The article explores the implementation of a trading strategy using the Momentum indicator within MetaTrader 5. Momentum, an important tool for traders, measures price velocity, aiding in identifying trend strength and direction. The article outlines the calculation methods for Momentum, both by subtraction and division, with emphasis on the latter used in MetaTrader 5. A simple Momentum strategy is proposed, focusing on crossover signals around the 100 level for buying and selling. It includes a detailed blueprint for coding this strategy into a trading system using MQL5, enabling automated signal generation, enhancing trading efficiency and decision-making.
π Read | AlgoBook | @mql5dev
#MQL5 #MT5 #Momentum
π Read | AlgoBook | @mql5dev
#MQL5 #MT5 #Momentum
β€58π13π3π¨βπ»3π€2
MetaTrader 5 build 5260 provides improvements to MQL5 Algo Forge, our Git-based project management platform: faster Git operations, more reliable modification checks, and new comprehensive documentation to help you explore, fork, and collaborate on algorithmic trading projects.
The MQL5 update introduces expanded OpenBLAS support with new matrix balancing methods and stricter inheritance rules, which make code safer and more predictable.
We've also added terminal translation into Irish, making the platform accessible and user-friendly for native speakers.
Read more...
The MQL5 update introduces expanded OpenBLAS support with new matrix balancing methods and stricter inheritance rules, which make code safer and more predictable.
We've also added terminal translation into Irish, making the platform accessible and user-friendly for native speakers.
Read more...
β€56π12π₯10π€£7π6β‘4π2
Implementing code to draw triangles on a chart assists in detecting harmonic patterns and visually plotting them. This technique can be extended to include the plotting of rhombuses and parallelograms, providing additional flexibility in geometric representation. Utilizing these shapes enhances the ability to clearly display detected patterns on charts, aiding in pattern analysis and verification processes. By adapting this approach, developers can accurately reflect complex structures, which can be crucial for detailed analytical frameworks and systems. Efficient code execution ensures reliable visualization of both triangular and quadrilateral figures, supporting advanced pattern detection methodologies in technical analysis.
π Read | NeuroBook | @mql5dev
#MQL4 #MT4 #AlgoTrading
π Read | NeuroBook | @mql5dev
#MQL4 #MT4 #AlgoTrading
β€42π5π¨βπ»2π€―1
Discover the groundbreaking exploration of markets through the lens of 3D bars, transcending traditional analysis by constructing a tensor model that integrates price, volume, and time. This innovative approach reveals powerful predictive patterns heralding trend reversals with remarkable accuracy, transforming market data into a vibrant, dynamic structure. By employing Gann's methodological principles for data normalization, coupled with a unique volumetric profile and the development of a trend strength integral indicator, the article demonstrates how these insights can enhance decision-making. The adaptable application of these findings within MetaTrader 5 underscores a significant leap in algorithmic trading, offering advanced foresight for traders and developers alike.
π Read | AppStore | @mql5dev
#MQL5 #MT5 #Indicator
π Read | AppStore | @mql5dev
#MQL5 #MT5 #Indicator
β€57π5π¨βπ»3π3π2
The Laguerre Filter is a technical analysis tool that employs Laguerre polynomials to provide a smoothing effect on price data. This indicator assists in identifying both short-term and long-term market trends. Traders can interpret signals as follows: a green indicator line suggests a buying opportunity, whereas a red line advises selling actions. The tool focuses on delivering clear and concise trend data, optimizing decision-making processes. Availability for this indicator exists outside this communication, with further resources accessible through designated channels. Subscription details are subject to specific distribution platforms.
π Read | Docs | @mql5dev
#MQL5 #MT5 #Indicator
π Read | Docs | @mql5dev
#MQL5 #MT5 #Indicator
β€39π16π7π¨βπ»1
Explore the advanced development of composite graphical objects in MetaTrader 5. Discover enhanced functionality as the author delves into event handling, focusing on real-time creation of these objects through drag-and-drop mechanics. The introduction of form objects for each anchor point allows precise positioning, facilitating seamless attachment to base objects. Unique methods for handling price and time coordinates ensure accurate tracking and management. The custom toolkit, embedded within base object classes, enables efficient form creation, object manipulation, and event response. This structured approach promises to optimize algorithmic trading strategies by offering practical insights for both traders and developers seeking refined control within the MetaTrader 5 environment.
π Read | Calendar | @mql5dev
#MQL5 #MT5 #GraphObj
π Read | Calendar | @mql5dev
#MQL5 #MT5 #GraphObj
β€53π7π5π2π1π¨βπ»1
The Adaptive CCI indicator offers significant improvements over the traditional Commodity Channel Index by utilizing dynamically adjusting thresholds that respond to market volatility. Unlike fixed limits, these thresholds, calculated through an Exponential Moving Average of detected peaks and troughs, automatically determine optimal overbought and oversold levels. This comprehensive update significantly enhances signal accuracy, particularly by eliminating false signals in sideways markets and ensuring asset-specific calibration.
Key functional aspects include volatility-based smoothing, which fine-tunes responsiveness through the Average True Range, allowing for greater sensitivity in volatile markets and stability during quieter periods. Additionally, the indicator is fully compatible with both real-time trading and historical backtesting, ensur...
π Read | Freelance | @mql5dev
#MQL5 #MT5 #Indicator
Key functional aspects include volatility-based smoothing, which fine-tunes responsiveness through the Average True Range, allowing for greater sensitivity in volatile markets and stability during quieter periods. Additionally, the indicator is fully compatible with both real-time trading and historical backtesting, ensur...
π Read | Freelance | @mql5dev
#MQL5 #MT5 #Indicator
β€51π5π5β3π3π¨βπ»3π±1
The ZigZag WaveSize indicator has undergone significant enhancements. Key improvements include adapting the code for MetaTrader 5 and optimizing interactions with graphical objects. New features have been added, such as horizontal levels on extrema with options for type selectionβhorizon, beams, or sectionsβand a liquid levels filter that remains unaffected by price. The breakout buffer now allows setting sensitivity to false breakouts. Enhanced label customization includes options for number, appearance, and automated deletion of outdated labels. Alerts have been introduced for structure breakdowns and changes in motion patterns. Optimization efforts focus on refining extremum update logic and enabling dynamic updates for new objects, reducing load when new bars surface. A centralized label system is now in place to manage positioning effectively, ...
π Read | VPS | @mql5dev
#MQL5 #MT5 #Indicator
π Read | VPS | @mql5dev
#MQL5 #MT5 #Indicator
β€43π10π¨βπ»4π€¨3π€―1
Explore the comprehensive guide to harnessing linear regression models in MetaTrader 5. The article delves into using statistical methods, such as Pearson's correlation coefficient, to evaluate market data effectively. Learn to implement simple and multiple linear regression models using MQL5 and Python to predict stock price changes based on key indicators. Uncover how to visualize data and measure predictive accuracy with R-squared, ensuring robust algorithmic trading strategies. The piece also highlights the importance of data quality and assumption validations, focusing on enhancing trading outcomes through informed decision-making. A perfect read for traders and developers seeking a deep dive into algorithmic trading solutions.
π Read | AlgoBook | @mql5dev
#MQL5 #MT5 #DataScience
π Read | AlgoBook | @mql5dev
#MQL5 #MT5 #DataScience
β€71π16π5π¨βπ»5
The Fractal with CCI Filter Indicator is designed to improve the performance of the classic fractal indicator using a CCI-based filter. By integrating the Commodity Channel Index, this version aims to reduce false signals, particularly in sideways markets, enhancing signal reliability through confirmation of the movement's strength.
Key features include a CCI Smart Filter, which activates fractal signals when the CCI reaches extreme levels, and timing accuracy by utilizing the CCI value on the signal candle. Additionally, the CCI period and filtering threshold offer full configurability. Visual aids include red arrows for sell signals and green arrows for buy signals, compatible with any timeframe.
To utilize effectively, monitor for sell signals when a red arrow is above a candle and for buy signals with a green arrow below. For increased reliabilit...
π Read | Freelance | @mql5dev
#MQL5 #MT5 #Indicator
Key features include a CCI Smart Filter, which activates fractal signals when the CCI reaches extreme levels, and timing accuracy by utilizing the CCI value on the signal candle. Additionally, the CCI period and filtering threshold offer full configurability. Visual aids include red arrows for sell signals and green arrows for buy signals, compatible with any timeframe.
To utilize effectively, monitor for sell signals when a red arrow is above a candle and for buy signals with a green arrow below. For increased reliabilit...
π Read | Freelance | @mql5dev
#MQL5 #MT5 #Indicator
β€42β6π3π₯2π2π¨βπ»2π2
Simplified CSV file writing using a straightforward class is achievable without extensive preparation or type casting declarations. Consider implementing a minimalistic class where you define a method for writing CSV files efficiently.
```python
import csv
class SimpleCSVWriter:
def __init__(self, filename):
self.filename = filename
def write(self, data):
with open(self.filename, mode='w', newline='') as file:
writer = csv.writer(file)
writer.writerows(data)
csv_writer = SimpleCSVWriter('output.csv')
data = [
['Name', 'Age', 'City'],
['Alice', 30, 'New York'],
['Bob', 25, 'Los Angeles'],
['Charlie', 35, 'Chicago']
]
csv_writer.write(data)
```
Instantiate the `SimpleCSVWriter` with the desired filename, prepare your list of lists containing rows, and utilize the `write` method to generate your...
π Read | CodeBase | @mql5dev
#MQL5 #MT5 #CSV
```python
import csv
class SimpleCSVWriter:
def __init__(self, filename):
self.filename = filename
def write(self, data):
with open(self.filename, mode='w', newline='') as file:
writer = csv.writer(file)
writer.writerows(data)
csv_writer = SimpleCSVWriter('output.csv')
data = [
['Name', 'Age', 'City'],
['Alice', 30, 'New York'],
['Bob', 25, 'Los Angeles'],
['Charlie', 35, 'Chicago']
]
csv_writer.write(data)
```
Instantiate the `SimpleCSVWriter` with the desired filename, prepare your list of lists containing rows, and utilize the `write` method to generate your...
π Read | CodeBase | @mql5dev
#MQL5 #MT5 #CSV
β€34β3π3π¨βπ»3β‘2π2π2
The article delves into the development of a custom Heikin Ashi indicator using MQL5, crucial for traders and developers focused on algorithmic trading. It provides an intricate breakdown of the Heikin Ashi candles, explaining their advantage in smoothing out market trends, enhancing clarity over traditional candlestick charts. The guide details the calculation methods for Heikin Ashi's open, high, low, and close values and the logic behind integrating these calculations into MQL5. The article emphasizes modular programming for maintaining clean, understandable code and explains setting up visual elements, such as color buffers, to improve indicator readability. It equips developers to create more refined trading tools.
π Read | AppStore | @mql5dev
#MQL5 #MT5 #Indicator
π Read | AppStore | @mql5dev
#MQL5 #MT5 #Indicator
β€31π4π₯3π¨βπ»3π€2
In delving into advanced machine learning, this article addresses a critical but often overlooked component: irreducible error. Beyond the inherent variability and model bias commonly acknowledged, it introduces a third source of error, obscured by abstraction. By examining models from a geometric perspective, practitioners can better understand the manifold mismatch, where predictions poorly align with target realities in their own domains. This discussion extends into practical trading applications, demonstrating enhanced profitability and reduced risk using an improved feedback controller approach. Both developers and traders can benefit from these insights, offering a more intelligent application of machine learning in trading strategies.
π Read | Forum | @mql5dev
#MQL5 #MT5 #ML
π Read | Forum | @mql5dev
#MQL5 #MT5 #ML
β€27β8π4π₯2π¨βπ»2πΎ2
Explore the groundbreaking Multi-Agent and Self-Adaptive portfolio optimization framework integrated with Attention mechanisms and Time series (MASAAT) for dynamic trading. This sophisticated framework harnesses attention mechanisms to extract trend features from noisy time series, utilizing Cross-Sectional Attention (CSA) and Temporal Attention (TA) for superior asset and temporal insight. Agents analyze market trends at various granularities, enhancing portfolio adaptability in volatile conditions. An MQL5 implementation showcases its practical application, emphasizing modular object structure for parallel operation. Leveraging OpenCL, multi-agent trend detection is optimized, paving the way for refined portfolio strategies in computational finance. Ideal for developers keen on algorithmic trading innovations.
π Read | Signals | @mql5dev
#MQL5 #MT5 #Portfolio
π Read | Signals | @mql5dev
#MQL5 #MT5 #Portfolio
β€28π9π¨βπ»3π1π1
Explore the cosmic-inspired Big Bang-Big Crunch (BBBC) algorithm, a global optimization method that simplifies complex problem-solving for algorithmic traders and developers. Drawing parallels to cosmic phenomena, this method uses a dynamic population of candidates, adapting through chaotic exploration and focused refinement phases. Innovative implementation balances randomness with precise targeting, ensuring robust solutions. Despite impressive outcomes on standard benchmarks, deeper analysis reveals limitations due to its over-reliance on central optima. By revising the approach, we enhance objectivity, leading to true optimization results. Whether adjusting algorithm parameters or testing new strategies, BBBC offers an intriguing perspective on iterative problem-solving.
π Read | Signals | @mql5dev
#MQL5 #MT5 #Algorithm
π Read | Signals | @mql5dev
#MQL5 #MT5 #Algorithm
β€30π€‘8π6π2π€¨2π¨βπ»2
The development of a replay system requires careful handling of futures contracts, particularly with assets that have both full and mini contract types. When designing an Expert Advisor to interpret Chart Trade instructions, programmers encounter challenges with assets like futures that have expiration dates. Addressing these challenges involves understanding contract types and ensuring historical data is correctly applied, as traders often rely on historical accuracy when strategizing.
While adapting the cross order system for varying contracts, establishing naming conventions is crucial. This involves a systematic method for identifying active contracts and mapping historical data to them, ensuring consistency in the display and execution of trades. The focus here is on extended timeframes and the continuity of data for long-term strategies.
Prog...
π Read | AlgoBook | @mql5dev
#MQL5 #MT5 #Strategy
While adapting the cross order system for varying contracts, establishing naming conventions is crucial. This involves a systematic method for identifying active contracts and mapping historical data to them, ensuring consistency in the display and execution of trades. The focus here is on extended timeframes and the continuity of data for long-term strategies.
Prog...
π Read | AlgoBook | @mql5dev
#MQL5 #MT5 #Strategy
β€48β‘5π¨βπ»4π2πΎ2
HedgeCover EA is engineered for meticulous risk management in trading operations. It stands out from high-risk martingale systems by providing a controlled environment to protect losing positions. Key functionalities include the One-Hedge-Per-Position method, which avoids infinite hedging loops and prevents excessive trades. It distinctly uses Magic Number Separation to differentiate main positions from hedges.
Configurable Loss Threshold allows traders to establish loss levels between 30 and 100 pips before hedge activation. A Cooldown Protection feature mandates a minimum period between hedges, ranging from 5 to 15 minutes, and Max Hedges Limit caps the total hedge count.
To prevent over-leverage, Margin Safety Checks enforce an 80% free margin requirement, and Symbol Filtering confines hedging to the current chart. It incorporates lot size validation and no...
π Read | Quotes | @mql5dev
#MQL5 #MT5 #EA
Configurable Loss Threshold allows traders to establish loss levels between 30 and 100 pips before hedge activation. A Cooldown Protection feature mandates a minimum period between hedges, ranging from 5 to 15 minutes, and Max Hedges Limit caps the total hedge count.
To prevent over-leverage, Margin Safety Checks enforce an 80% free margin requirement, and Symbol Filtering confines hedging to the current chart. It incorporates lot size validation and no...
π Read | Quotes | @mql5dev
#MQL5 #MT5 #EA
β€33π13β‘3π¨βπ»2π1π1
Orthogonal polynomials serve as a robust method for analyzing market data, thanks to their unique mathematical properties. In trading, they can efficiently simulate time series by filtering out noise and highlighting trends. Polynomials such as Legendre and Chebyshev can be applied in technical analysis for smoothing data, trend detection, and constructing complex trading indicators.
Their independence and adaptability enhance model stability and interpretability. Strategies using orthogonal polynomials, like polynomial regression and adjusted technical indicators, can significantly improve prediction accuracy and market adaptability. Moreover, they integrate well with machine learning to capture complex data relationships and reduce overfitting.
π Read | VPS | @mql5dev
#MQL5 #MT5 #Indicator
Their independence and adaptability enhance model stability and interpretability. Strategies using orthogonal polynomials, like polynomial regression and adjusted technical indicators, can significantly improve prediction accuracy and market adaptability. Moreover, they integrate well with machine learning to capture complex data relationships and reduce overfitting.
π Read | VPS | @mql5dev
#MQL5 #MT5 #Indicator
β€39π6π¨βπ»4
Discover how to build a robust MQL5 system that enhances price-action trading by transforming fractal pivots into reliable signals. This technical guide presents a practical approach to using fractal pivots as stable anchors, detecting pivotal market shifts through Changes of Character (ChoCH) and Breaks of Structure (BOS). These signals provide early warnings and confirmations of trend reversals, using closed-bar logic to ensure non-repainting and backtestable accuracy. The article delves into the complete algorithm design and MQL5 implementation, offering features like alerts, logging, and multi-channel notifications. Itβs a powerful tool for traders seeking to streamline their strategy with automated alerts and effective market analysis.
π Read | Quotes | @mql5dev
#MQL5 #MT5 #Trading
π Read | Quotes | @mql5dev
#MQL5 #MT5 #Trading
β€48π7π¨βπ»3
The latest update enhances the News Headline EA by incorporating a multi-chart visualization feature for multiple-symbol management. A new class, CChartMiniTiles, was developed to enable traders to view multiple charts within a single chart space, customizable in size and easily controlled via a toggle button. This feature supports real-time decision-making during volatile market events by allowing easy access and quick toggling of price views for selected trading pairs. The modular and maintainable design focused on separate testing, reducing errors during integration into complex systems.
An example EA, MiniChartsEA, was used to validate this functionality. Initial tests confirmed the seamless toggling of mini-chart views, adjusted to broker-specific symbol formats. This functionality will be integrated into the main EA, enhancing the trading workspace by...
π Read | VPS | @mql5dev
#MQL5 #MT5 #EA
An example EA, MiniChartsEA, was used to validate this functionality. Initial tests confirmed the seamless toggling of mini-chart views, adjusted to broker-specific symbol formats. This functionality will be integrated into the main EA, enhancing the trading workspace by...
π Read | VPS | @mql5dev
#MQL5 #MT5 #EA
β€81β9π8π¨βπ»4π€―3π3β‘2
Risk Calculator is a valuable resource for traders prioritizing swift and precise calculations. It eliminates the need for manual computations of financial values related to Stop Loss and Take Profit. This Expert Advisor provides an intuitive chart panel that allows for quick visualization of trade risk and reward, prior to order placement. With a streamlined and performance-optimized interface, it integrates smoothly into trading setups, offering essential information without chart clutter or system slowdown.
Key features include:
- Instant Calculation: Input lot size and point distances for Take Profit and Stop Loss to immediately view values in your account's currency.
- On-Chart Interface: User-friendly, positioned to not obstruct technical analysis.
- Real-Time Point Value: Displays monetary value per point for the current symbol, clarifying volatil...
π Read | Calendar | @mql5dev
#MQL5 #MT5 #EA
Key features include:
- Instant Calculation: Input lot size and point distances for Take Profit and Stop Loss to immediately view values in your account's currency.
- On-Chart Interface: User-friendly, positioned to not obstruct technical analysis.
- Real-Time Point Value: Displays monetary value per point for the current symbol, clarifying volatil...
π Read | Calendar | @mql5dev
#MQL5 #MT5 #EA
β€44π3π¨βπ»2β1πΎ1