Correlation Between Kulicke and Everspin Technologies
Can any of the company-specific risk be diversified away by investing in both Kulicke and Everspin Technologies 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 Kulicke and Everspin Technologies into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Kulicke and Soffa and Everspin Technologies, you can compare the effects of market volatilities on Kulicke and Everspin Technologies 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 Kulicke with a short position of Everspin Technologies. Check out your portfolio center. Please also check ongoing floating volatility patterns of Kulicke and Everspin Technologies.
Diversification Opportunities for Kulicke and Everspin Technologies
0.53 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Kulicke and Everspin is 0.53. Overlapping area represents the amount of risk that can be diversified away by holding Kulicke and Soffa and Everspin Technologies in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Everspin Technologies and Kulicke 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 Kulicke and Soffa are associated (or correlated) with Everspin Technologies. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Everspin Technologies has no effect on the direction of Kulicke i.e., Kulicke and Everspin Technologies go up and down completely randomly.
Pair Corralation between Kulicke and Everspin Technologies
Given the investment horizon of 90 days Kulicke and Soffa is expected to generate 0.98 times more return on investment than Everspin Technologies. However, Kulicke and Soffa is 1.02 times less risky than Everspin Technologies. It trades about 0.18 of its potential returns per unit of risk. Everspin Technologies is currently generating about 0.13 per unit of risk. If you would invest 4,633 in Kulicke and Soffa on September 19, 2024 and sell it today you would earn a total of 378.00 from holding Kulicke and Soffa or generate 8.16% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Kulicke and Soffa vs. Everspin Technologies
Performance |
Timeline |
Kulicke and Soffa |
Everspin Technologies |
Kulicke and Everspin Technologies Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Kulicke and Everspin Technologies
The main advantage of trading using opposite Kulicke and Everspin Technologies positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Kulicke position performs unexpectedly, Everspin Technologies 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 Everspin Technologies will offset losses from the drop in Everspin Technologies' long position.The idea behind Kulicke and Soffa and Everspin Technologies pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.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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