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Research investments and discuss your plans with an investment coach

See how an asset allocation behaved across different starting years

Backtest portfolio allocations with cash flows, benchmarks and simulations

Search public trading disclosures and compare the dates behind them

Compare strategy experiments across assets, parameters and historical periods

Query and deliver institutional pricing and reference data

Explore markets and portfolio tools in live or virtual mode

Save chart configurations and organize repeatable market scans

Build stock scans and inspect trading layouts in a paper account

Reconcile dividend expectations with portfolio transactions and payments

Track investments and examine account and portfolio performance

Connect financial data providers to Python and research applications

Examine stock-factor returns, predictive relationships and turnover

Build trading tools and examine cBot behaviour on historical data

Compare company fundamentals visually with historical stock valuations

Host coded or visual strategies through shared broker connections

Turn portfolio returns into charts and risk-analysis summaries

Research international banking, liquidity and financial-market statistics

Research and backtest quantitative strategies in notebooks and code

Create reusable chart conditions and filter stock watchlists

Explore international macroeconomic datasets and projection vintages

Calculate portfolio returns from a complete transaction history

Study an exploratory Python engine for historical equities tests

Build formula screens and examine their historical matches