Correlation Between Armstrong World and Burnham Holdings
Can any of the company-specific risk be diversified away by investing in both Armstrong World and Burnham Holdings at the same time? Although using a correlation coefficient on its own may not help to predict future stock returns, this module helps to understand the diversifiable risk of combining Armstrong World and Burnham Holdings into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Armstrong World Industries and Burnham Holdings, you can compare the effects of market volatilities on Armstrong World and Burnham Holdings and check how they will diversify away market risk if combined in the same portfolio for a given time horizon. You can also utilize pair trading strategies of matching a long position in Armstrong World with a short position of Burnham Holdings. Check out your portfolio center. Please also check ongoing floating volatility patterns of Armstrong World and Burnham Holdings.
Diversification Opportunities for Armstrong World and Burnham Holdings
0.35 | Correlation Coefficient |
Weak diversification
The 3 months correlation between Armstrong and Burnham is 0.35. Overlapping area represents the amount of risk that can be diversified away by holding Armstrong World Industries and Burnham Holdings in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Burnham Holdings and Armstrong World is a relative statistical measure of the degree to which these equity instruments tend to move together. The correlation coefficient measures the extent to which returns on Armstrong World Industries are associated (or correlated) with Burnham Holdings. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Burnham Holdings has no effect on the direction of Armstrong World i.e., Armstrong World and Burnham Holdings go up and down completely randomly.
Pair Corralation between Armstrong World and Burnham Holdings
Considering the 90-day investment horizon Armstrong World Industries is expected to under-perform the Burnham Holdings. In addition to that, Armstrong World is 2.12 times more volatile than Burnham Holdings. It trades about -0.33 of its total potential returns per unit of risk. Burnham Holdings is currently generating about -0.1 per unit of volatility. If you would invest 1,417 in Burnham Holdings on October 14, 2024 and sell it today you would lose (17.00) from holding Burnham Holdings or give up 1.2% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Armstrong World Industries vs. Burnham Holdings
Performance |
Timeline |
Armstrong World Indu |
Burnham Holdings |
Armstrong World and Burnham Holdings Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Armstrong World and Burnham Holdings
The main advantage of trading using opposite Armstrong World and Burnham Holdings positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Armstrong World position performs unexpectedly, Burnham Holdings can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in Burnham Holdings will offset losses from the drop in Burnham Holdings' long position.Armstrong World vs. Quanex Building Products | Armstrong World vs. Gibraltar Industries | Armstrong World vs. Beacon Roofing Supply | Armstrong World vs. Janus International Group |
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Check out your portfolio center.Note that this page's information should be used as a complementary analysis to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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