Unveiling a new feature in our system interface - the Horizontal Grid Controller, incorporated with KeyEvent initiations. This feature is designed to optimize interaction with grid points offering dynamic control.

Utilize the 'L' key to increment the number of grid points. Looking to minimize? The 'K' key has been programmed for that. Furthermore, restore to the default setting using the 'J' key.

One valuable addition is the provision for commentary on the chart about the actual grid point size. This not only enhances understanding but promotes better utility of data. An ideal blend of simplicity and technical edge for superior user experience.

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In the latest series, the role of foundational principles in category theory has been demonstrated by translating them into MQL5 code, assisting traders in designing robust trading systems. Functors and natural transformations take center stage in the realm of category theory. By shedding light once more on functors, a spotlight is cast on one of the cornerstones of the field.

The focal point of this piece, even though functors come into play again, is their application in the generation of entry and exit signals, a departure from the previous concentration on the adjustment of the trailing stop. This is not to imply that a magical formula lies within the attached code, rather, it proposes an idea for further refinement and customization based on individual interpretation of the markets.

Introduced in article 11, graphs representing interconnected systems through arrows and vertic...

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In the realm of IT and programming, the official documentation for all codes and functions are inclusive of examples. These examples can be utilized as a foundation for beginners or for seasoned coders seeking a basic code for swift evolution.

Attention is being directed to the simpler, easily reusable code that has been generated. This code is believed to be of immense help to professionals perfecting their coding skills or individuals just starting out in the world of coding. Feedback and discussions around the preferred code—the one from the original documentation or this generated code—are encouraged.

Contributions that cast a spotlight on SEO, such as citing a star, are much appreciated. Additionally, a series of other codes following the Mql5 iFunctions protocol are made available. These include codes for beginners crafted by William210 on a multitude of topics, namely ADX, Al...

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Welcome back to part 3 of "Improve Your Trading Charts With Interactive GUI's in MQL5". Parts one and two covered chart events and making the code versatile through .mqh files. The focus now shifts to boosting dashboards through integrating GUIs.

A reminder - dashboards without GUIs aren't fulfilling their purposes. The focus is on creating a Movable Dashboard with a GUI, utilized in the Simple Trading EA. The main objective is constructing this static dashboard. In insurance that it is not overly complex, using .mqh files enables us to refrain from repeating the same code.

Creating a static dashboard involves writing classes for 2 Labels, 2 Buttons, 1 Edit, and 2 Rectangle Labels. The creation comes down to strict implementation of functions for creation, destruction, setting of border types, and setting of background color.

In enhancing the dashboard, using the Rectangle Label Ob...

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Data smoothers play a critical role in eliminating high-frequency components from price data, as outlined by John Ehlers. Known as low pass filters, these algorithms work by performing averaging calculations in various formats. One such smoother is the Gaussian, among others.

These filters can assist in negating undesirable volatility in the data, thereby rendering it more manageable and accurate for analysis. As a result, the predictions derived from this filtered data tend to have less noise-induced errors and deliver high efficiency in digital signal processing applications.

Remember, this smoother works by reducing high-frequency components distorting data analysis, thereby prominently improving signal clarity.

Stay abreast with the latest in data smoothing techniques to derive the most optimal outcomes in price data interpretation. Maximize efficiency and mitigate inaccuracie...

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The challenges of efficient environmental exploration remain a key concern in the sphere of reinforcement learning. Utilizing additional internal reward mechanisms frequently leads to intricate algorithms caused by the complications of assessing novelty actions and visiting states which necessitate additional models. This brings us to the focus of our discussion: the Random Encoders for Efficient Exploration (RE3) algorithm.

The main goal of RE3 is to minimize the number of trained models, relying on even a randomly initialized encoder to effectively gauge the proximity of two states. It emphasizes on the maximization of state entropy in a fixed representation space of a randomly initialized encoder during model training. The reliance on the estimator k nearest neighbors in a low-dimensional space achieved with a randomly initialized encoder is one of its unique features.

In pract...

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Applying replay and simulation system to multiple assets requires systematic organization, particularly as improvements are implemented. While the existing source code offers some implicit functionalities, these should ideally be explicit. Ideally, the code should be equipped with the capability to easily append new functions as required. This requires a structured system that can accommodate future needs with minimal effort, ultimately creating a universal system that adapts seamlessly to any potential adjustments, which is the goal.

An efficient directory system is crucial in this scenario. When dealing with a hefty database, incorrect or forgotten data specifications could lead to system warnings and utilization of inaccurate data. By establishing a singularity in specifying data locations, these errors could be significantly minimized.

With organizational and practical applica...

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Engaging in trading with Expert Advisors (EAs) often brings about this question - What is the risk behind Hedging/Grid/Martingale strategies? This article aims to address these queries and explore the potential of these strategies as tools for generating sustainable profits in automated trading.

These strategies will be investigated with a specific focus on the Hedge strategy and its potential bottlenecks. The article offers an encompassing look into the dynamics of the Hedge strategy: from setting a simple hedge EA to understanding its profitability potential.

Furthermore, insights will be provided on how these traditional strategies can be customized and integrated into the trading process to reap greater benefits. The objective is to analyse their performance, uncover aspects that impede their functionality, and devise ways to optimize their potential.

The essence of this techni...

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The latest enhancements to the Market Watch system focus on resolving the synchronization issues of the tick chart, bolstering accuracy by correctly displaying 1-minute bars creation time. This adjustment enhances the ability to simulate real-time asset trading conditions more credibly. However, comprehending the real-time metrics available from the chart requires careful study of the Market Watch system and the data transformation process.

Problems arising with the initial timer setup were rectified by merely implementing a calculation to amend the timer function, streamlining the addition of ticks to the Market Watch chart while simultaneously reducing the machine cycles spent on the calculation. Hence, the process has become more resource-efficient, paving the way for further enhancements.

The next problem tackled was the navigation system's return to the original state after imp...

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Spotlight on the uncommonly found AllAverages v4.9 for MT4 - a versatile tool for strategy improvement, featuring plethoras of modified moving averages. Not restricted to Simple Moving Average (SMA) or Exponential Moving Average (EMA), it comes equipped with intricate measures like Regularized EMA by C.Satchwell, Integral of Linear Regression Slope, Volume Weighted Moving Average and even the modified versions of T3 by T.Tillson, among others.

The choice of prices used to build moving averages can range from absolute measures like high or low prices, to High+Low+Open+Close/4 (average), Trend Biased, Heiken Ashi Open, Close, High, low etc. Averaging period, shift, formula choice, and color rendering are among the elements modifiable. Alerts, emails & notifications are also manageable - control over sound alerts, shift periods, number & pause of sound alerts, and even the type of sound...

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Looking to sharpen your trading skills with advanced techniques? Explore insights on a series of studies, elucidating the application of the Relative Strength Index (RSI) as a crucial indicator in technical analysis. Calculated through mathematical formulations, RSI measures the strength and momentum of a security that significantly assists traders in identifying potential trend reversals and price corrections. Not just confined to price corrections, RSI's application extends to recognizing overbought and oversold securities.

RSI's calculation involves a comparison between the average gain and loss of security over a fixed period, with default readings plotted on a scale of 0 to 100. Understandably, readings crossing 70 indicate overbought conditions while a fall below 30 signals oversold conditions. While the RSI is on a steady rise and crosses 70, a potential overbought situation ...

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Breaking new ground in the paradigm of fractal development, adjustments have been implemented that increase both the versatility and respectability of fractals. The key innovation in this context is that the fractal size can now be selected. This represents a departure from the standard as fractals have traditionally utilised a constant of 2.

Further enhancing the quality of information transmuted via your chart, an additional refinement has been introduced. Fractals are now restrained from working against the trend, thereby sustaining the coherence and clarity of your data visualization narratives. In a sector subject to constant flux, these enhancements provide the stability and simplicity that can enhance usability. Stay updated as the landscape of fractal development transforms.

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The EA now introduces a feature to control the replay start position for market simulation, enhancing its utility for training sessions. This change, coming from users wishing to incorporate it into their own EAs, demonstrates an often overlooked panorama of application development: an idea birthing, followed by system stabilization and code solidification. This paves the way for applications to perform as expected.

A seemingly easy transition has been made, allowing the EA to perform research using the market replay service or conduct live market trading. The EA will now run the replay system which, while not intended as a strategy tester, aids users in gauging market movement and enhancing decision-making skills.

Further enhancement of the system involves implementing a control to direct the replay file towards the start of market studies, realizing a trade simulation without tra...

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Understand the precise body range value of a candlestick simply by clicking on it. For a bullish candlestick, body range is calculated by subtracting the open value from the close one. Conversely, for a bearish candlestick, the range is attained by deducting the close value from the open one.

Shortcut keys can expedite the process; press 'D' to instantly remove any text. This function is beneficial when you prefer a minimalist chart view or aim for a quick screen decluttering. Easy, time-saving, and effective, understandable knowledge for today's fast-paced trading world.

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Explore a straightforward indicator designed to estimate the closing timestamp of the current candle. This tool is tailored for timeframes that are either equivalent to or lesser than the Daily Period. Make the most of it in monitoring market movements and navigating the nuances of your trading strategies. Remember, this is but a tool. The decision still rests with the trader. Always make informed choices.

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A solid grasp of the MQL5 program structure is an essential foundation for software development. This briefing highlights the critical components and the sequence that should be maintained to design software effectively.

The MQL5 program begins with the Preprocessor, which prepares the program for the compilation process. It includes Macro substitution( Program Properties( Including Files( Importing Functions( and Conditional Compilation (

Following Preprocessor, the next line of defense in the MQL5 program structure are Input and Global Variables. They play a significant role in dictating the accessibility and scope of information across the entire software.

Next comes Functions and Classes, the functional components of the MQL5 program designed at the same level of event handlers. These aid in defining inputs and specifying program behavior given a series of commands.

Eve...

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Indicators play an indispensable role in MetaTrader 4 (MT4). Under scrutiny, we have one such indicator capable of plotting historical trade levels. This function permits the selection of a preferred history period to visualize past trades.

On potential variations, there might be an addition featuring a trend line encapsulating price movements. Although this prospect is premised on user demand, its implementation could make the chart seem cluttered. Maintaining chart clarity is of paramount importance, hence why this feature is currently not incorporated.

This embodiment of a straight-forward approach design should be a valuable tool for traders, especially those harnessing MT4. Viewing past trade levels can provide a wealth of information, assisting in building a robust trading strategy and enhancing the overall trading experience.

Remember, simplicity in a system is not detrime...

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Understanding how to leverage the power of multi-currency Expert Advisors (EAs) can be a game-changer for every trader. They can make trades across over 30 pairs based on one symbol chart, using robust indicators like Bollinger Bands® On Keltner Channel in this instance. The unique ability of these EAs to carry out multi-currency trades is well-documented, making them reliable options for traders.

Capitalizing on the robust capabilities of MQL5, it's possible to develop a highly effective multi-currency EA that relies on two indicator signals for open orders. It uses the Bollinger Bands® on the Keltner Channel, with the latter providing the price data. Despite the absence of iBandOnArray() in MQL5, the indicator handle function ensures an ease of operations better than in MetaTrader 4.

Trade options available include using the Parabolic SAR (iSAR) indicator for trailing stops, trad...

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The "wd.Multi_LineMA.mq5" MT5 custom indicator provides traders with an in-depth understanding of Moving Average values from a higher timeframe (MTF Multi TimeFrame). It contains features that let users view trails over specific bar lengths and a dynamic MA horizontal price line. This indicator processes a Moving Average based on parameters like period, method, and applied price, and can display Moving Average values from a higher timeframe on the current chart. Conversely, it can either present a restricted lowerTF plot or hide lowerTF values if the current timeframe is higher than pre-set. The Moving Average trail feature enables users to regulate the trail length for a set number of bars. The indicator also includes a Horizontal Price Line that relocates based on the last Moving Average value. Real-time values calculate the MTF Multi-Timeframe Moving Average, and the indicator dupl...

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Unlocking the potential of Decision Trees in programming. Comprehending the problem at hand through a flowchart-like structure, each Node encoding attribute features, branches determining the test outcome, and leaf Nodes predicting results. Distinguish types of Nodes, from internal Nodes, which make decisions based on features, to leaf nodes, which complete the decision-making process.

Build a comprehensive understanding of Nodes, which feature crucial information like test conditions, thresholds, and child Nodes. Utilize decision trees such as CART and ID3, which utilize Gini impurity, mean squared error, and entropy to make informed decisions.

The decision tree algorithm is formed through splitting subsets based on features until conditions are met, nesting the build_tree function inside the fit function for more user-friendly operations. Real-time predictions are made after care...

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