Correlation Between Tower Semiconductor and USWE SPORTS
Can any of the company-specific risk be diversified away by investing in both Tower Semiconductor and USWE SPORTS 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 Tower Semiconductor and USWE SPORTS into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Tower Semiconductor and USWE SPORTS AB, you can compare the effects of market volatilities on Tower Semiconductor and USWE SPORTS 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 Tower Semiconductor with a short position of USWE SPORTS. Check out your portfolio center. Please also check ongoing floating volatility patterns of Tower Semiconductor and USWE SPORTS.
Diversification Opportunities for Tower Semiconductor and USWE SPORTS
0.75 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Tower and USWE is 0.75. Overlapping area represents the amount of risk that can be diversified away by holding Tower Semiconductor and USWE SPORTS AB in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on USWE SPORTS AB and Tower Semiconductor 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 Tower Semiconductor are associated (or correlated) with USWE SPORTS. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of USWE SPORTS AB has no effect on the direction of Tower Semiconductor i.e., Tower Semiconductor and USWE SPORTS go up and down completely randomly.
Pair Corralation between Tower Semiconductor and USWE SPORTS
Assuming the 90 days horizon Tower Semiconductor is expected to generate 2.02 times less return on investment than USWE SPORTS. But when comparing it to its historical volatility, Tower Semiconductor is 1.51 times less risky than USWE SPORTS. It trades about 0.17 of its potential returns per unit of risk. USWE SPORTS AB is currently generating about 0.23 of returns per unit of risk over similar time horizon. If you would invest 65.00 in USWE SPORTS AB on April 20, 2025 and sell it today you would earn a total of 42.00 from holding USWE SPORTS AB or generate 64.62% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Tower Semiconductor vs. USWE SPORTS AB
Performance |
Timeline |
Tower Semiconductor |
USWE SPORTS AB |
Tower Semiconductor and USWE SPORTS Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Tower Semiconductor and USWE SPORTS
The main advantage of trading using opposite Tower Semiconductor and USWE SPORTS positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Tower Semiconductor position performs unexpectedly, USWE SPORTS 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 USWE SPORTS will offset losses from the drop in USWE SPORTS's long position.Tower Semiconductor vs. Universal Health Realty | Tower Semiconductor vs. Fevertree Drinks PLC | Tower Semiconductor vs. Siemens Healthineers AG | Tower Semiconductor vs. National Beverage Corp |
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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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