Correlation Between Spectra7 Microsystems and ASML Holding
Can any of the company-specific risk be diversified away by investing in both Spectra7 Microsystems and ASML Holding 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 Spectra7 Microsystems and ASML Holding into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Spectra7 Microsystems and ASML Holding NV, you can compare the effects of market volatilities on Spectra7 Microsystems and ASML Holding 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 Spectra7 Microsystems with a short position of ASML Holding. Check out your portfolio center. Please also check ongoing floating volatility patterns of Spectra7 Microsystems and ASML Holding.
Diversification Opportunities for Spectra7 Microsystems and ASML Holding
-0.19 | Correlation Coefficient |
Good diversification
The 3 months correlation between Spectra7 and ASML is -0.19. Overlapping area represents the amount of risk that can be diversified away by holding Spectra7 Microsystems and ASML Holding NV in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on ASML Holding NV and Spectra7 Microsystems 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 Spectra7 Microsystems are associated (or correlated) with ASML Holding. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of ASML Holding NV has no effect on the direction of Spectra7 Microsystems i.e., Spectra7 Microsystems and ASML Holding go up and down completely randomly.
Pair Corralation between Spectra7 Microsystems and ASML Holding
Assuming the 90 days horizon Spectra7 Microsystems is expected to generate 1.36 times less return on investment than ASML Holding. In addition to that, Spectra7 Microsystems is 3.59 times more volatile than ASML Holding NV. It trades about 0.0 of its total potential returns per unit of risk. ASML Holding NV is currently generating about 0.02 per unit of volatility. If you would invest 66,759 in ASML Holding NV on October 25, 2024 and sell it today you would earn a total of 7,865 from holding ASML Holding NV or generate 11.78% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 99.4% |
Values | Daily Returns |
Spectra7 Microsystems vs. ASML Holding NV
Performance |
Timeline |
Spectra7 Microsystems |
ASML Holding NV |
Spectra7 Microsystems and ASML Holding Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Spectra7 Microsystems and ASML Holding
The main advantage of trading using opposite Spectra7 Microsystems and ASML Holding positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Spectra7 Microsystems position performs unexpectedly, ASML Holding 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 ASML Holding will offset losses from the drop in ASML Holding's long position.Spectra7 Microsystems vs. Atomera | Spectra7 Microsystems vs. ASML Holding NV | Spectra7 Microsystems vs. Applied Materials | Spectra7 Microsystems vs. Aehr Test Systems |
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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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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