NETWORK STOCK PORTFOLIO OPTIMIZATION

Context and Problem Statement

Active investing in the asset management industry aims to beat the stock market’s average returns, for which portfolio managers track a particular index and try to beat that index by creating their own portfolios.

Portfolio construction involves selection of stocks that have a higher probability of giving better returns in comparison to the tracking index, like S&P 500. In this project, I used the concept of Network Analysis to select a basket of stocks and create two portfolios. I simulated portfolio value by investing a certain amount, keeping the portfolio for an entire year and we will then compare it against the S&P 500 index.

In this project we will try to follow the approach mentioned in the below research paper:

Dynamic portfolio strategy using a clustering approach

Proposed Approach

• Collect the price data for all S&P 500 components from 2011 till 2020

• Compute log returns for the S&P 500 components for same time period

• Compute the correlation matrix for the above log returns

• Find out the Top n central and peripheral stocks based on the following network topological parameters:

  • Degree centrality

  • Betweenness centrality

  • Distance on degree criterion

  • Distance on correlation criterion

  • Distance on distance criterion

• Simulate the performance of central and peripheral portfolios against the performance of S&P 500 for the year 2021