Correlation Between Amkor Technology and FIREWEED METALS
Can any of the company-specific risk be diversified away by investing in both Amkor Technology and FIREWEED METALS 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 Amkor Technology and FIREWEED METALS into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Amkor Technology and FIREWEED METALS P, you can compare the effects of market volatilities on Amkor Technology and FIREWEED METALS 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 Amkor Technology with a short position of FIREWEED METALS. Check out your portfolio center. Please also check ongoing floating volatility patterns of Amkor Technology and FIREWEED METALS.
Diversification Opportunities for Amkor Technology and FIREWEED METALS
-0.59 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Amkor and FIREWEED is -0.59. Overlapping area represents the amount of risk that can be diversified away by holding Amkor Technology and FIREWEED METALS P in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on FIREWEED METALS P and Amkor Technology 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 Amkor Technology are associated (or correlated) with FIREWEED METALS. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of FIREWEED METALS P has no effect on the direction of Amkor Technology i.e., Amkor Technology and FIREWEED METALS go up and down completely randomly.
Pair Corralation between Amkor Technology and FIREWEED METALS
Assuming the 90 days horizon Amkor Technology is expected to under-perform the FIREWEED METALS. But the stock apears to be less risky and, when comparing its historical volatility, Amkor Technology is 1.24 times less risky than FIREWEED METALS. The stock trades about -0.22 of its potential returns per unit of risk. The FIREWEED METALS P is currently generating about 0.07 of returns per unit of risk over similar time horizon. If you would invest 96.00 in FIREWEED METALS P on December 29, 2024 and sell it today you would earn a total of 11.00 from holding FIREWEED METALS P or generate 11.46% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Amkor Technology vs. FIREWEED METALS P
Performance |
Timeline |
Amkor Technology |
FIREWEED METALS P |
Amkor Technology and FIREWEED METALS Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Amkor Technology and FIREWEED METALS
The main advantage of trading using opposite Amkor Technology and FIREWEED METALS positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Amkor Technology position performs unexpectedly, FIREWEED METALS 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 FIREWEED METALS will offset losses from the drop in FIREWEED METALS's long position.Amkor Technology vs. Sporting Clube de | Amkor Technology vs. The Boston Beer | Amkor Technology vs. Air Transport Services | Amkor Technology vs. Suntory Beverage Food |
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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 Performance Analysis module to check effects of mean-variance optimization against your current asset allocation.
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