sometimes the terms for the quantile are used for the groups created, rather than for the cut points.
q-Quantiles are values that partition a finite set of values into q subsets of (nearly) equal sizes. There are q − 1 of the q-quantiles, one for each integer k satisfying 0 < k < q. In some cases the value of a quantile may not be uniquely determined, as can be the case for the median (2-quantile) of a uniform probability distribution on a set of even size. Quantiles can also be applied to continuous distributions, providing a way to generalize rank statistics to continuous variables. When the cumulative distribution function of a random variable is known, the q-quantiles are the application of the quantile function (the inverse function of the cumulative distribution function) to the values {1/q, 2/q, …, (q − 1)/q}.
More information can be found here : https://en.wikipedia.org/wiki/Quantile
This indicator is constructing "bands" using 3 quantile values
Here is a version of Bollinger bands made as a filled area too
But to avoid just making the usual Bollinger bands with some more colors, this version has a choice of calculating the standard deviation as a sample or as an uncorrected deviation. The explanation for that would be the following :
Uncorrected sample standard deviation
Firstly, the formula for the population standard deviation (of a finite population) can be applied to the sample, using the size of the sample as the size of the population (though the actual population size from which the sample is drawn may be much larger). This estimator, denoted by sN, is known as the uncorrected sample standard deviation, or sometimes the standard deviation of the sample (considered as the entire population), and is defined as follows:[citation needed]
s N = 1 N ∑ i = 1 N ( x i − x ¯ ) 2 , {\displaystyle s_{N}={\sqrt {{\frac {1}{N}}\sum _{i=1}^{N}(x_{i}-{\overline {x}})^{2}}},}where { x 1 , x 2 , … , x N } {\displaystyle \scriptstyle \{x_{1},\,x_{2},\,\ldots ,\,x_{N}\}} are the observed values of the sample items and x ¯ {\displaystyle \scriptstyle {\overline {x}}} is the mean value of these observations, while the denominator N stands for the size of the sample: this is the square root of the sample variance, which is the average of the squared deviations about the sample mean.
This is a consistent estimator (it converges in probability to the population value as the number of samples goes to infinity), and is the maximum-likelihood estimate when the population is normally distributed.[citation needed] However, this is a biased estimator, as the estimates are generally too low. The bias decreases as sample size grows, dropping off as 1/n, and thus is most significant for small or moderate sample sizes; for n > 75 {\displaystyle n>75} 75"> the bias is below 1%. Thus for very large sample sizes, the uncorrected sample standard deviation is generally acceptable. This estimator also has a uniformly smaller mean squared error than the corrected sample standard deviation.
Corrected sample standard deviation
If the biased sample variance (the second central moment of the sample, which is a downward-biased estimate of the population variance) is used to compute an estimate of the population's standard deviation, the result is
s N = 1 N ∑ i = 1 N ( x i − x ¯ ) 2 . {\displaystyle s_{N}={\sqrt {{\frac {1}{N}}\sum _{i=1}^{N}(x_{i}-{\overline {x}})^{2}}}.}Here taking the square root introduces further downward bias, by Jensen's inequality, due to the square root being a concave function. The bias in the variance is easily corrected, but the bias from the square root is more difficult to correct, and depends on the distribution in question.
An unbiased estimator for the variance is given by applying Bessel's correction, using N − 1 instead of N to yield the unbiased sample variance, denoted s2:
s 2 = 1 N − 1 ∑ i = 1 N ( x i − x ¯ ) 2 . {\displaystyle s^{2}={\frac {1}{N-1}}\sum _{i=1}^{N}(x_{i}-{\overline {x}})^{2}.}This estimator is unbiased if the variance exists and the sample values are drawn independently with replacement. N − 1 corresponds to the number of degrees of freedom in the vector of deviations from the mean, ( x 1 − x ¯ , … , x n − x ¯ ) . {\displaystyle \scriptstyle (x_{1}-{\overline {x}},\;\dots ,\;x_{n}-{\overline {x}}).}
Taking square roots reintroduces bias (because the square root is a nonlinear function, which does not commute with the expectation), yielding the corrected sample standard deviation, denoted by s:
s = 1 N − 1 ∑ i = 1 N ( x i − x ¯ ) 2 . {\displaystyle s={\sqrt {{\frac {1}{N-1}}\sum _{i=1}^{N}(x_{i}-{\overline {x}})^{2}}}.}As explained above, while s2 is an unbiased estimator for the population variance, s is still a biased estimator for the population standard deviation, though markedly less biased than the uncorrected sample standard deviation. The bias is still significant for small samples (N less than 10), and also drops off as 1/N as sample size increases. This estimator is commonly used and generally known simply as the "sample standard deviation".
The difference is usually not big, but it exists. So now we have the Bollinger bands with a choice of these two deviation types too (with the usual set of 22 price types addition)
Fibonacci auto channel
I believe not too much explanation needed. The indicator is finding out the minimum and maximum for the desire period and draws fibo zones in those bounds. Highest high and lowest low current trend is marked by the color (sometimes it is very useful to see the change in the "trend" of those extremes)
I have an mt4 ea that I need to convert to mt5. It is simple and small. I am willing to pay someone to do it.
Thanks
Here is a version of Bollinger bands made as a filled area too
But to avoid just making the usual Bollinger bands with some more colors, this version has a choice of calculating the standard deviation as a sample or as an uncorrected deviation. The explanation for that would be the following :
The difference is usually not big, but it exists. So now we have the Bollinger bands with a choice of these two deviation types too (with the usual set of 22 price types addition)
Dear mladen,
should be possible to have a .mq4 version of the indicator (if the areas are not coloured and filled it's ok).
Thanks,
Andrea
Fibonacci auto channel
I believe not too much explanation needed. The indicator is finding out the minimum and maximum for the desire period and draws fibo zones in those bounds. Highest high and lowest low current trend is marked by the color (sometimes it is very useful to see the change in the "trend" of those extremes)
Can we have a version with levels adjustable?
Can we have a version with levels adjustable?
sebastianK
Here is a version in which you can adjust 4 levels (the 3 main levels are calculated using high/low period parameter)