Correlation Between PKSHA TECHNOLOGY and American Eagle
Can any of the company-specific risk be diversified away by investing in both PKSHA TECHNOLOGY and American Eagle 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 PKSHA TECHNOLOGY and American Eagle into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between PKSHA TECHNOLOGY INC and American Eagle Outfitters, you can compare the effects of market volatilities on PKSHA TECHNOLOGY and American Eagle 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 PKSHA TECHNOLOGY with a short position of American Eagle. Check out your portfolio center. Please also check ongoing floating volatility patterns of PKSHA TECHNOLOGY and American Eagle.
Diversification Opportunities for PKSHA TECHNOLOGY and American Eagle
-0.35 | Correlation Coefficient |
Very good diversification
The 3 months correlation between PKSHA and American is -0.35. Overlapping area represents the amount of risk that can be diversified away by holding PKSHA TECHNOLOGY INC and American Eagle Outfitters in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on American Eagle Outfitters and PKSHA 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 PKSHA TECHNOLOGY INC are associated (or correlated) with American Eagle. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of American Eagle Outfitters has no effect on the direction of PKSHA TECHNOLOGY i.e., PKSHA TECHNOLOGY and American Eagle go up and down completely randomly.
Pair Corralation between PKSHA TECHNOLOGY and American Eagle
Assuming the 90 days horizon PKSHA TECHNOLOGY INC is expected to generate 1.29 times more return on investment than American Eagle. However, PKSHA TECHNOLOGY is 1.29 times more volatile than American Eagle Outfitters. It trades about 0.05 of its potential returns per unit of risk. American Eagle Outfitters is currently generating about 0.03 per unit of risk. If you would invest 1,350 in PKSHA TECHNOLOGY INC on October 16, 2024 and sell it today you would earn a total of 830.00 from holding PKSHA TECHNOLOGY INC or generate 61.48% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
PKSHA TECHNOLOGY INC vs. American Eagle Outfitters
Performance |
Timeline |
PKSHA TECHNOLOGY INC |
American Eagle Outfitters |
PKSHA TECHNOLOGY and American Eagle Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with PKSHA TECHNOLOGY and American Eagle
The main advantage of trading using opposite PKSHA TECHNOLOGY and American Eagle positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if PKSHA TECHNOLOGY position performs unexpectedly, American Eagle 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 American Eagle will offset losses from the drop in American Eagle's long position.PKSHA TECHNOLOGY vs. Silicon Motion Technology | PKSHA TECHNOLOGY vs. CARSALESCOM | PKSHA TECHNOLOGY vs. BOS BETTER ONLINE | PKSHA TECHNOLOGY vs. Lamar Advertising |
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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 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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