Correlation Between Mueller Industries and SG Blocks
Can any of the company-specific risk be diversified away by investing in both Mueller Industries and SG Blocks 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 Mueller Industries and SG Blocks into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Mueller Industries and SG Blocks, you can compare the effects of market volatilities on Mueller Industries and SG Blocks 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 Mueller Industries with a short position of SG Blocks. Check out your portfolio center. Please also check ongoing floating volatility patterns of Mueller Industries and SG Blocks.
Diversification Opportunities for Mueller Industries and SG Blocks
-0.64 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Mueller and SGBX is -0.64. Overlapping area represents the amount of risk that can be diversified away by holding Mueller Industries and SG Blocks in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on SG Blocks and Mueller Industries 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 Mueller Industries are associated (or correlated) with SG Blocks. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of SG Blocks has no effect on the direction of Mueller Industries i.e., Mueller Industries and SG Blocks go up and down completely randomly.
Pair Corralation between Mueller Industries and SG Blocks
Considering the 90-day investment horizon Mueller Industries is expected to generate 0.39 times more return on investment than SG Blocks. However, Mueller Industries is 2.55 times less risky than SG Blocks. It trades about 0.07 of its potential returns per unit of risk. SG Blocks is currently generating about -0.21 per unit of risk. If you would invest 7,249 in Mueller Industries on August 30, 2024 and sell it today you would earn a total of 885.00 from holding Mueller Industries or generate 12.21% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Mueller Industries vs. SG Blocks
Performance |
Timeline |
Mueller Industries |
SG Blocks |
Mueller Industries and SG Blocks Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Mueller Industries and SG Blocks
The main advantage of trading using opposite Mueller Industries and SG Blocks positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Mueller Industries position performs unexpectedly, SG Blocks 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 SG Blocks will offset losses from the drop in SG Blocks' long position.Mueller Industries vs. Insteel Industries | Mueller Industries vs. Carpenter Technology | Mueller Industries vs. Haynes International | Mueller Industries vs. Northwest Pipe |
SG Blocks vs. Insteel Industries | SG Blocks vs. Carpenter Technology | SG Blocks vs. Haynes International | SG Blocks vs. Mueller Industries |
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 Equity Valuation module to check real value of public entities based on technical and fundamental data.
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