Market Data
Candles, ticks & market context
AEGIS®
Systems for market decisions.
Engineered to be tested.
A personal trading and backtesting framework built to translate market analysis into structured, testable decisions.
FIG. 001 / SYSTEM MAPDATA IN. DECISIONS OUT. RESULTS TO BE VERIFIED.
01↗
Market Data
Candles, ticks & market context
02↗
Analysis & Strategy
Market structure and trade decisions
03↗
Execution & Portfolio
Orders, positions, balances and fees
04↙
Backtest & Analytics
Simulation, metrics and evaluation
01 / OVERVIEWTHE REASON BEHIND THE SYSTEM
From market
signals to
structured decisions.
AEGIS is a personal engineering project focused on building a structured environment for trading decisions, execution management, and strategy evaluation.
Rather than treating a trading signal as the whole system, AEGIS separates analysis, decision-making, execution, position state, and performance measurement into distinct parts of a larger workflow.
The goal is to make system behavior easier to inspect, test, and improve over time.
02 / ARCHITECTUREHOW THE PIECES CONNECT
Analysis & Strategy
Market structure and trade decisions
Execution & Portfolio
Orders, positions, balances and fees
Backtest & Analytics
Simulation, metrics and evaluation
A conceptual view of the system's responsibilities, not a complete runtime or deployment diagram.
03 / ENGINEERINGPRINCIPLES OVER SHORTCUTS
Separation of concerns
Keep market analysis, strategy decisions, execution, portfolio state, and analytics as distinct responsibilities.
Testable decisions
Make strategy behavior observable and evaluate decisions against historical data rather than relying on assumptions.
Execution consistency
Account for position state, balances, fees, and execution behavior when evaluating the system.
04 / VALIDATIONMEASURE. DON'T ASSUME.
Performance
must be
proven.
A working trading system and a profitable strategy are two different things. AEGIS treats strategy evaluation as a separate engineering problem.
Historical simulation, execution costs, out-of-sample testing, and drawdown analysis are important when assessing whether a strategy has a repeatable edge.
↗Net profit after costs
↗Expectancy & profit factor
↗Maximum drawdown
↗Out-of-sample performance
These are evaluation criteria, not claims of achieved results or guaranteed profitability.