Athena

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

Investors want to gain maximum returns from their portfolio while minimizing the risks associated. But purchasing assets without analyzing the fundamentals and merely relying on speculation and market sentiment is a significant problem in portfolio management. This is the problem that the model is trying to solve so that investors can get suggestions from the model and invest wisely.

We intend to propose a novel solution to optimize and enhance portfolio performance using a combination of deep learning and statistical models along with asset fundamentals analysis to obtain maximum returns with minimal risk.

Uses

• The proposed model can be used to maximize the returns and minimize the risk of a given portfolio (a collection of stocks and other assets) by allocating an optimal weight for each asset in the portfolio.
• It can provide a portfolio that delivers high return per unit risk.
• It can also create a balanced portfolio with many different investments such as stocks, bonds and mutual funds.

Model architecture

Reference Links

Site links

• Portfolio Optimization methods

YouTube links

• Battle of Portfolio Optimization methods
• Portfolio Optimization using Python
• What is LSTM? Simple explanation of LSTM