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Configure active-trading layouts, routing and order limits

Calculate returns, portfolio statistics and allocation weights in Python

Filter market headlines alongside live audio and economic calendars

Screen fundamentals, visualize metrics and export financial data

Keep confirmed dividend dates and income forecasts in view

Connect portfolio events with dividend targets and income progress

Build historical market simulations with configurable orders and costs

Generate trading rules and test how their results withstand changes

Study traded volume with footprint charts, profiles and heatmaps

Filter a trading journal by symbols, tags, dates and rule adherence

Fit portfolio models and evaluate them on later market data

Test entry and exit rules against historical price bars

Find economic time series by release, source or category

Follow dividend declarations and plan a portfolio income schedule

Inspect the product, model and market inputs behind a valuation

Research trading decisions with reinforcement-learning experiments

Build custom market scans and test chart-based strategies

Review trading records alongside deposits, dividends and costs

Compare market-structure measurements with their historical outcomes

Keep trade plans, checklists and later review in one journal

Experiment with financial language models, sentiment and forecasts

Screen options, test explicit rules and inspect each simulated trade

Compare stock valuation models and the assumptions inside them

Build technical stock screens from readable filtering rules