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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

Research ETF characteristics and compare fund costs

Build technical stock screens from readable filtering rules

Follow Australian and U.S. investments with watchlists and performance history

Compare disclosed manager holdings and quarterly portfolio changes

Replay historical markets across charts and depth-of-market views

Screen stocks and examine the factors behind company ratings

Research UK investment accounts, funds and retirement choices

Compare portfolio risks and test allocation changes before making them

Research options in a browser or build on licensed historical datasets

Maintain event-driven Python backtests with the Zipline research model

Search financial documents and trace research back to its sources

Find private companies by sector, funding stage and location

Find quantitative trading ideas and examine the research behind them

Turn portfolio return histories into metrics, charts and shareable reports