Correlation Between Peak Resources and URBAN OUTFITTERS
Can any of the company-specific risk be diversified away by investing in both Peak Resources and URBAN OUTFITTERS 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 Peak Resources and URBAN OUTFITTERS into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Peak Resources Limited and URBAN OUTFITTERS, you can compare the effects of market volatilities on Peak Resources and URBAN OUTFITTERS 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 Peak Resources with a short position of URBAN OUTFITTERS. Check out your portfolio center. Please also check ongoing floating volatility patterns of Peak Resources and URBAN OUTFITTERS.
Diversification Opportunities for Peak Resources and URBAN OUTFITTERS
0.71 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Peak and URBAN is 0.71. Overlapping area represents the amount of risk that can be diversified away by holding Peak Resources Limited and URBAN OUTFITTERS in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on URBAN OUTFITTERS and Peak Resources 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 Peak Resources Limited are associated (or correlated) with URBAN OUTFITTERS. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of URBAN OUTFITTERS has no effect on the direction of Peak Resources i.e., Peak Resources and URBAN OUTFITTERS go up and down completely randomly.
Pair Corralation between Peak Resources and URBAN OUTFITTERS
Assuming the 90 days horizon Peak Resources Limited is expected to under-perform the URBAN OUTFITTERS. In addition to that, Peak Resources is 2.62 times more volatile than URBAN OUTFITTERS. It trades about -0.02 of its total potential returns per unit of risk. URBAN OUTFITTERS is currently generating about 0.06 per unit of volatility. If you would invest 2,400 in URBAN OUTFITTERS on January 10, 2025 and sell it today you would earn a total of 2,230 from holding URBAN OUTFITTERS or generate 92.92% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Peak Resources Limited vs. URBAN OUTFITTERS
Performance |
| Timeline |
| Peak Resources |
| URBAN OUTFITTERS |
Peak Resources and URBAN OUTFITTERS Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Peak Resources and URBAN OUTFITTERS
The main advantage of trading using opposite Peak Resources and URBAN OUTFITTERS positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Peak Resources position performs unexpectedly, URBAN OUTFITTERS 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 URBAN OUTFITTERS will offset losses from the drop in URBAN OUTFITTERS's long position.| Peak Resources vs. Sinopec Shanghai Petrochemical | Peak Resources vs. Sumitomo Chemical | Peak Resources vs. FORMPIPE SOFTWARE AB | Peak Resources vs. GBS Software AG |
| URBAN OUTFITTERS vs. MAGIC SOFTWARE ENTR | URBAN OUTFITTERS vs. Singapore Airlines Limited | URBAN OUTFITTERS vs. Monster Beverage Corp | URBAN OUTFITTERS vs. Tsingtao Brewery |
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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