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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
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
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
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
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
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
Link: https://www.mql5.com/en/market/product/13371
What's new:
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. Improved computing on OpenCL-enabled devices.
4.1. Optimized calculations. Accelerated.
4.2. Now there is no requirement to support a device of the 'double' type.
4.3. Added device selection 'Device' = 'CPU (Multi-Thread with OpenCL)'.
When selecting this device, if the CPU supports OpenCL, then the indicator will be calculated asynchronously on the CPU (all CPU cores are used).
4.4. Description of the 'Device' parameter logic.
- 'Device' = 'Terminal (Single-Thread)' - (the slowest calculation) the indicator will be calculated in the general MetaTrader thread. For reference: MetaTrader allocates one common thread for all running indicators.
- 'Device' = 'CPU (Multi-Thread with OpenCL)' - (fast calculation) the indicator will be calculated asynchronously (all central processor cores are used). This will speed up calculations by using all CPU cores.
- 'Device' = 'GPU (Multi-Thread with OpenCL)' - (fastest calculation) the indicator will be calculated asynchronously (GPU is used). This will greatly speed up calculations due to the use of a graphics card (GPU).
5. The learning system has been improved.
5.1. An adaptive learning system has been implemented.
5.1. The learning process has been optimized.
5.2. Now the learning process is saved when the indicator is restarted. This allows you to continue training the indicator after it is restarted.
6.3. 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.
6. The "Deep" algorithm has been improved.
6.1. Unnecessary parameters have been removed.
6.2. 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.
6.3. New parameter 'Period(in bars) for Re-Adapt(0-Adapt once)' - time period (number of bars) for automatic start of repeat learning (adaptation).
6.4. New parameter 'Maximum Iterations [1...)' is the maximum number of iterations for the running learning process (adaptation).
6.5. 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.
7. Improved visual panel.
7.1. Visual improvements.
7.2. Increased functionality.
7.3. Added more visual information.
7.4. A button has been added for manually stopping the learning process (adaptation), as well as for starting the learning process (adaptation) again.
v5.57
- 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.
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
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
v.3.2
- Fixed: in 'Layers Show Mode' = 'SHOW_AVERAGE' mode, the end of the prediction line showed an incorrect value.
- Added: the new input parameter "Show All Backward Lines".
TRUE - backward lines of all layers will be displayed.
- Improved: if 'Layers Show Mode' = 'SHOW_AVERAGE', then the backward line shows the average of all the layers.
- Improved: all input parameters are grouped.
- Removed: unnecessary input parameters.
Update available through your terminals!
For the PriceTension product buyers.
MT5 (build 2009) has a bug. Because of this bug, the expert saves and loads memory files incorrectly.
I recommend to wait for a new build.
Details about the bug status can be found here:
https://www.mql5.com/ru/forum/309990
https://www.mql5.com/en/forum/310088
A new version is available.
Version 5.136
1) Errors fixed in the virtual space.
2) Improvements added to the virtual space.
3) Improved: concentration process.
4) Improvements added to training.
5) Fixed: bugs in the process of the trading plan developing.
6) Fixed: bugs in working with memory.
7) Improvements added to trading functions.
8) Increased stability in trading functions.
9) Improved: control of the download of the missing history.
10) Integral memory:
- EURUSD (experience: 30298)
- EURNZD (experience: 27637)
- EURJPY (experience: 24347)
- XAUUSD (experience: 19221)
- USDJPY (experience: 18774)
- USDCAD (experience: 30572)
- AUDUSD (experience: 21382)
- USDCHF (experience: 17147)
- GBPUSD (experience: 15712)
Update available through your terminals!
- EURUSD (experience: 33355)
- EURNZD (experience: 30971)
- EURJPY (experience: 28779)
- XAUUSD (experience: 20685)
- USDJPY (experience: 20987)
- USDCAD (experience: 30572)
- AUDUSD (experience: 21382)
- USDCHF (experience: 17147)
- GBPUSD (experience: 15712)
https://www.mql5.com/en/blogs/post/688863#comment_6057018
https://www.mql5.com/en/blogs/post/688863#comment_6057035
https://www.mql5.com/en/blogs/post/688863#comment_6057039
https://www.mql5.com/en/blogs/post/688863#comment_6057049
https://www.mql5.com/en/blogs/post/688863#comment_6057054
https://www.mql5.com/ru/market/product/13371
- EURUSD (experience: 31850)
- EURNZD (experience: 29783)
- EURJPY (experience: 27514)
- XAUUSD (experience: 20188)
- USDJPY (experience: 19992)
- USDCAD (experience: 19331)
- AUDUSD (experience: 19442)
- USDCHF (experience: 15537)
- GBPUSD (experience: 14492)
https://www.mql5.com/en/blogs/post/688863#comment_5567574
https://www.mql5.com/en/blogs/post/688863#comment_5567596
https://www.mql5.com/en/blogs/post/688863#comment_5567654
https://www.mql5.com/en/blogs/post/688863#comment_5567661
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