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Senior Software Engineer
在
Tecgraf/Ondeb
Most retail trading algorithms fail not because of a bad strategy, but due to poor memory management, execution lag, and sloppy matrix calculations.
As a senior C++ software engineer, I bridge the gap between institutional-grade software architecture and retail quantitative trading. My expertise lies in stripping away the subjectivity of retail trading and translating pure mathematics, low-latency execution engines.
What I guarantee in every architecture I build:
- Execution Stability: Deeply optimized C++ logic to prevent terminal crashes and memory leaks.
- Strict Quant Math: Converting visual/subjective strategies into objective, array-based Boolean logic.
- No Black Boxes: 100% transparent Object-Oriented Programming (OOP) with clean, maintainable code.
- Capital Protection: Failsafe routing modules (handling Broker Error 130, requotes, and slippage organically).
If you need a robust algorithmic foundation that executes exactly as designed, let's analyze your logic.
As a senior C++ software engineer, I bridge the gap between institutional-grade software architecture and retail quantitative trading. My expertise lies in stripping away the subjectivity of retail trading and translating pure mathematics, low-latency execution engines.
What I guarantee in every architecture I build:
- Execution Stability: Deeply optimized C++ logic to prevent terminal crashes and memory leaks.
- Strict Quant Math: Converting visual/subjective strategies into objective, array-based Boolean logic.
- No Black Boxes: 100% transparent Object-Oriented Programming (OOP) with clean, maintainable code.
- Capital Protection: Failsafe routing modules (handling Broker Error 130, requotes, and slippage organically).
If you need a robust algorithmic foundation that executes exactly as designed, let's analyze your logic.
Alex David Hernandez Maturrano
已发布产品
KINETIC BARYCENTER MT5 First-Principles quantitative mechanics: Center of mass, Multi-Horizon price gravity and Elastic exhaustion bands By ONDEB Labs THE PARADIGM SHIFT: MEASURING MARKET MASS INSTEAD OF CHRONOLOGICAL TIME Major technical indicators were conceived decades ago under the assumption that chronological time is uniform. Simple and Exponential Moving Averages (SMA, EMA) treat quiet, low-volume consolidation bars with the exact same mathematical weight as massive institutional
Alex David Hernandez Maturrano
已发布代码Reverse RSI Bands
“反向RSI区间”是一种领先指标，它通过数学方法对RSI公式进行了反向推导。该指标会直接在主图表上绘制精确的目标价格区间，实时显示RSI将在何处触及您设定的超买或超卖水平。
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488
Alex David Hernandez Maturrano
Studying SMC logic in C++/MQL5 today.
Automating market structure isn't about subjective patterns; it's about quantifying the imbalance of buying and selling pressure. Drawing directly from the foundational concepts of Richard Wyckoff, here is how to engineer robust trading logic for your algorithms:
- The Theory: Price action is the result of a motive force attempting to move price and a resistive force opposing it. Instead of trading random chart rectangles, algorithms should look for classic Wyckoff "springs" (failure tests at the bottom of a range) and "upthrusts". These false breakouts represent critical zones where bulls or bears are so exhausted that a small amount of pressure can reverse a trend.
- Volume Confirmation: A structural pattern is meaningless without volume analysis. You must gauge whether a trend is advancing steadily or if it is facing "absorption" (where heavy volume yields no price progress near support or resistance). This behavior validates the true defense of a price zone by large operators.
- The Architecture: To implement this complex logic in MQL5, leverage Object-Oriented Programming (OOP). By creating robust, reusable classes for your trade placement and order management, you can hide unnecessary implementation details, reduce code duplication, and keep your algorithmic execution lightning-fast. How are you coding your structural and volume confirmations?
Automating market structure isn't about subjective patterns; it's about quantifying the imbalance of buying and selling pressure. Drawing directly from the foundational concepts of Richard Wyckoff, here is how to engineer robust trading logic for your algorithms:
- The Theory: Price action is the result of a motive force attempting to move price and a resistive force opposing it. Instead of trading random chart rectangles, algorithms should look for classic Wyckoff "springs" (failure tests at the bottom of a range) and "upthrusts". These false breakouts represent critical zones where bulls or bears are so exhausted that a small amount of pressure can reverse a trend.
- Volume Confirmation: A structural pattern is meaningless without volume analysis. You must gauge whether a trend is advancing steadily or if it is facing "absorption" (where heavy volume yields no price progress near support or resistance). This behavior validates the true defense of a price zone by large operators.
- The Architecture: To implement this complex logic in MQL5, leverage Object-Oriented Programming (OOP). By creating robust, reusable classes for your trade placement and order management, you can hide unnecessary implementation details, reduce code duplication, and keep your algorithmic execution lightning-fast. How are you coding your structural and volume confirmations?