This repository houses a financial portfolio optimization tool developed using Particle Swarm Optimization (PSO). The project utilizes historical return data for three assets to calculate expected returns and covariance matrix. The objective is to formulate an optimal asset allocation strategy that maximizes the Sharpe ratio, resulting in a balanced portfolio with optimal return and minimized volatility.
- Particle Swarm Optimization (PSO): Applied PSO to find the optimal combination of asset weights that maximizes the Sharpe ratio. PSO is a heuristic optimization technique inspired by the social behavior of birds and fish.
- Historical Return Data: Utilized historical return data for three assets to calculate key financial metrics, including expected returns and covariance matrix.
- Sharpe Ratio Maximization: Formulated an objective function to maximize the Sharpe ratio, representing the trade-off between return and risk. The goal is to achieve an optimal balance that enhances risk-adjusted performance.
- Efficient Frontier Plots: Visualized the results through efficient frontier plots, illustrating the set of optimal portfolios that offer the highest expected return for a given level of risk.
- Scatter Plots: Presented the optimal asset allocation with scatter plots, providing a clear representation of the portfolio's risk and return characteristics.
The optimized portfolio achieved a balanced asset allocation with maximized Sharpe ratio, leading to enhanced risk-adjusted performance.
- Optimal Portfolio Weights: [0.14485298 0.32144943 0.53369759]
- Optimal Portfolio Return: 0.015010062621142822
- Optimal Portfolio Volatility: 0.0013236549826573269
- The project was inspired by the need for effective portfolio optimization techniques in financial markets.
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