Syarief Azman bin Rosli
Laboratory Precision: The Scientific Foundation
How chemical quality control protocols and Good Laboratory Practice (GLP) translate directly into financial algorithm design.
High-Sensitivity Analytical Instrumentation
Backed by a professional background in high-precision analytical chemistry and quality assurance, his technical workflow has mandated the calibration and operation of cutting-edge analytical instruments:
- ICP-MS: Inductively Coupled Plasma Mass Spectrometry (Agilent 8900 Triple Quad)
- HPLC & LC-MS: High-Performance Liquid Chromatography & Mass Spectrometry
- GC-MS: Gas Chromatography-Mass Spectrometry for organic compound separation
ISO Calibration & GLP Protocols
Analytical laboratory testing operates under a zero-tolerance policy for methodological deviations. Routine compliance includes executing rigid Standard Operating Procedures:
- ISO 8655-2: Gravimetric verification of micropipette volume precision
- ISO 4787: Volumetric verification of laboratory glassware
- GLP (Good Laboratory Practice): Uncompromising traceability, chain-of-custody, and audit trails
This exact mindset is carried into software development: code is treated like a chemical assay, where assumptions must be proved through empirical data rather than wishful thinking.
Translating Chemistry to Quantitative Trading
Why does this matter to forex traders? Traditional retail traders fail because they react with emotion, chase losses, and rely on static indicators that fail when market regimes shift.
In laboratory science, if a baseline expands, you re-calibrate. In EA Budak Ubat, if market volatility expands from a quiet Asian session into a volatile New York session, the AutoConfig AI engine automatically recalibrates pip steps and take profits every single minute.
The Autodidact Engineer: 2.87M Lines of Code
A relentless builder mentality balancing demanding professional engineering discipline with institutional-grade algorithmic software architecture.
🎓 Formal Computer Science Foundations
To formalize his self-taught quantitative skills, Syarief completed Harvard University’s rigorous onlineCS50x (Introduction to Computer Science) and CS50 Cybersecurity programs. His technical stack spans C/C++ (MetaQuotes MQL4 & MQL5), Python, JavaScript/TypeScript, Next.js, FastAPI, and Supabase.
📊 24-Hour Disciplined Commit Schedule
Maintaining 68+ public repositories on GitHub (@syarief02), code analytics showcase a meticulously balanced work ethic: 26.8% commits early morning, 24.1% daytime,25.6% evening, and 23.5% late night. His most productive coding day is Sunday, reflecting weekend dedication to refining algorithmic logic.
🏢 Real-World Lab Automation Systems
His coding isn’t confined to forex. He has built automated analytical calculation tools that slashed hours of manual laboratory data processing down to seconds: including the Uniformity of Weight Guide (USP 43)and laboratory data automation workflows.
Technical Architecture: The AutoConfig AI Volatility Engine
Why traditional static grid bots blow accounts, and how mathematically derived dynamic volatility adaptation solves it.
The Flaw of Static Grids
Traditional retail grid bots use fixed pip intervals (e.g. open a trade every 20 pips). In a quiet consolidation market, 20 pips is meaningful; but during high-impact news releases or London/NY opens, 20 pips is absorbed in seconds. Static bots stack dangerous lot sizes too quickly, leading to immediate margin calls.
ADR Mathematical Anchoring
EA Budak Ubat’s AutoConfig AI module measures both macro volatility (rolling 365-day baseline) and micro volatility (20-day Average Daily Range). Take-Profit is dynamically derived as ADR ÷ 25, and the minimum pip distance step is computed as ADR ÷ 4.
1-Minute Dynamic Recalculation
This is not a one-time setup. The algorithm recalculates market volatility every 60 seconds. When an asset experiences surging volatility, the grid step expands automatically, spacing out subsequent layers to preserve free equity. When volatility contracts, the grid tightens to capture quick micro-profits.
Intra-Candle Tick Break-Even
In v1.67, the EA calculates the volume-weighted average cost of all open layers on every tick. As soon as floating equity surpasses the safety threshold, the system moves stop-losses into profit, closing entire heavy baskets on minor retracements.
Risk Mathematics: Bounding Martingale & Cent Cushioning
Uncompromising honesty about probability theory, the “fat-tail” problem, and the mandatory capital architecture required to trade safely.
The Fat-Tail Problem in Retail Trading
In theoretical probability, an unconstrained Martingale sequence has a 100% win rate—assuming infinite capital and zero broker leverage limits. In real-world retail forex, both constraints are finite. While grid bots achieve high win rates (often exceeding 80%) in ranging markets, unidirectional macro trends (central bank rate shocks, geopolitical crises) cause geometric drawdown accumulation if left unbounded.
How EA Budak Ubat Mathematically Bounds Risk:
Historical Milestones: 12+ Years of Continuous Iteration
From its 2014 initial publicization (v1.27) and open-source community forum testing to official MQL5 Market commercial verification and generative AI integration.
The Algorithmic Product Ecosystem
A diversified suite of automated trading tools designed for different market conditions, asset classes, and risk appetites.
EA Budak Ubat (Flagship)
Flagship multi-method grid system featuring 4 analysis methods, dynamic ADR AutoConfig AI, and intra-candle tick basket break-even.
GoldMind AI
Automated trading system utilizing Python FastAPI to capture MT5 chart screenshots, querying OpenAI vision models for trend confirmation.
BracketBlitz EA
Rapid-fire One-Cancels-the-Other (OCO) bracket orders deployed every 30 seconds to capture violent news breakouts without directional bias.
MathEdge Pro
Quantitative sequencing algorithm that computes daily mathematical levels and executes a strict 3-trade sequence during NY open.
Encik Moku & Aligator Gozaimasu
Zero-martingale trend-following systems confirming momentum across 4 simultaneous timeframes using Ichimoku Kumo and Alligator lines.
Aegis Risk Sentinel
On-chart Head-Up Display (HUD) monitoring floating drawdown in real-time, enforcing hard daily percentage cutoffs for prop-firm compliance.
Tested in MetaQuotes Strategy Tester against rigorous tick simulations
Compatible with all MT5 broker margin accounting systems worldwide
Highest security standard — zero external binaries or security risks
Automatic download and 20 terminal activations right in MetaTrader 5
Connect Directly with the Developer
Have questions about bot parameters, set files, broker authorization, or custom quantitative development? Syarief Azman provides direct technical support on Telegram.