The 65 -
day average correlation of stocks fell to 0.52 in January.
Not exact matches
Correlation uses a 252 trading
day moving
average.
Specifically, they calculate the
average Pearson correlation of daily returns among all 30 stocks comprising the Dow Jones Industrial Average (DJIA) over a specified interval (ranging from 10 to 60 trading days), accounting for occasional index rev
average Pearson
correlation of daily returns among all 30 stocks comprising the Dow Jones Industrial
Average (DJIA) over a specified interval (ranging from 10 to 60 trading days), accounting for occasional index rev
Average (DJIA) over a specified interval (ranging from 10 to 60 trading
days), accounting for occasional index revisions.
Here is a heat map where the
average 60 -
day past return is on the horizontal axis, and
average sector
correlation is on the vertical axis, and the variable displayed is
average future 60 -
day returns.
Here is a graph showing the price return on the S&P 500 over the next 60
days as a function of the
average sector
correlation over the last 60
days:
Here is a heat map where the
average 60 -
day past return is on the horizontal axis, and
average sector
correlation is on the vertical axis, and the variable displayed is frequency of occurrence.
Given that
correlations tend to rise in a panic, a reasonable measure of sentiment is to measure the
average absolute value of 10 -
day correlations.
Just looking at the
average correlation or
average downside
correlation of the typical Russell 1000 stock to the S&P 500 using a 252 -
day lookback should clearly demonstrate a positive trend over time.
In mid-December 2017, it made up 19 percent, and the long - run
average for the 90 -
day correlation was negative 1 percent.