Correlation Between Corning Incorporated and Meta Materials
Can any of the company-specific risk be diversified away by investing in both Corning Incorporated and Meta Materials 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 Corning Incorporated and Meta Materials into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Corning Incorporated and Meta Materials, you can compare the effects of market volatilities on Corning Incorporated and Meta Materials 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 Corning Incorporated with a short position of Meta Materials. Check out your portfolio center. Please also check ongoing floating volatility patterns of Corning Incorporated and Meta Materials.
Diversification Opportunities for Corning Incorporated and Meta Materials
-0.7 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Corning and Meta is -0.7. Overlapping area represents the amount of risk that can be diversified away by holding Corning Incorporated and Meta Materials in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Meta Materials and Corning Incorporated 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 Corning Incorporated are associated (or correlated) with Meta Materials. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Meta Materials has no effect on the direction of Corning Incorporated i.e., Corning Incorporated and Meta Materials go up and down completely randomly.
Pair Corralation between Corning Incorporated and Meta Materials
Considering the 90-day investment horizon Corning Incorporated is expected to generate 0.2 times more return on investment than Meta Materials. However, Corning Incorporated is 5.02 times less risky than Meta Materials. It trades about 0.0 of its potential returns per unit of risk. Meta Materials is currently generating about -0.06 per unit of risk. If you would invest 3,483 in Corning Incorporated on January 24, 2024 and sell it today you would lose (328.00) from holding Corning Incorporated or give up 9.42% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Corning Incorporated vs. Meta Materials
Performance |
Timeline |
Corning Incorporated |
Meta Materials |
Corning Incorporated and Meta Materials Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Corning Incorporated and Meta Materials
The main advantage of trading using opposite Corning Incorporated and Meta Materials positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Corning Incorporated position performs unexpectedly, Meta Materials 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 Meta Materials will offset losses from the drop in Meta Materials' long position.Corning Incorporated vs. OSI Systems | Corning Incorporated vs. Fabrinet | Corning Incorporated vs. Jabil Circuit | Corning Incorporated vs. Vicor |
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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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