Correlation Between IPG Photonics and Meta Materials
Can any of the company-specific risk be diversified away by investing in both IPG Photonics 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 IPG Photonics and Meta Materials into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between IPG Photonics and Meta Materials, you can compare the effects of market volatilities on IPG Photonics 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 IPG Photonics with a short position of Meta Materials. Check out your portfolio center. Please also check ongoing floating volatility patterns of IPG Photonics and Meta Materials.
Diversification Opportunities for IPG Photonics and Meta Materials
-0.75 | Correlation Coefficient |
Pay attention - limited upside
The 3 months correlation between IPG and Meta is -0.75. Overlapping area represents the amount of risk that can be diversified away by holding IPG Photonics and Meta Materials in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Meta Materials and IPG Photonics 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 IPG Photonics 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 IPG Photonics i.e., IPG Photonics and Meta Materials go up and down completely randomly.
Pair Corralation between IPG Photonics and Meta Materials
Given the investment horizon of 90 days IPG Photonics is expected to generate 716.42 times less return on investment than Meta Materials. But when comparing it to its historical volatility, IPG Photonics is 23.29 times less risky than Meta Materials. It trades about 0.01 of its potential returns per unit of risk. Meta Materials is currently generating about 0.19 of returns per unit of risk over similar time horizon. If you would invest 7.00 in Meta Materials on August 28, 2024 and sell it today you would lose (0.90) from holding Meta Materials or give up 12.86% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
IPG Photonics vs. Meta Materials
Performance |
Timeline |
IPG Photonics |
Meta Materials |
IPG Photonics and Meta Materials Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with IPG Photonics and Meta Materials
The main advantage of trading using opposite IPG Photonics and Meta Materials positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if IPG Photonics 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.IPG Photonics vs. Teradyne | IPG Photonics vs. Ultra Clean Holdings | IPG Photonics vs. Onto Innovation | IPG Photonics vs. Cohu Inc |
Meta Materials vs. Cps Technologies | Meta Materials vs. Kopin | Meta Materials vs. Wallbox NV | Meta Materials vs. Corning Incorporated |
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 Headlines Timeline module to stay connected to all market stories and filter out noise. Drill down to analyze hype elasticity.
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