dcajasn/Riskfolio-Lib
Riskfolio Lib
Riskfolio-Lib is a Python portfolio optimization library and convex risk management tool. It provides a framework for calculating optimal asset allocations using convex risk measures and mathematical programming solvers, supporting linear, quadratic, and semidefinite programming.
The library features a hierarchical risk parity framework and financial asset clustering tools to group similar instruments and improve diversification. It includes a portfolio backtesting engine for simulating investment strategies using historical data and cross-validation.
The system covers a broad range of quantitative capabilities, including mean-risk portfolio optimization, risk parity strategy implementation, and the application of graph-based and integer portfolio constraints. It also provides tools for portfolio report generation and integration that exposes optimization models as functions within spreadsheet environments.
Features
- Convex Optimization Solvers - Implements convex optimization solvers to determine optimal asset allocations that balance expected returns and risk.
- Financial Asset Clustering - Groups similar financial instruments using hierarchical clustering to enhance diversification through risk parity.
- Hierarchical Allocation Strategies - Groups assets by risk profile and allocates weights through risk parity or equal risk contribution.
- Hierarchical Optimization - Builds portfolios using clustering algorithms and hierarchical risk parity or equal risk contribution methods.
- Mean-Risk Models - Calculates asset weights to maximize utility or return while minimizing risk via convex measures.
- Statistical Estimation - Provides statistical methods for inferring asset parameters from historical data to feed optimization models.
- Hierarchical Risk Parity - Allocates asset weights based on risk parity and equal risk contribution using a hierarchical clustering framework.
- Risk Quantification - Provides mathematical measurement of potential losses and volatility using statistical distributions and drawdown metrics.
- Portfolio Risk Metrics - Implements quantitative risk metrics such as Value at Risk and Maximum Drawdown for portfolio stability evaluation.
- Convex Risk Frameworks - Provides a comprehensive framework for quantifying investment risk and balancing returns via convex programming.
- Graph-Based Optimization - Enforces investment limits and diversification constraints using network theory and graph metrics.
- Investment Constraints - Provides tools to define regulatory and structural limits within the portfolio optimization process.
- Risk Parity Optimization - Balances the risk contribution of each asset across dispersion, downside, and drawdown risk measures.
- Financial Performance Reports - Produces visual and tabular summaries of portfolio metrics and allocations for detailed performance analysis.
- Trading Strategy Backtesters - Evaluates portfolio optimization strategies against historical market data using cross-validation.
- Backtesting Engines - Simulates investment strategies using historical data and cross-validation to evaluate long-term performance.
- Investor Belief Integration - Allows users to adjust asset return and risk expectations by integrating subjective investor beliefs with market data.
- Optimization Constraint Enforcement - Applies integer constraints, such as cardinality and buy-in thresholds, to ensure structural portfolio requirements.
- Risk Allocation Clustering - Diversifies portfolios by grouping assets through hierarchical risk parity based on underlying correlation structures.
- Risk Parity Implementation - Allocates assets such that each contributes equally to the total portfolio risk across multiple categories.
- Spectral Asset Clustering - Groups financial assets into clusters using correlation matrices to improve portfolio diversification.
- Backtesting Simulations - Simulates the historical performance of portfolio optimization strategies to validate effectiveness before deployment.
- Financial Analytics - Portfolio optimization and strategic asset allocation.
- Financial Analytics Tools - Library for portfolio optimization and strategic asset allocation.
- Portfolio Management - Portfolio optimization and risk management library.
- Portfolio Optimization - Quantitative strategic asset allocation and portfolio optimization.
