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Develop Python strategies with graphical backtesting and market gateways

Backtest portfolio allocations with cash flows, benchmarks and simulations

Compare options history with the risks of current positions

Develop and compare trading strategies in a Windows backtesting workspace

Compare portfolio risks and test allocation changes before making them

Research and backtest quantitative strategies in notebooks and code

Choose Python research and backtesting engines for the task

Study an exploratory Python engine for historical equities tests

Assemble portfolio backtests from reusable Python rules

AI investing tools and managed portfolios

Turn portfolio returns into charts and risk-analysis summaries

Calculate portfolio returns from a complete transaction history

Follow dividend income with projections, alerts and portfolio goals

Test entry and exit rules against historical price bars

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

Maintain event-driven Python backtests with the Zipline research model

Compare historical portfolios and model allocation scenarios

Explore markets and portfolio tools in live or virtual mode

A timeline-led project and portfolio planner with task lists, Kanban, dependencies, and dashboards.

Screen stocks and compare fundamentals beside portfolio exposure

An enterprise portfolio platform for roadmaps, budgets, capacity, Agile delivery, and project collaboration.

Track portfolio performance and expected dividend dates

Turn stock-ranking ideas into screens and portfolio simulations

AI trading copilot for market research, strategy and execution.