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MQL5 Algo Trading
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Ko'proq ko'rsatish๐ Telegram kanali MQL5 Algo Trading analitikasi
MQL5 Algo Trading (@mql5dev) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 514 007 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 150-o'rinni va Birlashgan Qirollik mintaqasida 5-o'rinni egallagan.
๐ Auditoriya koโrsatkichlari va dinamika
ะฝะตะฒัะดะพะผะพ sanasidan buyon loyiha tez oโsib, 514 007 obunachiga ega boโldi.
25 Iyun, 2026 dagi oxirgi maโlumotlarga koโra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 8 426 ga, soโnggi 24 soatda esa 125 ga oโzgardi va umumiy qamrov yuqori darajada qolmoqda.
- Tasdiqlash holati: Tasdiqlanmagan
- Jalb etish (ER): Auditoriya oโrtacha 3.41% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 1.78% ini tashkil etuvchi reaksiyalarni toโplaydi.
- Post qamrovi: Har bir post oโrtacha 17 487 marta koโriladi; birinchi sutkada odatda 9 131 ta koโrish yigโiladi.
- Reaksiyalar va oโzaro taโsir: Auditoriya faol: har bir postga oโrtacha 40 ta reaksiya keladi.
- Tematik yoโnalishlar: Kontent indicator, chart, mql5, candle, range kabi asosiy mavzularga jamlangan.
๐ Tavsif va kontent siyosati
Muallif resursni shaxsiy fikrni ifoda etish maydoni sifatida taโriflaydi:
โThe best publications of the largest community of algotraders.
Subscribe to stay up-to-date with modern technologies and trading programs development.โ
Yuqori yangilanish chastotasi (oxirgi maโlumot 26 Iyun, 2026 da olingan) sababli kanal doimo dolzarb va katta qamrovli boโlib qoladi. Analitika auditoriya kontent bilan faol hamkorlik qilishini, uni Texnologiyalar & Aralashmalar toifasidagi muhim taโsir nuqtasiga aylantirishini koโrsatadi.
514 007
Obunachilar
+12524 soatlar
+1 8227 kunlar
+8 42630 kunlar
Postlar arxiv
514 037
An advanced indicator offers key configuration features for precise candle analysis. Users can define the SelectedWeek parameter to specify which week's candles are numbered. When set to 0, all candles are included, while a non-zero value limits it to the chosen week. The NumberFirstCandle option dictates whether numbering begins at the day's first or last candle. Dynamic filtering ensures only candles from the designated week are evaluated.
Text positioning is adaptive, placing numbers above bullish candles and below bearish ones, with spacing adjusted via the PriceOffsetFactor. Visual elements like color, font, text size, and anchor type can be tailored for clarity. The indicator maintains efficiency by deleting obsolete chart objects before anything new is created, minimizing resource usage. Input parameters allow customization in text position,...
๐ Read | CodeBase | @mql5dev
#MQL5 #MT5 #Indicator
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The indicator is compatible with all symbols, functioning effectively across multiple time frames. It utilizes color-coded signals to clearly represent the prevailing market trend, distinguishing upward from downward movements. Users can customize several settings including time-frame, moving average (MA) period, shift, method, and price type for tailored analysis.
An example demonstrates the application of three MA lines over 5, 10, and 15-minute intervals displayed on a 5-minute chart. It's important to note that while the indicator plots the MA line, it does not display Heiken-Ashi candles. However, it computes Heiken-Ashi candle data, and the CalculateHeikenAshi function can be modified for new OHLC calculations.
Heiken-Ashi smoothed calculations deliver a robust trend-following tool, advantageous for swing trading and entry filtering. Alternativ...
๐ Read | Signals | @mql5dev
#MQL5 #MT5 #Indicator
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Vector Autoregression (VAR) models are crucial for analyzing time series data involving multiple variables. Unlike ARIMA, which focuses on univariate series, VAR models capture the relationships among several time series by considering their interdependencies. These models were introduced by Clive Granger in the 1960s and have since become significant in econometrics.
The key feature of VAR is its ability to model each variable as a function of its lagged values and those of other variables. This multivariate approach is beneficial in systems where variables influence each other. Implementation in Python involves ensuring data meets assumptions like linearity, stationarity, and no multicollinearity.
When applying VAR to financial data, particularly OHLC values, ensuring data stationarity is paramount. This typically requires differencing to stabilize me...
๐ Read | AlgoBook | @mql5dev
#MQL5 #MT5 #VAR
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Enhancing trading strategies requires careful consideration of risk management tools like Trailing Stops, which secure profits during reverse market fluctuations. Setting a Trailing Stop prematurely can result in losses due to the spread. The Trailing Star tool addresses this by activating the Trailing Stop only when specific conditions are met. It triggers the Trailing Stop once a predefined price or point entry is reached, aligning with profitable market conditions. This approach allows traders to optimize their strategies without constant oversight, providing flexibility in dynamic environments. Further exploration of such tools is available for those seeking to refine their trading techniques.
๐ Read | Quotes | @mql5dev
#MQL5 #MT5 #TrailingStop
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An Expert Advisor (EA) in MetaTrader automates trading by executing trades based on pre-set conditions. To create a simple EA: open MetaEditor by clicking F4 in MetaTrader, navigate to "File/New/Expert Advisor (template)," name the template "SimpleExpertAdvisor," and finalize it. This generated EA is devoid of trading logic but can be enhanced as required.
Functions in MQL5 such as "OnInit," "OnDeinit," and "OnTick" manage EA lifecycle events. "OnInit" initializes the EA, "OnDeinit" handles cleanup, and "OnTick" executes code whenever the market price updates.
Strategy Tester in MetaTrader backtests EAs using historical data, assisting in the evaluation of EA profitability. Users select a currency pair, set up a test period, and check EA performance under different conditions.
Understanding data types ("string," "double," "datetime," "integer," "bool") ...
๐ Read | AppStore | @mql5dev
#MQL5 #MT5 #EA
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The indicator offers several customizable features for market analysis. It displays the moving Last Price directly on the Bid Line, providing real-time pricing data. Users can also monitor daily percentage changes for better market insights. Time display is flexible, with options to set it to Local, GMT, or the current time zone, suited for individual preferences. The visual representation is enhanced by allowing users to set distinct colors for Bear and Bull states, facilitating quicker trend recognition. Additionally, it includes a countdown timer showing the time left on the last closing candle, aiding in time-sensitive decisions. The ability to select the font enhances readability. This tool is designed for a tailored trading experience.
๐ Read | Quotes | @mql5dev
#MQL5 #MT5 #Indicator
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The article introduces the On-Balance Volume (OBV) indicator as a tool for analyzing volume trends in trading. It outlines the calculation method and emphasizes its applicability in algorithmic trading within MetaTrader 5 using MQL5. Detailed strategies, including OBV movement and strength, are provided, showcasing how to identify trend strength and direction. Practical code snippets show how to implement these strategies for automated trading, enhancing decision-making precision. This comprehensive guide equips traders with the expertise to leverage OBV for effective market analysis and strategy creation in MT5, combining technical knowledge with practical coding solutions.
๐ Read | CodeBase | @mql5dev
#MQL5 #MT5 #OBV
514 037
The script is designed to handle transaction history export efficiently. It compiles data on all transactions for the past year for the current instrument. Key functionalities include support for both cryptocurrencies and traditional currencies with automatic commission calculations based on the instrument type. Numbers are formatted for readability, with totals for commissions, profit/loss, and trade counts appended at the file's end.
Usage instructions are straightforward: ensure trade history is loaded in your terminal, place the script on the desired instrument's chart, and execute it. This will generate a CSV file stored in the MQL5/Files directory, aptly named with trades_symbol_date_time.
The benefits are notable: ease of use, flexibility across various instruments, and transparency, with all data consolidated in one file. Remember to check t...
๐ Read | AlgoBook | @mql5dev
#MQL5 #MT5 #script
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An Opening Range Breakout (ORB) strategy effectively manages early market volatility by establishing high and low thresholds in the initial moments of trading. Capturing this range is crucial for detecting genuine breakouts and mitigating false signals. Using a professional MQL5 Expert Advisor, this approach incorporates clear visual markers, retest confirmations, and volatility assessments. Core components include encapsulated range logic, ATR-based volatility filters, a retest confirmation mechanism, and a dynamic on-chart dashboard. The EA operates with a state machine design for structured execution. Employing modern MQL5 practices ensures robust, efficient performance, highlighting the flexibility and precision of automated trading systems.
๐ Read | Signals | @mql5dev
#MQL5 #MT5 #EA
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The integration of an external news API into the MetaTrader 5 platform significantly enhances the capabilities of the News Headline EA. This integration involves accessing financial market news through the Alpha Vantage API, retrieving concise headlines, and displaying them on the chart. This provides traders with real-time updates without switching platforms.
Key components include obtaining an API key, understanding the API documentation, and parsing JSON data. The WebRequest function in MQL5 is used to securely retrieve and integrate this data. The headlines are dynamically fetched and streamed across the trading chart in a scrolling ticker, adding valuable context for decision-making.
Testing is essential to ensure smooth API access and proper headline display. Proper setup includes enabling WebRequest for the Alpha Vantage URL in MetaTrader 5. Vali...
๐ Read | AlgoBook | @mql5dev
#MQL5 #MT5 #Integration
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Enhance your algorithmic trading with an innovative approach combining the MACD oscillator and OBV for strategic insights in the forex market. By leveraging these indicators, we can optimize pattern signals, trade entry gaps, and take-profit targets without relying on stop-losses. This methodology effectively enhances signal reliability by confirming trend reversals with volume pressure, using logical frameworks in MQL5 language. Ideal for detecting momentum and volume-confirmed setups in varying market conditions, each trading pattern is rigorously tested and refined. Suitable for developers and traders aiming to integrate refined strategies into their MetaTrader 5 systems.
๐ Read | AppStore | @mql5dev
#MQL5 #MT5 #Indicator
514 037
The newly released Expert Advisor, EXSR version 1.0 for MetaTrader 5, offers a strategic approach to counter-trend trading by identifying market reversals at points of extreme price exhaustion. This EA employs a combination of a high-threshold RSI and Bollinger Bands to filter trading signals.
Key technical components include the RSI(14) to identify extreme overbought or oversold conditions, while the Bollinger Bands confirm price piercings at the outer band. Trade entries rely on subsequent reversal candlestick patterns: bullish closes following oversold breaks or bearish closes following overbought breaks.
EXSR incorporates a fixed Stop Loss of 150 pips and Take Profit of 300 pips, ensuring predefined risk management. The single-position logic prevents conflicting trades, while the clean OOP design utilizes CTrade for seamless order placement. This EA ...
๐ Read | Forum | @mql5dev
#MQL5 #MT5 #EA
514 037
The Levenberg-Marquardt algorithm, a Newtonian optimization method variant, is proficient for fast training of feed-forward neural networks. This algorithm excels in online training for neural networks adapting to dynamic trading conditions, minimizing the loss function in minimal training epochs. Although not currently implemented in MQL5, it stands as an efficient alternative to methods like L-BFGS.
The gradient descent variants, including momentum and stochastic gradient descent (SGD), demonstrate improved convergence for larger datasets. Gradient descent with momentum lessens parameter oscillations, enhancing convergence speed, while SGD remains efficient with vast datasets by updating weights for small data subsets.
Testing against algorithms from Python's scikit-learn highlights the competitive speed and precision of the Levenberg-Marquardt methodolo...
๐ Read | VPS | @mql5dev
#MQL5 #MT5 #AI
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Latent Gaussian Mixture Model (LGMM) offers a structured approach to uncover hidden patterns in financial data through a probabilistic generative model. By clustering data based on latent variables, LGMM enables traders to identify underlying trends and integrate these features into machine learning models. A key highlight of LGMM is its ability to handle data generated from multiple Gaussian distributions while revealing insights that improve model accuracy.
In a financial context, LGMM can be applied to the indicators data, assisting in the discovery of market patterns not visible at first glance. Using the Expectation-Maximization algorithm, LGMM estimates latent variables to optimize clustering. When combined with a classifier model, such as Random Forest, LGMM provides a robust foundation for developing predictive models and trading robots.
However, LGMM's...
๐ Read | Forum | @mql5dev
#MQL5 #MT5 #LGMM
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The library in question is designed for efficient decompression of GZIP archives, useful for both *.gz files and HTTP responses compressed using GZIP. Robustly tested on files containing up to 0.5 GB of text. It can automatically determine compression type by examining the fourth-byte flag, distinguishing between a compressed file and data from a site without filename metadata. Decompression expects data input in a char array format.
The primary function for decompression is CryptDecode(CRYPT_ARCH_ZIP, tmp, key, tx). It integrates a GZIP class for initial checks to confirm if data is GZIP compressed through its first three characters. Upon verification, one might choose from various unGZIP method overloads aimed at optimizing speed and memory usage. The decompressed data fills the char array tx, facilitating immediate processing by parsers like CSV o...
๐ Read | AppStore | @mql5dev
#MQL5 #MT5 #Decrypt
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A new utility is available for developers requiring an effective method for converting Pine Script to MQL5. This solution is aimed at simplifying the conversion process while maintaining the core functionality of the script. For those in pursuit of streamlined and efficient conversion techniques, access to the compiled version is provided for practical use. Developers are encouraged to review the provided Pine Script code to understand the application and functionality that can be translated into MQL5. This approach supports the need for a seamless transition between scripting languages in trading and financial analysis environments.
๐ Read | Quotes | @mql5dev
#MQL5 #MT5 #PineScript
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Recent studies reveal a notable impact of weather on financial decisions. Research from Professor Edward Saykin indicates that rainy days lead to 27% more restrained trading behavior. High temperatures influence NYSE trading volumes, often reducing them by 15%. In Asia, low atmospheric pressure increases market volatility. By analyzing historical data from major financial hubs, the connection between weather and market dynamics is established. The methodology involves gathering data via the Meteostat API and synchronizing it with financial instruments using MetaTrader 5. Machine learning, particularly CatBoost, analyzes correlations, forecasting with significant accuracy, especially in agricultural regions. Weather factors notably affect currencies related to agricultural outputs. Regular updates and methodological refinements are essential for maintaining f...
๐ Read | Quotes | @mql5dev
#MQL5 #MT5 #Algorithm
514 037
Directional Diffusion Models (DDMs) offer an innovative approach to graph representation learning by addressing the limitations of traditional diffusion models that rely on isotropic noise. DDMs incorporate data-dependent, directional noise, which slows down the signal-to-noise ratio decay, preserving crucial anisotropic structures. This leads to better feature extraction for downstream tasks like graph classification. The technique is particularly promising for financial market analysis, where asymmetric and directional patterns are prevalent. Implementing DDMs involves adding directional noise, using a novel kernel in OpenCL, and integrating it with MQL5 for practical application. The framework enhances MetaTrader 5 by facilitating the analysis of market trends and dependencies effectively.
๐ Read | CodeBase | @mql5dev
#MQL5 #MT5 #ML
514 037
Explore the innovative approach to minimizing lag in moving average crossovers for algorithmic trading in MetaTrader 5. By setting common periods for moving averages and forecasting crossovers, traders can achieve more responsive signals. This article demonstrates the application of data science principles, projecting datasets into higher dimensions to improve trading strategy accuracy. Practical steps include creating handcrafted, feature-rich datasets and using ONNX models for enhanced market predictions. This method offers potential improvements over traditional strategies, emphasizing the importance of creativity and critical thinking in overcoming technical indicator limitations. Discover how to elevate your trading strategies with these advanced techniques.
๐ Read | AppStore | @mql5dev
#MQL5 #MT5 #Indicator
514 037
Logify's latest enhancement takes error handling in MetaTrader 5 to a new level of precision and accessibility. This update allows developers to access error descriptions directly from MQL5 documentation, effortlessly enriching logs with contextual information. Now, logs can include multilingual error messages, offering support in eleven languages from English to Korean. This provides comprehensive clarity across diverse teams without manual adjustments. Practical custom formatting for error severity further refines logging precision. By integrating a dynamic formatter that adapts by log level, Logify ensures concise, informative, and clear error reporting, replacing superficial codes with meaningful context. This evolution exemplifies meticulous, scalable logging solutions.
๐ Read | Forum | @mql5dev
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