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ahmedbello82
Joined
Apr 08, 2024
Connections:
1
Experience:
3-5 years
Location:
Nigeria
Profile
Bio
I am a Financial Engineering professional with a strong background in Mathematics, Finance, Economics, Engineering, and ICT. I apply advanced analytical and quantitative techniques to design, develop, and implement innovative financial instruments and trading strategies that optimize returns and minimize risk.
My expertise extends to algorithmic trading, where I specialize in creating, testing, and optimizing custom cBots for cTrader. I leverage quantitative models, data-driven insights, and market dynamics to build intelligent automated trading systems that adapt to various market conditions.
Skilled in financial modeling, risk management, portfolio optimization, and market analysis, I bring both technical precision and strategic foresight to every project. My goal is to deliver robust, efficient, and high-performing trading solutions that help clients and traders achieve consistent, long-term success in financial markets.
My expertise extends to algorithmic trading, where I specialize in creating, testing, and optimizing custom cBots for cTrader. I leverage quantitative models, data-driven insights, and market dynamics to build intelligent automated trading systems that adapt to various market conditions.
Skilled in financial modeling, risk management, portfolio optimization, and market analysis, I bring both technical precision and strategic foresight to every project. My goal is to deliver robust, efficient, and high-performing trading solutions that help clients and traders achieve consistent, long-term success in financial markets.
Trading style
Algo cBot Trader & Strategy Developer
I am a systematic algorithmic trader and cBot developer, specializing in the design, coding, and optimization of fully automated trading strategies using C# (cTrader/cAlgo) and Python. My trading approach is rule-based, data-driven, and risk-controlled, eliminating emotional decision-making and ensuring consistency across market conditions.
Core Trading Philosophy
My trading style is built on three pillars:
Precision Entries
Strict Risk Management
Session-Based Market Behavior
Every strategy I develop is backtested, forward-tested, and optimized to perform reliably under real-market conditions, with a strong emphasis on capital preservation and drawdown control.
Strategy Framework & Methodology
1. Market Structure & Session Trading
Trades are structured around Asian, London, and New York sessions
Identifies high-probability liquidity windows
Uses Opening Range Breakout (ORB) and session highs/lows for directional bias
Optimized especially for XAUUSD (Gold) and major FX pairs
2. Entry Logic & Confirmation
Strategies use multi-layer confirmation, including:
Price action patterns (Engulfing candles, Pin bars)
Break-and-retest logic
Volatility filters (ATR-based conditions)
Time-based confirmation (15M / session open logic)
Optional Fair Value Gap (FVG) and range box validation
This reduces false breakouts and improves trade quality.
3. Risk & Trade Management (Core Strength)
Every algo includes advanced protection mechanisms:
ATR-based Stop Loss & Take Profit
Fixed or dynamic Risk-to-Reward (R:R) ratios
Break-even automation at 1R
Trailing stop (price-based or time-based)
Daily max loss limits (Kill Switch)
Equity & drawdown protection
Multi-entry scaling with controlled exposure
Risk is always predefined before trade execution.
Automation & Development Stack
cTrader / C# (Primary)
Custom cBot development using cAlgo API
Modular, clean, and optimized C# architecture
Supports:
Multi-session filters
Multi-symbol trading
News filters
Parameter optimizers
Backtesting & forward testing
Fully compliant with cTrader Store publishing standards
Python (Research & Advanced Logic)
Strategy research & statistical analysis
Indicator prototyping and signal validation
Backtest result analysis
Risk modeling & performance metrics
Python logic can be translated into C# cBots for live deployment
Trading Style Summary
Style: Algorithmic / Systematic Trading
Execution: Fully automated (no manual intervention)
Markets: Forex & Gold (XAUUSD)
Timeframes: Intraday (M5–M15 core logic)
Edge: Session-based volatility + price action confirmation
Risk Profile: Conservative to moderate, drawdown-controlled
What Sets Me Apart
Strong balance between trading logic and software engineering
Strategies built for real-world broker conditions
Emphasis on robust risk control, not overfitting
Fully customizable bots tailored to client strategies
Deep understanding of both trading psychology and automation discipline
I am a systematic algorithmic trader and cBot developer, specializing in the design, coding, and optimization of fully automated trading strategies using C# (cTrader/cAlgo) and Python. My trading approach is rule-based, data-driven, and risk-controlled, eliminating emotional decision-making and ensuring consistency across market conditions.
Core Trading Philosophy
My trading style is built on three pillars:
Precision Entries
Strict Risk Management
Session-Based Market Behavior
Every strategy I develop is backtested, forward-tested, and optimized to perform reliably under real-market conditions, with a strong emphasis on capital preservation and drawdown control.
Strategy Framework & Methodology
1. Market Structure & Session Trading
Trades are structured around Asian, London, and New York sessions
Identifies high-probability liquidity windows
Uses Opening Range Breakout (ORB) and session highs/lows for directional bias
Optimized especially for XAUUSD (Gold) and major FX pairs
2. Entry Logic & Confirmation
Strategies use multi-layer confirmation, including:
Price action patterns (Engulfing candles, Pin bars)
Break-and-retest logic
Volatility filters (ATR-based conditions)
Time-based confirmation (15M / session open logic)
Optional Fair Value Gap (FVG) and range box validation
This reduces false breakouts and improves trade quality.
3. Risk & Trade Management (Core Strength)
Every algo includes advanced protection mechanisms:
ATR-based Stop Loss & Take Profit
Fixed or dynamic Risk-to-Reward (R:R) ratios
Break-even automation at 1R
Trailing stop (price-based or time-based)
Daily max loss limits (Kill Switch)
Equity & drawdown protection
Multi-entry scaling with controlled exposure
Risk is always predefined before trade execution.
Automation & Development Stack
cTrader / C# (Primary)
Custom cBot development using cAlgo API
Modular, clean, and optimized C# architecture
Supports:
Multi-session filters
Multi-symbol trading
News filters
Parameter optimizers
Backtesting & forward testing
Fully compliant with cTrader Store publishing standards
Python (Research & Advanced Logic)
Strategy research & statistical analysis
Indicator prototyping and signal validation
Backtest result analysis
Risk modeling & performance metrics
Python logic can be translated into C# cBots for live deployment
Trading Style Summary
Style: Algorithmic / Systematic Trading
Execution: Fully automated (no manual intervention)
Markets: Forex & Gold (XAUUSD)
Timeframes: Intraday (M5–M15 core logic)
Edge: Session-based volatility + price action confirmation
Risk Profile: Conservative to moderate, drawdown-controlled
What Sets Me Apart
Strong balance between trading logic and software engineering
Strategies built for real-world broker conditions
Emphasis on robust risk control, not overfitting
Fully customizable bots tailored to client strategies
Deep understanding of both trading psychology and automation discipline
Motto
Engineering discipline into every trade.
Systems by ahmedbello82
Recent Posts
319
Jan 03 at 13:44
