Documentation

Upload your Zerodha or Groww holdings and rebalance from the portfolio you own

Per-stock bounds, exclusions, sector limits and market-cap limits inside the optimization

Enterprise runs under mandate constraints, measured against NIFTY 500 TRI by default

Simulate periodic rebalancing with expanding or rolling training windows

Forward wealth paths, conditional on the selected model, frozen inputs, configuration, engine version and seed

PDF reports and Excel workbooks for optimization, backtest and Monte Carlo runs

Run optimizations and read results from Claude, ChatGPT and other MCP clients

17 Indian and US benchmarks, with the price index or Total Return Index basis

US-listed equities with total-return ETF benchmarks and a US risk-free rate

The daily India 10-year yield and the US rate curve behind every excess return

Equity mutual funds with daily NAVs from AMFI's official history

Capital Asset Pricing Model for expected return estimation

Markowitz framework for optimal portfolio construction

The set of portfolios offering maximum return for each risk level

Techniques for estimating future asset returns

Measuring and interpreting asset price variability

Classic Markowitz portfolio optimization

Minimize total portfolio risk

Maximize risk-adjusted returns

Maximize expected utility with risk aversion

Exact efficient frontier tracing algorithm

Bayesian blend of equilibrium returns and entropy-tilted views

MVO with exponentially weighted moments that adapt to volatility

Ellipsoidal worst-case MVO that hedges against return estimation error

Michaud-style resampled efficient frontier via block bootstrap

L1-penalised mean-variance for concentrated portfolios

Markov-switching regime-conditioned mean-variance optimization

Equal risk contribution from each asset

Generalised risk parity across alternative risk measures

Closed-form weighting inversely proportional to standalone volatility

Maximise the diversification ratio across the asset universe

Minimise the quadratic form of the correlation matrix

ML-based hierarchical clustering allocation

Hierarchical Equal Risk Contribution

Enhanced Hierarchical Equal Risk Contribution

Nested Clustered Optimization

Minimize Conditional Value at Risk

Minimize Conditional Drawdown at Risk

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

Minimise Entropic Drawdown-at-Risk for capital preservation mandates

Penalise downside variance only, leaving upside untouched

Worst-case CVaR over a Wasserstein ball of distributions

Long-only enhanced indexing with a tracking-error budget

Replicate an index with a small subset of constituents

Cross-validated meta-optimizer that combines multiple base allocators

Simple 1/N allocation baseline

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

Long-only growth-optimal portfolio that maximises log wealth

Stat-arb on cointegrated pairs with a Kalman-filtered hedge ratio (API and MCP only)