PyPortfolioOpt
github.comExplore portfolio weights with explicit return, risk and constraint choices
Explore portfolio weights with explicit return, risk and constraint choices
Read options positioning beside price levels and live hedging estimates
Build event-driven market simulations with a shared strategy engine
Configure active-trading layouts, routing and order limits
Calculate returns, portfolio statistics and allocation weights in Python
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
Find economic time series by release, source or category
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