Correlation Between AURUBIS AG and SIVERS SEMICONDUCTORS
Can any of the company-specific risk be diversified away by investing in both AURUBIS AG and SIVERS SEMICONDUCTORS 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 AURUBIS AG and SIVERS SEMICONDUCTORS into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between AURUBIS AG UNSPADR and SIVERS SEMICONDUCTORS AB, you can compare the effects of market volatilities on AURUBIS AG and SIVERS SEMICONDUCTORS 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 AURUBIS AG with a short position of SIVERS SEMICONDUCTORS. Check out your portfolio center. Please also check ongoing floating volatility patterns of AURUBIS AG and SIVERS SEMICONDUCTORS.
Diversification Opportunities for AURUBIS AG and SIVERS SEMICONDUCTORS
-0.82 | Correlation Coefficient |
Pay attention - limited upside
The 3 months correlation between AURUBIS and SIVERS is -0.82. Overlapping area represents the amount of risk that can be diversified away by holding AURUBIS AG UNSPADR and SIVERS SEMICONDUCTORS AB in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on SIVERS SEMICONDUCTORS and AURUBIS AG 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 AURUBIS AG UNSPADR are associated (or correlated) with SIVERS SEMICONDUCTORS. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of SIVERS SEMICONDUCTORS has no effect on the direction of AURUBIS AG i.e., AURUBIS AG and SIVERS SEMICONDUCTORS go up and down completely randomly.
Pair Corralation between AURUBIS AG and SIVERS SEMICONDUCTORS
Assuming the 90 days trading horizon AURUBIS AG UNSPADR is expected to generate 0.62 times more return on investment than SIVERS SEMICONDUCTORS. However, AURUBIS AG UNSPADR is 1.61 times less risky than SIVERS SEMICONDUCTORS. It trades about 0.02 of its potential returns per unit of risk. SIVERS SEMICONDUCTORS AB is currently generating about 0.0 per unit of risk. If you would invest 3,574 in AURUBIS AG UNSPADR on September 20, 2024 and sell it today you would earn a total of 206.00 from holding AURUBIS AG UNSPADR or generate 5.76% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
AURUBIS AG UNSPADR vs. SIVERS SEMICONDUCTORS AB
Performance |
Timeline |
AURUBIS AG UNSPADR |
SIVERS SEMICONDUCTORS |
AURUBIS AG and SIVERS SEMICONDUCTORS Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with AURUBIS AG and SIVERS SEMICONDUCTORS
The main advantage of trading using opposite AURUBIS AG and SIVERS SEMICONDUCTORS positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if AURUBIS AG position performs unexpectedly, SIVERS SEMICONDUCTORS 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 SIVERS SEMICONDUCTORS will offset losses from the drop in SIVERS SEMICONDUCTORS's long position.AURUBIS AG vs. Southern Copper | AURUBIS AG vs. Sandfire Resources Limited | AURUBIS AG vs. Superior Plus Corp | AURUBIS AG vs. NMI Holdings |
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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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