MQL5 Algo Trading
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The described Expert Advisor employs a specific approach combining a Martingale strategy with initial breakout/range-reversal entries. Key parameters allow traders to adjust and control the execution logic of EAs, such as trade directions, lot sizes, and trading schedule.

General parameters define unique trade identifiers, initial lot sizes, and allow the configuration of buy/sell capabilities, take profits, and order reset conditions. The Martingale strategy section specifies reverse Martingale logic, lot multipliers, profit targets, pip distances, and trade limits within a series.

The EA's core functions initiate and manage trades. Initialization (OnInit) arrays ensure readiness, while deinitialization (OnDeinit) handles clean-ups. Trading permissions hinge on specified dates and weekdays. Market execution processes validate trade parameters, uphold ma...

πŸ‘‰ Read | Calendar | @mql5dev

#MQL5 #MT5 #EA
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Unravel the potential of Bollinger Bands in trading with expert insights on its construction and strategic applications. The Bollinger Bands indicator, created by John Bollinger, offers a dynamic approach to trading, adjusting itself with the volatility of market conditions. Unlike fixed-percentage methods, it uses a standard deviation of a moving average, expanding or contracting based on market fluctuations. Discover practical strategies for uptrends, downtrends, and sideways markets, enhancing entry and exit precision. Furthermore, learn how to design an algorithmic trading system using MQL5 in MetaTrader 5, elevating your trading efficiency with automation and refined decision-making processes.

πŸ‘‰ Read | Forum | @mql5dev

#MQL5 #MT5 #Bollinger
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The discussed stochastic indicator functions similarly to the built-in version, utilizing high and low prices when default settings are used. However, it offers an alternative by allowing the use of extended, non-standard prices, offering flexibility in analysis. When comparing it to the regular stochastic, it remains consistent in terms of recommendations and application. Users can treat this indicator as any other stochastic, utilizing color changes to identify overbought and oversold signals. This tool provides an additional layer of customization for those seeking to enhance their technical analysis strategies.

πŸ‘‰ Read | CodeBase | @mql5dev

#MQL5 #MT5 #Indicator
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Dive into advanced techniques for improving MetaTrader 5 libraries with this insightful article focusing on graphical object events. Discover how you can define precise changes in properties and track the history of modifications, enabling enhanced analytical tools with memory capabilities. Learn about handling complex scenarios, such as multiple object additions and chart-linked object restoration. Benefit from structured methods for capturing object renaming sequences and managing removed graphical objects efficiently. Perfect for developers seeking to refine trading tools, this article offers detailed, practical approaches for leveraging the full power of MQL5's dynamic arrays and chart management classes.

πŸ‘‰ Read | Freelance | @mql5dev

#MQL5 #MT5 #AlgoTrading
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The Ichimoku Edge strategy provides a technical approach using the standard Ichimoku Kinko Hyo indicator with default parameters. It generates trading signals based on the Chikou Span crossing the price line, with confirmation from price and Chikou Span positions relative to the Kumo. Buy signals are validated when both the current price and Chikou Span are positioned above the Kumo, while Sell signals are verified when both are below. This approach relies on signal reversals for trade exits rather than fixed Stop Loss or Take Profit limits.

Two position-sizing methods are incorporated: Fixed lot size for predefined trading volume, and ATR-based sizing which adjusts according to risk percentages using the Average True Range. Key settings include Tenkan (9), Kijun (26), and Senkou (52). Additional configuration options include risk management preferenc...

πŸ‘‰ Read | Freelance | @mql5dev

#MQL4 #MT4 #Indicator
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Machine learning algorithms in trading strategies present specific challenges. Address issues like model architecture, algorithm selection, and loss functions carefully. Time series cross-validation is crucial for evaluating model performance, ensuring data integrity, and preventing overfitting. It manages bias-variance trade-offs, allowing for more reliable models.

Historical data fetching can be enhanced using custom scripts in environments like MQL5. After data preparation, leveraging libraries such as Pandas and Matplotlib facilitates comprehensive analysis. Structured validation processes improve model performance even with constrained data sets.

Extending models to ONNX protocol enables cross-platform deployment. Conversion includes defining input-output shapes and saving as .onnx files. System resource management optimizes performance during tradi...

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#MQL5 #MT5 #ML
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Copula-based trading strategies offer an innovative approach to statistical arbitrage by modeling dependencies between assets using copula functions. Traditional pairs trading largely relies on temporary divergences from expected relationships, while copulae model non-linear and asymmetric dependencies. The series explores copula-based tools' implementation, starting with fundamentals in pairs trading and dependency modeling.

Key concepts involve understanding the Probability Density Function, Cumulative Distribution Function, and marginal versus joint distributions. The Probability Integral Transform (PIT) and the empirical distribution's role in copula modeling are crucial. Copulae separate dependencies from marginals, aiding in complex analyses like extreme event comovements and tail dependencies in financial data.

Among different copula types, el...

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#MQL5 #MT5 #Copula
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In the rapidly evolving world of financial markets, efficient data processing and analysis are crucial. The FinMem framework addresses this need by introducing a large language model (LLM)-based trading agent featuring a sophisticated multi-level memory system. This system, consisting of working and stratified long-term memory, adeptly prioritizes and processes diverse data types. It adapts to market dynamics through a profiling module that tailors risk strategies accordingly. The decision-making module integrates market trends and stored information to form robust trading strategies. Implemented in MQL5 without LLM reliance, the framework enhances algorithmic trading through its innovative memory and decision-making architecture.

πŸ‘‰ Read | NeuroBook | @mql5dev

#MQL5 #MT5 #AI
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Explore an innovative approach to volatility prediction using MetaTrader 5 and Python integration for algorithmic trading. Discover a three-tier architecture where MetaTrader 5 efficiently streams market data, while Python employs libraries like Sklearn and XGBoost to identify volatility patterns, thanks to the property of stationarity. The Data Pipeline processes data for noise removal and metric calculation, ensuring optimized performance. The Analytics Core leverages machine learning for accurate volatility forecasts, outperforming complex models with simplicity. The Risk Advisor uses these forecasts for dynamic risk management adjustments. This system offers robust, adaptable trading strategy enhancements, bridging traditional indicators and modern analytics.

πŸ‘‰ Read | CodeBase | @mql5dev

#MQL5 #MT5 #AlgoTrading
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A comprehensive approach to technical analysis often requires the integration of multiple well-established indicators. By combining different tools such as moving averages, RSI, MACD, and Bollinger Bands, one can enhance decision-making processes. Each indicator provides unique insights, offering confirmation and reducing the risk of reliance on a single source of information.

Moving averages help in identifying trend directions. RSI provides signals on overbought and oversold conditions. MACD can offer insights into trend changes and momentum shifts. Bollinger Bands are effective for volatility assessment and trend strength.

Utilizing a blended strategy with these indicators may increase the accuracy of analysis, offering stronger, data-driven insights. Proper integration requires careful analysis and understanding of how these tools interact in ...

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#MQL5 #MT5 #Indicator
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A new tool provides a visual representation of trading sessions by aligning them with the 24-hour clock. It synchronizes session names with specific hours based on your broker's server time, while also displaying your computer's local time. The active session or any overlaps are highlighted in yellow, helping to clarify which sessions are live at any given moment. This can reduce uncertainty regarding session timings and potential overlaps with server times, streamlining the trading process and enhancing situational awareness for traders managing multiple time zones.

πŸ‘‰ Read | Forum | @mql5dev

#MQL5 #MT5 #Trading
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Statistical validation in trading is key to uncovering patterns that might not be immediately apparent from visual analysis alone. The Price Level Testing EA addresses the need for empirical evidence by allowing traders to test specific price levels for their historical significance. Traders can identify whether these levels typically act as support or resistance over time, providing objective data to inform decisions.

The EA tackles two major problems: the uncertainty in estimating a level’s strength and the reliability of breakouts. By converting subjective visual impressions into measurable data, it offers insights into how prices behave around key levels. This data-driven approach helps eliminate biases such as recency and confirmation bias.

The tool uses explicit rules to classify events like touches and breakouts, improving consistency and reliabil...

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#MQL5 #MT5 #PriceAction
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MetaTrader 4/5 has consistently been a preferred platform due to its flexibility, supporting both manual and automated trading. There are specialized toolkits for different trading methods, such as an events-news-calendar for manual traders and a strategy-tester-console for those who favor automation. A standout feature in automated trading is the MQL5 Wizard, which allows users to prototype multi-signal systems integrating customizable trailing stops and money management functionalities.

The recent focus on a custom Signal Class combines the Stochastic Oscillator with the Fractal Adaptive Moving Average (FrAMA) to enhance trade decision systems. This approach seeks to create a hybrid system, acting as a digital noise filter for market patterns. With ten market catering indicator patterns, real-time testing across different market regimes like ...

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#MQL5 #MT5 #ExpertAdvisor
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In the latest installment of our MQL5 series, we delve into automating the Opening Range Breakout (ORB) technique, using MetaTrader 5's programming capabilities. The ORB strategy involves identifying high and low price levels immediately after market opening and trading based on price breakouts from this range. This tutorial guides on how to set up your Expert Advisor (EA) to detect and trade these breakouts using 5-minute charts while implementing robust risk management through adjustable parameters. The EA ensures precise entries by relying on candle closure logic, preventing overtrading by executing a single trade per breakout session. This project equips traders with practical skills for developing automated trading systems.


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#MQL5 #MT5 #ORB
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Risk management is foundational in automated trading. It regulates open positions by controlling losses according to predefined limits such as daily or weekly constraints. The system also calculates appropriate lot sizes for each trade, optimizing strategy performance and safeguarding capital.

Automated trading demands rigorous risk management to prevent costly mistakes such as overtrading. It establishes strict boundaries, maintaining strategic operation and protecting funds, particularly vital during funding challenges. With precise lot calculations and loss limits, risk management provides structured operation for consistent trading.

Core concepts include maximum loss constraints on different timescales and acceptable loss per trade. These metrics inform decisions for trade execution, ensuring risks are controlled and profitability is optimized....

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#MQL5 #MT5 #RiskMgmt
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A new tool is available that focuses on risk management, specifically stop loss and take profit settings. Users must set a negative value for the stop loss, as it does not function with zero input. The tool allows a take profit multiplier based on the stop loss value, aiding in strategic profit-taking. A notable limitation is its inability to recognize pending orders. However, it efficiently sets a stop loss to default on orders, beneficial for those managing long and short-term positions. Two stop loss strategies are offered: a direct order-based stop loss and a position closure through input multiples. It aims to enforce disciplined stop loss practices, suitable for frequent traders seeking systematic risk control.

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#MQL5 #MT5 #TradingTool
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The inherent complexity of trading systems challenges even experienced developers, as these applications operate in dynamic and chaotic environments. Successfully adapting to market uncertainty remains a core issue, given the infinite nature of market outcomes. While simple strategies might perform during stable markets, stress tests under volatile conditions often reveal weaknesses in both simple and complex systems. Control theory, typically underused in this niche, focuses on maintaining stability, offering a structured way to address these challenges. By integrating control theory with machine learning, it’s feasible to approximate relationships from raw data, enhancing system adaptability, performance, and efficiency in algorithmic trading.

πŸ‘‰ Read | NeuroBook | @mql5dev

#MQL5 #MT5 #Algorithm
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Explore a pioneering approach in algorithmic trading through biologically-inspired neural models, leveraging the Nobel Prize-winning Hodgkin-Huxley model. Unlike conventional algorithms, this system mimics the brain's ability to process market data, using dynamic, plasma-like environments for deeper, more nuanced insights into financial movements. The architecture integrates advanced learning mechanisms, capturing intricate patterns and fostering a holistic understanding, akin to how neurons assimilate sensory input. Tested on EURUSD data, it demonstrates potential for identifying stable price levels amidst noise, opening new avenues for traders seeking a predictive edge. Ideal for MetaTrader 5 developers aiming to harness biology for market analysis.

πŸ‘‰ Read | AlgoBook | @mql5dev

#MQL5 #MT5 #NeuralNet
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The last analysis touched upon the first five signal patterns between the Stochastic-Oscillator and Fractal Adapting Moving Average (FrAMA). These patterns showed profitable forward trends in specific market conditions. A focus remained on pairing correct asset types with market archetypes: trending/mean-reverting, auto-correlated/decoupled, and volatility levels. Now, consider the next set of signal patterns.

Pattern-5: Designed for low volatility, Pattern-5 identifies scenarios where both FrAMA and price demonstrate flattening before breaking out. Tested primarily with USD JPY to capture periods of volatility shifts, it struggled in dynamic volatility environments, indicating the need for more adaptive windowing.

Pattern-6: This pattern attempts trend resumption using β€˜W’ and β€˜M’ formations within the stochastic oscillator. Combining FrAMA for dire...

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#MQL5 #MT5 #Indicator
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MetaTrader 5 build 5370 delivers enhancements to the web version of the platform:

β€’ Added display of contract start and end dates in instrument specifications.
β€’ Correct price delay indication in the "Quotes" section in mobile view.
β€’ Fixed timeframe selection menu display in mobile view.
β€’ Proper display of available account types in the demo account creation window.
β€’ Fixed localization issues in the account connection window.

Discuss the update...
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