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MAC-Z & MACD Leader signal [ChuckBanger]This is a combination of my MACD Leader script and MAC-Z with option to add Laguerre filter. The advantage of the MAC-Z over MACD is that it is a more accurate and “assumption-free” indicator that can more accurately describe how a market actually perform. But you can use this as a regular MACD indicator.
Crossovers signals
The MAC-Z line and signal line can be utilized in the same way as a stochastic oscillator, with the crossover between the two lines providing buy and sell signals. As with most crossover strategies, a buy signal comes when the shorter-term, more reactive line – in this case the MAC-Z line (blue line) crosses above the slower signal line (orange line). For example, when the MAC-Z line crosses below the signal line it provides a bearish sell signal.
Zero line crossing
The zero cross strategy is based on either of the lines crossing the zero line. If the MAC-Z crosses the zero line from below, it is a signal for a possible new uptrend, while the MAC-Z crossing from above is a signal that a new downtrend may be starting. This is special powerful if the lines has a fast up or down movement but the price action doesn't reflect that movement.
Divergences
Bearish and bullish divergences is my favorite signals. When price action and oscillators follow the same path it is called Convergences, when they don’t, it’s called a Divergence. Don't confuse the two because they have not the same meaning. But be aware that for example during consolidation or low liquidity, some small divergences between price and indicators might form, but that doesn't mean we should consider them as real divergences.
There is many different types of divergences. It is easier to show a picture then explaining it so I recommend you to check out the link below. Especially the top image. It sums this up very well
medium.com
MACD Leader
The MACD leader is only showing the crossing of MACD as a vertical line
Green vertical line = MACD Leader Bullish Cross
Red vertical line = MACD Leader Bearish Cross
MACD Leader:
MAC-Z:
More Information
cssanalytics.wordpress.com
en.wikipedia.org
drive.google.com Индикатор
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Dependent Variable Odd Generator For Machine Learning TechniquesCAUTION : Not suitable for strategy, open to development.
If can we separate the stagnant market from other markets, can we be so much more accurate?
This project was written to research it. It is just the tiny part of the begining.
And this is a very necessary but very small side function in the main function. Lets start :
Hi users, I had this idea in my mind for a long time but I had a hard time finding the parameters that would make the market stagnant. This idea is my first original command system. Although it is very difficult to make sense of the stagnant market, I think that this command system can achieve realistic proportions. With 's money flow index, I opened the track to determine the level. On the other hand, the prices were also using a money flow index, and it forced me to make the limitations between the levels in a logical way. But the good thing is that since the bollinger bandwidth uses a larger period, we are able to print normal values at extreme buy and sell values.
In terms of price, we can define excessive purchase and sale values as the period is smaller. I have repeatedly looked at the limit values that determine the bull, bear, and bollinger bandwidth (mfi), and I think this is the right one. Then I have included these values in the probability set.
The bull and bear market did not form the intersection of the cluster, and because there are connected events, the stagnant market, which is the intersection, will be added to the other markets with the same venn diagram logic and the sum of the probability set will be 1. is equal to. I hope that we can renew the number generators in the very important parameters of machine learning such as Markov Process with generators dependent on dependent variables, which bring us closer to reality. This function is open to development and can be made of various ideas on machine learning. Best wishes.
This code is open source under the MIT license. If you have any improvements or corrections to suggest, please send me a pull request via the github repository github.com Индикатор
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Bilateral Stochastic Oscillator - For The Sake Of EfficiencyIntroduction
The stochastic oscillator is a feature scaling method commonly used in technical analysis, this method is the same as the running min-max normalization method except that the stochastic oscillator is in a range of (0,100) while min-max normalization is in a range of (0,1). The stochastic oscillator in itself is efficient since it tell's us when the price reached its highest/lowest or crossed this average, however there could be ways to further develop the stochastic oscillator, this is why i propose this new indicator that aim to show all the information a classical stochastic oscillator would give with some additional features.
Min-Max Derivation
The min-max normalization of the price is calculated as follow : (price - min)/(max - min) , this calculation is efficient but there is alternates forms such as :
price - (max - min) - min/(max - min)
This alternate form is the one i chosen to make the indicator except that both range (max - min) are smoothed with a simple moving average, there are also additional modifications that you can see on the code.
The Indicator
The indicator return two main lines, in blue the bull line who show the buying force and in red the bear line who show the selling force.
An orange line show the signal line who represent the moving average of the max(bull,bear), this line aim to show possible exit/reversals points for the current trend.
Length control the highest/lowest period as well as the smoothing amount, signal length control the moving average period of the signal line, the pre-filtering setting indicate which smoothing method will be used to smooth the input source before applying normalization.
The default pre-filtering method is the sma.
The ema method is slightly faster as you can see above.
The triangular moving average is the moving average of another moving average, the impulse response of this filter is a triangular function hence its name. This moving average is really smooth.
The lsma or least squares moving average is the fastest moving average used in this indicator, this filter try to best fit a linear function to the data in a certain window by using the least squares method.
No filtering will use the source price without prior smoothing for the indicator calculation.
Relationship With The Stochastic Oscillator
The crosses between the bull and bear line mean that the stochastic oscillator crossed the 50 level. When the Bull line is equal to 0 this mean that the stochastic oscillator is equal to 0 while a bear line equal to 0 mean a stochastic oscillator equal to 100.
The indicator and below a stochastic oscillator of both period 100
Using Levels
Unlike a stochastic oscillator who would clip at the 0 and 100 level the proposed indicator is not heavily constrained in a range like the stochastic oscillator, this mean that you can apply levels to trigger signals
Possible levels could be 1,2,3... even if the indicator rarely go over 3.
Its then possible to create strategies using such levels as support or resistance one.
Conclusion
I've showed a modified stochastic oscillator who aim to show additional information to the user while keeping all the information a classical stochastic oscillator would give. The proposed indicator is no longer constrained in an hard range and posses more liberty to exploit its scale which in return allow to create strategies based on levels.
For pinescript users what you can learn from this is that alternates forms of specific formulas can be extremely interesting to modify, changes can be really surprising so if you are feeling stuck, modifying alternates forms of know indicators can give great results, use tools such as sympy gamma to get alternates forms of formulas.
Thanks for reading !
If you are looking for something or just want to say thanks try to pm me :)
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