Documentation

Learn how to use the Portfolio Optimization platform to build optimized investment portfolios for Indian markets.

What is Portfolio Optimization?

Portfolio optimization is the process of selecting the best portfolio (asset distribution) from a set of all portfolios being considered. The objective typically maximizes factors such as expected return and minimizes costs like financial risk.

Our platform provides enterprise-grade portfolio optimization services specifically designed for Indian equity markets, supporting stocks listed on NSE and BSE with real-time data and advanced optimization algorithms.

Optimization Methods

Mean-Variance (MVO)

Classic Markowitz portfolio optimization

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Minimum Variance

Minimize total portfolio risk

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Maximum Sharpe

Maximize risk-adjusted returns

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Max Quadratic Utility

Maximize expected utility with risk aversion

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Critical Line Algorithm

Exact efficient frontier tracing algorithm

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Black-Litterman

Bayesian blend of equilibrium returns and entropy-tilted views

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EWMA Mean-Variance

MVO with exponentially weighted moments that adapt to volatility

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Robust Mean-Variance

Ellipsoidal worst-case MVO that hedges against return estimation error

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Resampled Mean-Variance

Michaud-style resampled efficient frontier via block bootstrap

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Sparse Markowitz (L1)

L1-penalised mean-variance for concentrated portfolios

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HMM Regime MVO

Markov-switching regime-conditioned mean-variance optimization

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Risk Parity

Equal risk contribution from each asset

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Risk Budgeting

Generalised risk parity across alternative risk measures

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Inverse Volatility

Closed-form weighting inversely proportional to standalone volatility

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Maximum Diversification

Maximise the diversification ratio across the asset universe

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Maximum Decorrelation

Minimise the quadratic form of the correlation matrix

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Hierarchical Risk Parity

ML-based hierarchical clustering allocation

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HERC

Hierarchical Equal Risk Contribution

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HERC2

Enhanced Hierarchical Equal Risk Contribution

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Nested Clustered (NCO)

Nested Clustered Optimization

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Minimum CVaR

Minimize Conditional Value at Risk

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Minimum CDaR

Minimize Conditional Drawdown at Risk

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Minimum EVaR

Minimise Entropic Value-at-Risk, a coherent upper bound on CVaR

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Minimum EDaR

Minimise Entropic Drawdown-at-Risk for capital preservation mandates

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Minimum Semivariance

Penalise downside variance only, leaving upside untouched

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Distributionally Robust CVaR

Worst-case CVaR over a Wasserstein ball of distributions

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Benchmark Tracker

Long-only enhanced indexing with a tracking-error budget

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Sparse Index Tracking

Replicate an index with a small subset of constituents

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Stacking Optimization

Cross-validated meta-optimizer that combines multiple base allocators

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Equally Weighted

Simple 1/N allocation baseline

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Quintile Momentum

Equal-weight the top momentum quintile, the long leg of the factor

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Kelly Optimization

Long-only growth-optimal portfolio that maximises log wealth

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Kalman Pairs Trading

Stat-arb on cointegrated pairs with a Kalman-filtered hedge ratio

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Dividend Optimizer

Optimize for dividend yield and growth (not yet available)

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