Analyzing Macro Trends

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While Finsera provides a very powerful engine for analyzing cross-sectional investment ideas, the Finsera platform is also an extremely useful tool to analyze market trends.

Consider the case of dispersion in stock returns. Return dispersion is commonly thought of as a measure of the potential value of stock selection ability. During times in which stocks have relatively low dispersion, an active investor will generally find it more difficult to beat a passive index, making the case for passive investing more compelling. On the other hand, if there is greater variability in stock returns there is also a greater opportunity for active investors to shine and the case for active investing is more compelling.

Using the Finsera platform, one can easily construct a measure of stock return dispersion to determine which periods historically presented a greater opportunity for an active investor. We construct this measure in the following manner:

  1. Compute the returns of all stocks in the universe in the past month
  2. Split then into 5 quintiles
  3. Compute the median return for each quintile
  4. Compute the difference in medians between Q5 and Q11

In the Finsera platform, this can be done using a couple of lines of code:

Macro Signal

And subsequently, you can analyze this dispersion measure over a period of several years for any universe of stocks. Below is the return dispersion for the Russell 1000 investment universe over time.

Macro Analysis

1 A more traditional measure of stock dispersion, such as the sum of the weighted squared deviations from the universe cap-weighted return yields results that are highly correlated (~0.9) with the measure used herein. Both measures were computed using the Finsera platform.