Correlation Between AGRICULTBK HADR/25 and Apple
Can any of the company-specific risk be diversified away by investing in both AGRICULTBK HADR/25 and Apple 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 AGRICULTBK HADR/25 and Apple into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between AGRICULTBK HADR25 YC and Apple Inc, you can compare the effects of market volatilities on AGRICULTBK HADR/25 and Apple 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 AGRICULTBK HADR/25 with a short position of Apple. Check out your portfolio center. Please also check ongoing floating volatility patterns of AGRICULTBK HADR/25 and Apple.
Diversification Opportunities for AGRICULTBK HADR/25 and Apple
0.79 | Correlation Coefficient |
Poor diversification
The 3 months correlation between AGRICULTBK and Apple is 0.79. Overlapping area represents the amount of risk that can be diversified away by holding AGRICULTBK HADR25 YC and Apple Inc in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Apple Inc and AGRICULTBK HADR/25 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 AGRICULTBK HADR25 YC are associated (or correlated) with Apple. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Apple Inc has no effect on the direction of AGRICULTBK HADR/25 i.e., AGRICULTBK HADR/25 and Apple go up and down completely randomly.
Pair Corralation between AGRICULTBK HADR/25 and Apple
Assuming the 90 days trading horizon AGRICULTBK HADR/25 is expected to generate 1.84 times less return on investment than Apple. In addition to that, AGRICULTBK HADR/25 is 1.37 times more volatile than Apple Inc. It trades about 0.14 of its total potential returns per unit of risk. Apple Inc is currently generating about 0.36 per unit of volatility. If you would invest 20,575 in Apple Inc on September 1, 2024 and sell it today you would earn a total of 1,860 from holding Apple Inc or generate 9.04% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
AGRICULTBK HADR25 YC vs. Apple Inc
Performance |
| Timeline |
| AGRICULTBK HADR/25 |
| Apple Inc |
AGRICULTBK HADR/25 and Apple Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with AGRICULTBK HADR/25 and Apple
The main advantage of trading using opposite AGRICULTBK HADR/25 and Apple positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if AGRICULTBK HADR/25 position performs unexpectedly, Apple 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 Apple will offset losses from the drop in Apple's long position.| AGRICULTBK HADR/25 vs. Scandinavian Tobacco Group | AGRICULTBK HADR/25 vs. British American Tobacco | AGRICULTBK HADR/25 vs. ITALIAN WINE BRANDS | AGRICULTBK HADR/25 vs. VIRGIN WINES UK |
| Apple vs. Enter Air SA | Apple vs. Wayside Technology Group | Apple vs. DELTA AIR LINES | Apple vs. Align Technology |
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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