Refining Custom Investment Baskets

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In a previous blog (Building Custom Baskets), we showed how Finsera Basket Builder can be used to easily construct a custom cybersecurity basket.

Here we show how the performance of such a basket can be incrementally enhanced.

At first, we evaluate the performance of two factors in the cap-weighted basket of cybersecurity names:

  • Sales growth defined as year over year change in total sales
  • Market beta evaluated over trailing 52 week period

For the signals, we divide the universe into quintiles based on signal exposure and evaluate the average performance by quintile.

The quintile analysis shows that the slowest growing companies consistently underperform the rest of the investment universe. Similarly the quintile analysis shows that the highest beta names have significantly inferior performance.

Quintile Analysis - Sales Growth:

Quintile Analysis - Sales Growth

Quintile Analysis - Beta:

Quintile Analysis - Beta

We then incrementally build and compare the performance of 3 different baskets:

  • The initial cap-weighted basket of cybersecurity stocks based on the largest 5 ETFs by AUM (cyber_5)
  • A second basket which excludes the bottom quintile of cybersecurity names based on Sales Growth (cyber_5_1)
  • A third basket which further excludes the highest quintile of names based on market Beta (cyber_5_2)

Using our basket compare module:

Basket compare configuration

We can see that Finsera’s basket builder makes it easy to test assumptions and implement small refinements in basket composition which can result in meaningful performance improvements.

Basket Compare Annualized Return Charts:

Basket Compare Annualized Return Chart

‘cyber_5’: initial basket; ‘cyber_5_1’: excludes bottom quintile based on Sales Growth; ‘cyber_5_2’: excludes bottom quintile based on Sales Growth and excludes highest quintile of names based on Beta