Make smarter allocation decisions for Indian equities. Institutional-grade optimization that turns complex quantitative strategies into clear, actionable portfolio weights.
Sharpe
1.45
Return
18.4%
Volatility
12.7%
Max DD
-11.2%
Optimal Allocation
10 assetsExample 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.
How It Works
Go from stock selection to optimized portfolio weights for Indian equities in minutes.
Choose from hundreds of NSE and BSE equities, or US-listed stocks (NYSE / NASDAQ). Search by ticker or name to build your investment universe.
Pick from 16 optimization methods - Mean-Variance, HRP, Risk Parity, Black-Litterman, and more.
Set your lookback period, risk-free rate, constraints, and benchmark. Fine-tune to match your risk profile.
Receive actionable portfolio weights with full analytics - 50+ risk metrics, performance charts, and downloadable reports.
Who It's For
Optimize your Indian equity portfolio without a quant background. Turn research into data-driven allocation decisions for NSE and BSE stocks.
Run institutional-grade analysis for client portfolios across NSE and BSE. Compare methods, generate reports, and maintain audit trails.
Compare 16 optimization methods with 50+ risk metrics on Indian market data. Full API access for systematic research workflows.
FAQ
Common questions about portfolio optimization for Indian equities.
Portfolio optimization is the process of selecting the best asset weights to maximize returns or minimize risk for a basket of Indian equities. Folio Lab applies quantitative methods like Mean-Variance, Hierarchical Risk Parity, and Black-Litterman to NSE and BSE stocks, computing optimal weights backed by decades of academic research.
There is no single best method - it depends on your goals. Mean-Variance works well with reliable return estimates, Risk Parity is robust when you want balanced risk exposure, and HRP excels when dealing with correlated Indian market sectors. Folio Lab lets you compare all 16 methods side-by-side.
Manual allocation relies on intuition and simple heuristics. Folio Lab uses mathematically optimal algorithms that account for correlations, volatility, and tail risk across your entire portfolio - delivering measurably better risk-adjusted returns as shown by decades of academic research.
Folio Lab is currently in beta and offers a free tier that lets you run optimizations, analyze results, and access the full documentation. Depending on how this beta performs, a full version with retail and enterprise pricing will be released. Create an account to get started in minutes.
Folio Lab calculates 50+ metrics including Sharpe Ratio, Sortino Ratio, Value at Risk (VaR), CVaR, Maximum Drawdown, Jensen's Alpha, Treynor Ratio, Information Ratio, and multiple beta variants - all computed specifically for your optimized Indian equity portfolio.
Yes. You can optimize portfolios on either exchange - choose NSE stocks with Nifty or Bank Nifty as the benchmark, or BSE stocks with Sensex. Each optimization run uses a single exchange for consistent pricing and benchmark comparison.
Yes. Pro and Enterprise plans support US-listed equities (NYSE / NASDAQ), benchmarked against the S&P 500, Nasdaq-100 or Russell 3000, with US Treasury or fed-funds risk-free rates from FRED. US and Indian assets can't be mixed in a single run.
Folio Lab can optimize portfolios with hundreds of Indian stocks simultaneously. The platform handles large covariance matrices efficiently, even for methods like Mean-Variance and Black-Litterman that require matrix inversion.
Folio Lab uses historical price data for NSE and BSE equities, Indian government bond yields for risk-free rates, and Nifty 50 / Sensex as benchmark indices. All data is sourced and processed for accurate covariance estimation and return calculation.
Roadmap
New capabilities on the roadmap.
Optimize US-listed equities (NYSE / NASDAQ) against the S&P 500, Nasdaq-100 or Russell 3000, with US Treasury / fed-funds risk-free rates. Available on Pro and Enterprise.
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.
Optimize across Indian mutual funds alongside equities. Build multi-asset portfolios spanning NAV-based schemes, equity funds, and hybrid allocations.