Example Output
A sample optimization on 10 Nifty 50 stocks using Hierarchical Risk Parity — optimized vs equal-weight allocation.
Expected Return
18.4%
Volatility
12.7%
Sharpe Ratio
1.45
Max Drawdown
-11.2%
Illustrative example using historical data. Past performance does not guarantee future results.
Methods
From classical Markowitz to modern clustering-based approaches — pick the strategy that fits your risk profile.
Features
Everything you need to go from stock selection to optimized allocation.
15+ optimization methods — from classical Mean-Variance to modern Hierarchical Risk Parity — pick the right strategy for your goals.
Sharpe, Sortino, drawdown, VaR, and 50+ metrics with interactive charts so you understand exactly how your portfolio behaves.
Run complex optimizations across hundreds of stocks and get actionable weights in seconds, not hours.
Save templates, compare runs side-by-side, download reports, and maintain a full audit trail of every decision.
Roadmap
New capabilities on the roadmap.
Run thousands of simulated portfolio paths to estimate return distributions, confidence intervals, and tail-risk probabilities.
Ask questions about your portfolio in plain language. An AI agent interprets results, surfaces insights, and guides you through optimization decisions step by step.