TradeJournal: An Intelligent Web-Based Trading Journal System

In modern financial markets, trading activities are highly dynamic and data-intensive, requiring disciplined
decision-making and continuous performance evaluation. Many traders lack a structured mechanism to
systematically record and analyze their trades, leading to inconsistent results and repeated mistakes.
TradeJournal: Intelligent Trading Journal is designed as a comprehensive digital solution to address this
challenge by providing an organized platform for tracking, analyzing, and improving trading performance.
The application incorporates advanced analytical features that generate key performance indicators such
as win rate, profit factor, drawdown, expectancy, and strategy-wise profitability. Interactive dashboards
and graphical visualizations help users identify patterns, assess strengths and weaknesses, and recognize
recurring errors. The system is implemented using Next.js for the front-end, Python Flask for the back-end,
and SQLite for persistent data storage.