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Deep Moving Average MT4

40 USD

Versione demo scaricata: 257

Pubblicato: 10 luglio 2017

Versione attuale: 6.18

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Deep Moving Average MT4

Indicatori
Marat Sultanov
Versione: 6.18
Aggiornato: 16 maggio 2022
Attivazioni: 20

Every indicator has its advantages and disadvantages. Trending ones show good signals during a trend, but lag during a flat. Flat ones thrive in the flat, but die off as soon as a trend comes. All this would not be a problem, if it was easy to predict when a flat changes to a trend and when a trend changes to a flat, but in practice it is an extremely serious task.

What if you develop such an algorithm, which could eliminate an indicator's flaws and enhance its strengths? What if such an algorithm could improve the operation of a trend indicator during a flat, but at the same time increase the efficiency during a trend, and fix the signals of a flat indicator during a trend and perfect them during a flat?

Deep is the algorithm that enhances the advantages of an indicator and reduces its disadvantages. This algorithm improves indicator quality as a result of combining neural networks with indicator algorithm.

About the Deep algorithm

The specified task, due to its non-reproducibility and complex regularity, are best soled by non-linear algorithms. Neural networks are a very versatile and powerful tool, which allows to achieve a lot, if the task is set correctly and the solution is formed reasonable. The algorithm is based on this tool.

This algorithm calculates the optimal periods of the moving average, depending on the state of the trend and the flat. The algorithm trains the neural network to predict the optimal moving average for each market condition, so the indicator adapts to the flat and trend, eliminating the shortcomings of the basic algorithm. In the flat condition, the neural network adapts the period of the moving average in the direction of the flat, in the trending condition in the direction of the trend.

The neural network architecture and the heuristic search algorithm were designed specifically for the optimal solution of the task. For convenience, there are Presets of the neural network structure, as well as all the necessary parameters for fine-tuning the neural network.

Advantages

The algorithm has a self-learning system. This is an adaptive system that helps to learn flexibly all the time using a neural network so that the algorithm always keeps up with all market changes.
Graphical control panel. Using the panel directly on the chart, you can flexibly control and manage the learning system.
Parameters for fine-tuning all functions.

altro...

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PRO Renko System è un sistema di trading altamente accurato appositamente progettato per il trading di grafici RENKO. Questo è un sistema universale che può essere applicato a vari strumenti di trading. Il sistema neutralizza efficacemente il cosiddetto rumore di mercato che consente di accedere a segnali di inversione accurati. L'indicatore è molto facile da usare e ha un solo parametro responsabile della generazione del segnale. Puoi facilmente adattare lo strumento a qualsiasi strumento di

Order block hunter indicator is the best indicator for hunt the order blocks that area where there has been a large concentration of limit orders waiting to be executed Order blocks are identified on a chart by observing previous price action and looking for areas where the price experienced significant movement or sudden changes in direction .This indicator does that for you by using very complicated codes and helps you to take the best areas To buy and sell because it make marks at the best a

Do you want to see the future lines of the ZigZag indicator? This indicator will help you do that because the indicator model is based on two indicators: Historical Memory and ZigZag. So it can forecast the ZigZag lines. Very useful as an assistant, acts as a key point to forecast the future price movement. The forecast is made using the method of searching the most similar part in the history (pattern) to the current one. The indicator is drawn as a line that shows the result of change o

Every indicator has its advantages and disadvantages. Trending ones show good signals during a trend, but lag during a flat. Flat ones thrive in the flat, but die off as soon as a trend comes. All this would not be a problem, if it was easy to predict when a flat changes to a trend and when a trend changes to a flat, but in practice it is an extremely serious task. What if you develop such an algorithm, which could eliminate an indicator's flaws and enhance its strengths? What if such an algorit

Tired of adjusting the indicator settings losing precious time? Tired of the uncertainty regarding their efficiency? Afraid of the uncertainty in their profitability? Then the indicator ACI (automatically calibrateable indicator) is designed exactly for you. Launching it, you can easily solve these three issues just performing the simplest action: clicking a single Calibrate button. To achieve the highest efficiency, you should perform another additional action: move the power slider to the maxi

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Indicator-forecaster. Very useful as an assistant, acts as a key point to forecast the future price movement. The forecast is made using the method of searching the most similar part in the history (pattern). The indicator is drawn as a line that shows the result of change of the close price of bars. The depth of history, the number of bars in the forecast, the patter size and the quality of search can be adjusted via the indicator settings. Settings: PATTERN_Accuracy_ - quality of the search.

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Every indicator has its advantages and disadvantages. Trending ones show good signals during a trend, but lag during a flat. Flat ones thrive in the flat, but die off as soon as a trend comes. All this would not be a problem, if it was easy to predict when a flat changes to a trend and when a trend changes to a flat, but in practice it is an extremely serious task. What if you develop such an algorithm, which could eliminate an indicator's flaws and enhance its strengths? What if such an algorit

The B150 model is a fully revised version of the Historical Memory indicator with a significantly improved algorithm. It also features a graphical interface what makes working with this perfect tool quick and convenient. Indicator-forecaster. Very useful as an assistant, acts as a key point to forecast the future price movement. The forecast is made using the method of searching the most similar part in the history (patter). The indicator is drawn as a line that shows the result of change of the

The B150 model is a fully revised version of the Historical Memory indicator with an improved search algorithm. It also features a graphical interface what makes working with this tool quick and convenient. Indicator-forecaster. Very useful as an assistant, acts as a key point to forecast the future price movement. The forecast is made using the method of searching the most similar part in the history (patter). The indicator is drawn as a line that shows the result of change of the close price o

Tired of adjusting the indicator settings losing precious time? Tired of the uncertainty regarding their efficiency? Afraid of the uncertainty in their profitability? Then the indicator ACI (automatically calibrateable indicator) is designed exactly for you. Launching it, you can easily solve these three issues just performing the simplest action: clicking a single Calibrate button. To achieve the highest efficiency, you should perform another additional action: move the power slider to the maxi

FREE

Every indicator has its advantages and disadvantages. Trending ones show good signals during a trend, but lag during a flat. Flat ones thrive in the flat, but die off as soon as a trend comes. All this would not be a problem, if it was easy to predict when a flat changes to a trend and when a trend changes to a flat, but in practice it is an extremely serious task. What if you develop such an algorithm, which could eliminate an indicator's flaws and enhance its strengths? What if such an algori

Do you want to see the future lines of the ZigZag indicator? This indicator will help you do that because the indicator model is based on two indicators: Historical Memory and ZigZag. So it can forecast the ZigZag lines. Very useful as an assistant, acts as a key point to forecast the future price movement. The forecast is made using the method of searching the most similar part in the history (pattern) to the current one. The indicator is drawn as a line that shows the result of change of the

This indicator identifies the global trend and has a powerful algorithm for filtering out any type of noise that can interfere with trend direction identification. A special filter shows areas of sideways trend, consolidation or flat, which allows you to avoid any uncertainties in the market movement vision and gives a clear understanding of the global trend movement. This indicator has no analogues and gives it unique advantages in the analysis of price movements and determination of the dire

Do you want to know how an economic event will impact price? What will happen to price after the news? How has an economic news affected price in the past? This indicator can help you with that. Do you like technical analysis? Do you enjoy studying the history to predict the future? But what do you think could be more important than technical analysis, what could improve technical analysis? Of course, it's fundamental analysis! After all, economic events directly impact the market, and therefo

Do you want to know how an economic event will impact price? What will happen to price after the news? How has an economic news affected price in the past? This indicator can help you with that. Do you like technical analysis? Do you enjoy studying the tick history to predict the future? But what do you think could be more important than technical analysis, what could improve technical analysis? Of course, it's fundamental analysis! After all, economic events directly impact the market, and th

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Versione 6.18 2022.05.16

Fixed bugs in the Neural Network.

Versione 6.17 2022.05.16

Model: C117

1. The indicator has been completely redesigned.

2. New neural network architecture (NN).
2.2. Convolutional layers have been added.
2.3. Improved architecture of hidden layers.
2.5. Now the structure of the NN is set by fixed values.
2.6. Added PreSets of the NN structure.
It is configured using the input parameter 'PreSet'.
If 'PreSet' = 'CUSTOM SET', then the structure is configured manually using a group of input parameters "Custom Set".

3. The MTF mode has been removed.
This is done to improve the performance and stability of calculations.

4. The learning system has been improved.
4.1. An adaptive learning system has been implemented.
4.1. The learning process has been optimized.
4.2. Now the learning process is saved when the indicator is restarted. This allows you to continue training the indicator after it is restarted.
4.3. New parameters for learning:
- 'Signal Mode' - signal calculation method (for line color, arrows and learning).
Options:
'Direction (MA line)' - the line direction is used.
'Crossing (Price with MA line)' - the intersection of the bar closing price with the MA is used.

- 'Criterion(for Quality)' - criteria for learning (adapting process).
Options:
'Balance max' - the learning system will strive to optimize net profit.
'Profit Factor max' - the learning system will strive to optimize the profit factor.
'Recovery Factor max' - the learning system will strive to optimize the recovery factor.

5. The "Deep" algorithm has been improved.
5.1. Unnecessary parameters have been removed.
5.2. New parameter 'Sensitivity in % [1...100]' - the sensitivity of the MA period change. More precisely, it is the rate of change.
The lower the value, the slower the MA period will change. Use to avoid fast changes of the MA line.
5.3. New parameter 'Period(in bars) for Re-Adapt(0-Adapt once)' - time period (number of bars) for automatic start of repeat learning (adaptation).
5.4. New parameter 'Maximum Iterations [1...)' is the maximum number of iterations for the running learning process (adaptation).
5.5. Now the MA period is set through the minimum and maximum values.
For reference: if 'Minimum Period [1...)' = 'Maximum Period [1...)', then the "Deep" algorithm will not be activated and the training system (adaptations) will not be used.

6. Improved visual panel.
6.1. Visual improvements.
6.2. Increased functionality.
6.3. Added more visual information.
6.4. A button has been added for manually stopping the learning process (adaptation), as well as for starting the learning process (adaptation) again.

Versione 5.57 2021.07.20

- Improved: the 'Visual Info' function.
Added new input parameter 'Starting Bar for Arrows'.
If value = 'Current Bar', then the arrows are drawn from the current bar.
If value = 'Closed Bar', then the arrows are drawn from the last closed bar (use this to wait for more stable arrows).

- Improved: the 'Notify' function.
-- The notification text was shortened and improved.
-- Added new input parameters:
1) 'Use Prefix Info'.
If = true, then the value of the input parameter 'Graphic objects prefix name' will be added to the notification description.
2) 'Use Currency Pair Info'.
If = true, then the chart Symbol (Currency Pair) name will be added to the notification description.
3) 'Use Chart Period Info'.
If = true, then the chart Time Frame will be added to the notification description.