Side Projects

Intelligent Portfolio Builder: Bayesian Optimization Engine

Quantitative finance application that constructs optimal investment portfolios using Bayesian optimization. Builds portfolios minimizing volatility while hitting target returns with institutional-grade risk management.

Portfolio construction is traditionally a manual, time-intensive process. Intelligent Portfolio Builder automates optimal portfolio creation using advanced Bayesian optimization techniques, balancing return targets with volatility minimization.

Core Algorithm

Bayesian Optimization Approach:

1User defines target annual return (e.g., 12%)

2Algorithm explores asset allocation space using Gaussian processes

3Optimization objective: minimize portfolio volatility subject to return constraint

4Institutional constraints: sector limits, concentration caps, rebalancing costs

5Output: optimal weights with expected return/risk metrics

Risk Management Features

Volatility Minimization: Reduces portfolio standard deviation while meeting return targets

Concentration Limits: Caps maximum position size to prevent over-exposure

Sector Diversification: Enforces sector allocation constraints

Rebalancing Cost Model: Accounts for transaction costs in optimization

Historical Backtest: Validates portfolio performance on historical data

Technical Implementation

Python-based optimization engine using scikit-optimize for Bayesian optimization. Portfolio analytics calculated using modern portfolio theory (Markowitz, Sharpe ratio, drawdown metrics). Supports multiple asset classes: equities, bonds, ETFs, mutual funds.

Difference from Portfolio Optimization Platform

This project focuses on algorithmic portfolio construction using Bayesian optimization for personal/academic exploration. The Portfolio Optimization Platform (professional project) is a production advisor tool with client-facing reports, Excel export, and AI-written narratives.

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