Explore a new approach to market data analysis that goes beyond traditional timeframes by integrating Volume, Range, Renko, and Kagi bars using a Python library. This innovative method captures intricate trading dynamics by adapting to market conditions, optimizing real-time data interpretation for strategic trades. The library seamlessly integrates with MetaTrader 5, offering real-time updates and performance optimization. It highlights how different bar types enhance trading strategies, offering insights for both novice and seasoned traders. Developers benefit from detailed implementations, including handling streaming updates. Tests reveal unique statistical insights, showcasing each bar type's efficiency and market signal clarity.

👉 Read | CodeBase | @mql5dev

#MQL5 #MT5 #Algorithm

In MetaTrader 5 build 5326, we have introduced several improvements to the desktop platform:

• Resolved an issue with the generation of implicit constructors and copy operators for structures and classes. In some cases, this could lead to critical failures in MQL programs.
• Added password length check during first-time account connection after migration from MetaTrader 4. The system now correctly checks the complexity of the new password.
• Fixed the display of the 'ID' column (external system identifier) in the list of open positions. The column will now only appear if at least one of the operations in the list has an associated identifier.

Discuss the update...

Stochastic Eclipse EA is a robust MT4 Expert Advisor utilizing the Stochastic Oscillator for trading. It targets overbought and oversold conditions to capitalize on early market reversals and major momentum changes while filtering out false signals.

Key components include Stochastic Oscillator integration with default overbought/oversold levels set at 80/20, which are customizable. Traders can modify %K, %D, and Slowing values according to specific strategies. The system adopts dual thresholds, executing trades exclusively at boundary crossings, and offers signal confirmation options for immediate or delayed entries.

In terms of trade management, lot size is set at 0.10 by default, modifiable based on individual risk levels. Stop loss and take profit parameters are established at 100 pips each, offering a balanced approach to safety and reward.

A backtest c...

👉 Read | Forum | @mql5dev

#MQL4 #MT4 #EA

In the latest iteration, our MetaTrader 5 program offers a sophisticated ChatGPT dashboard with enhanced interactivity for algorithmic traders and developers seeking AI-driven insights. Key elements include a scrollable, chat-style UI capable of handling multi-turn interactions with timestamps and dynamic message handling. Implemented in MQL5, the program optimizes conversation flow, retains context across sessions, and enhances usability by refining text display for better readability. With configurable scrollbar settings and extended token limits, it empowers developers to customize and extend the tool for richer trading strategies. By modularizing API communication and message handling, the system ensures efficient, adaptive engagement with AI.

👉 Read | Freelance | @mql5dev

#MQL5 #MT5 #AI

Discover the power of candlestick pattern analysis with the Candlestick Probability EA for MetaTrader 5. This tool analyzes key patterns like Pinbar, Engulfing, and Doji across different instruments and timeframes, providing empirical data on their effectiveness in signaling trend reversals or continuations. By quantifying success rates based on historical data, traders can make informed decisions, reducing premature entries often associated with these patterns. Designed for both manual and algorithmic traders, this EA offers a robust framework for turning visual patterns into actionable statistics, helping you refine trading strategies with confidence and precision. Perfect for enhancing your trading research and system development.

👉 Read | Signals | @mql5dev

#MQL5 #MT5 #EA

Market depth is crucial for order block detection. Initiation involves creating dynamic arrays for buy and sell volumes. During OnInit, arrays resize to start storing market order volumes. Depth availability is key, determined by broker support, checked via the chart corner for volume indication.

Initial set-up involves global variables marking market depth availability. Successful initialization uses Depth of Market functions checking OnInit. OnBookEvent tracks volume changes in dynamic arrays. Verification ensures updates with new candlesticks, controlling array size to 30 elements maintaining recent data integrity.

Structured logic for order blocks involves set conditions without loop iterations. Arrays hold critical price points to maintain real-time trading strategy integrity. Buffers are visualized using dynamic arrays, with OnInit processing...

👉 Read | Forum | @mql5dev

#MQL5 #MT5 #OrderBlock

In the continuation of our trading strategy development in MQL5, we have built a Supply and Demand Trading System leveraging a retest and impulse model. This system identifies supply and demand zones through periods of consolidation, confirms their validity with impulsive price moves, and facilitates trading on retests.

Key components of this strategy include defining risk parameters, implementing trend confirmation, and enhancing chart visualization with dynamic labels and colors. We covered the framework, implementation in MQL5, key enumerations, zone detection and validation, trading logic, and the integration of trailing stops. This comprehensive approach provides a functional trading strategy in MQL5 to efficiently manage supply and demand zones for potential reentry trades.

👉 Read | AppStore | @mql5dev

#MQL5 #MT5 #Trading

This script outlines three methodologies for calculating the current Aroon Up and Aroon Down values. The first method involves utilizing the CopyHigh and CopyLow functions. The second method uses iHighest and iLowest functions to determine these values. The final method employs the Aroon indicator directly for the calculation. The indicator, authored by Nikolay Kositsin, is available for download from the MQL5 library. Access to this resource enables integration and comparison of these approaches, allowing for enhanced decision-making in technical analysis and algorithmic trading strategies.

👉 Read | Docs | @mql5dev

#MQL5 #MT5 #Indicator

A custom optimization function crafted for the MetaTrader 5 Strategy Tester, this script assists in analyzing test results beyond the typical use of Expert Advisors, indicators, or scripts. The code begins by collecting trade history from the tester, ensuring a minimum of 50 trades, and recognizing the initial deposit and testing periods. Trades are divided into In-Sample (IS) and Out-of-Sample (OOS) periods, facilitating a more robust analysis.

Thereafter, it calculates a series of metrics, covering factors like profitability, drawdown, Sharpe and Sortino ratios, and profit factor. Statistical analysis is conducted using Kolmogorov-Smirnov and Jarque-Bera tests. Strategy evaluation incorporates multiple dimensions: profitability, consistency, risk-adjusted performance, and statistical quality.

This code is applicable in various scenarios: strategy...

👉 Read | Calendar | @mql5dev

#MQL5 #MT5 #AlgoTrading

The Balance of Power (BOP) indicator, devised by Igor Livshin in 2001, assists in determining the dominance dynamics between buyers and sellers per candle session. This variant integrates a Simple Moving Average (SMA) to effectively reduce market noise, enhancing clarity in reading the indicator. The visual representation delineates buyer dominance (bulls) when the closing price approximates the high and seller dominance (bears) when it nears the low. The formula driving BOP is: (Close - Open) / (High - Low). A BOP above zero indicates buyer control, below zero suggests seller control, and values around zero reflect market balance or indecision. Extreme values, such as ±0.2, often signal potential corrections due to excessive strength.

👉 Read | Freelance | @mql5dev

#MQL5 #MT5 #Indicator

The article delves into enhancing MetaTrader 5's library classes to manage the complete history of graphical object changes on trading charts. This innovative approach enables recording every property change within a graphical object, providing a comprehensive snapshot of its historical data. Developers can effectively restore any object to a previous state, facilitating nuanced technical analysis by recognizing past object configurations. By introducing new properties and updating existing ones like Group and Species, the framework is optimized for sorting and accessing change history effectively. This is particularly beneficial for developers aiming to create sophisticated tools for analyzing market trends with precision and efficiency.

👉 Read | Signals | @mql5dev

#MQL5 #MT5 #EA

PriceVar% is a technical indicator that calculates the percentage difference between market price and a moving average. It measures market movement strength against a reference value. When the closing price is above the moving average, use this formula: Var = (High - MA) / MA * 100. If it's below, the formula is: Var = (Low - MA) / MA * 100. Results are shown as a percentage histogram: green signals price above average, indicating buying force; red signals price below average, indicating selling force.

For interpretation, positive values represent the high's distance from the average, while negative values represent the low's distance. Larger absolute values mean a greater percentage distance. This indicator helps detect overbought or oversold conditions, quantify volatility, and support breakout or reversal strategies. It's also useful for setting th...

👉 Read | Quotes | @mql5dev

#MQL5 #MT5 #Indicator

The article explores the integration of the AutoCorrelation Function (ACF) as a filter in enhancing the Moving Average Crossover strategy for algorithmic trading. It utilizes sixteen years of M15 currency data to assess the effectiveness of the ACF, which identifies time series patterns by measuring correlations within price data. Unlike conventional indicators like ATR and Bollinger Bands, the ACF is not influenced by volatility, showing potential to differentiate profitable from non-profitable trades. When applied to the SMA Crossover Strategy, the ACF threshold requirement significantly bolstered profitability for both EURUSD and GBPUSD pairs, highlighting its utility for expert advisors and algorithmic traders.

👉 Read | AppStore | @mql5dev

#MQL5 #MT5 #EA

Dollar Index Tracker offers a tool for traders to gauge the US Dollar's standing against a basket of major currencies directly alongside their trading charts. It displays USDX composed of six major pairs with EUR/USD having the most influence. Established in 1973 at a value of 100, it remains crucial for measuring dollar strength. The tracker executes the USDX formula in real time, enabling customization with moving averages to identify trends. Input settings allow adjustment of currency pairs and coefficients, offering strategic advantages such as detecting divergence and confirming trends. Multi-timeframe analysis can enhance alignment with dollar trends across various trading frames. It serves as a critical correlation filter, providing clarity on dollar momentum and guarding against false trading signals. Ensure all key currency pairs are listed in Mar...

👉 Read | Freelance | @mql5dev

#MQL4 #MT4 #USDX

Introducing a technical solution for traders seeking to leverage retail sentiment: the Ziwox Retail Sentiment EA. This Expert Advisor employs data from the Ziwox API to implement a contrarian strategy by analyzing retail trader sentiment. Overextended market conditions often occur when most retail traders take one side. By understanding these positions, traders can apply contrarian moves, potentially in synergy with broader market trends and institutional flows.

The advisor retrieves sentiment data via an API call, interpreting the Retail Long and Short Ratios. The contrarian logic triggers sell trades if the long sentiment exceeds a certain threshold with a confirmed technical trend and triggers buys in the opposite scenario. A technical filter with moving averages ensures trades align with established trends, preventing this from crowding.

Automated trad...

👉 Read | Calendar | @mql5dev

#MQL4 #MT4 #Sentiment

The StockFormer hybrid trading system leverages cutting-edge methods like predictive coding and reinforcement learning to forecast market dynamics. Its innovative structure features three specialized Transformer branches for extracting asset interdependencies, and short and long-term predictions. The integration through advanced attention mechanisms enhances pattern detection and adaptability in volatile markets. Practical implementation emphasizes the use of the Diversified Multi-Head Attention module for efficient pattern recognition in noisy data. The training of predictive models focuses on constructing expert systems for time series analysis, optimizing for profitability through focused trajectory selection in neural network training. This robust framework positions StockFormer as a powerful tool for algorithmic trading development.

👉 Read | Quotes | @mql5dev

#MQL5 #MT5 #AI

Markets often operate in cycles of optimism and pessimism, and traditional mechanical strategies can fall short in volatile conditions. To address this issue, advanced machine learning methods such as Variational Autoencoders (VAEs) are introduced for trading strategies. These models compress noisy data into core features, crucial for discerning valid signals amidst market noise.

A significant advance involves the integration of VAEs with binary event encoding, contrasting previous continuous-value pipelines which diluted key signals. This approach enhances signal clarity, stability, and live performance. The MQL5 Wizard facilitates the assembly of trading strategies by combining custom signal classes with machine learning models. This allows for adaptive strategies that are aligned with market dynamics.

The process involves training models in Python, expo...

👉 Read | VPS | @mql5dev

#MQL5 #MT5 #ML

The latest article in our MetaTrader 5 Machine Learning series delves into the implementation of the adaptive trend-scanning labeling method. This method refines trade prediction by dynamically determining the most statistically significant time horizon, rather than relying on a fixed duration. The trend-scanning technique utilizes t-statistics to find genuine trends, enhancing adaptability to volatile or calm market periods. Key innovations include the use of Numba for speed optimization and dynamic volatility filtering to prevent noise. Tested with a moving average crossover strategy, trend-scanning significantly outperformed fixed horizon labeling, improving risk-adjusted returns and offering robust insights for adaptive algorithmic trading.

👉 Read | Calendar | @mql5dev

#MQL5 #MT5 #ML

The article delves into an intricate challenge faced by MetaTrader 5 developers: effective communication between the Chart Trade indicator and the Expert Advisor to manage futures contracts. The proposed solution involves using message exchanges between these components, carefully addressing sequence and synchronization issues when MetaTrader 5 changes the chart timeframe. A notable approach is implementing custom events to smoothly adjust contract types and maintain user interface consistency without convoluting systems. This innovative strategy enhances flexibility in contract management while keeping interface components separate, emphasizing the importance of structured message passing for improved algorithmic trading applications.

👉 Read | Forum | @mql5dev

#MQL5 #MT5 #Trading

Testing trading strategies in a controlled environment enables precise calibration of variables like StopLoss and TakeProfit levels. A recent assessment demonstrated unexpected profitability by adjusting these elements. The experiment also examined integrating various trailing stop methods, including Parabolic SAR and moving averages. By utilizing trailing stops, specifically those based on double exponential moving averages, a notable increase in profitability was observed compared to original trading settings. However, not all indicators provided positive outcomes. Customization of trailing parameters per symbol is advisable for optimal results, as individual symbol characteristics influence trading performance significantly.

👉 Read | CodeBase | @mql5dev

#MQL5 #MT5 #Strategy