Correlation Between Apple and SOFI TECHNOLOGIES
Can any of the company-specific risk be diversified away by investing in both Apple and SOFI 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 Apple and SOFI TECHNOLOGIES into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Apple Inc and SOFI TECHNOLOGIES, you can compare the effects of market volatilities on Apple and SOFI 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 Apple with a short position of SOFI TECHNOLOGIES. Check out your portfolio center. Please also check ongoing floating volatility patterns of Apple and SOFI TECHNOLOGIES.
Diversification Opportunities for Apple and SOFI TECHNOLOGIES
0.75 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Apple and SOFI is 0.75. Overlapping area represents the amount of risk that can be diversified away by holding Apple Inc and SOFI TECHNOLOGIES in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on SOFI TECHNOLOGIES and Apple 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 Apple Inc are associated (or correlated) with SOFI TECHNOLOGIES. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of SOFI TECHNOLOGIES has no effect on the direction of Apple i.e., Apple and SOFI TECHNOLOGIES go up and down completely randomly.
Pair Corralation between Apple and SOFI TECHNOLOGIES
Assuming the 90 days trading horizon Apple is expected to generate 8.57 times less return on investment than SOFI TECHNOLOGIES. But when comparing it to its historical volatility, Apple Inc is 3.04 times less risky than SOFI TECHNOLOGIES. It trades about 0.14 of its potential returns per unit of risk. SOFI TECHNOLOGIES is currently generating about 0.39 of returns per unit of risk over similar time horizon. If you would invest 1,016 in SOFI TECHNOLOGIES on August 25, 2024 and sell it today you would earn a total of 391.00 from holding SOFI TECHNOLOGIES or generate 38.48% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Apple Inc vs. SOFI TECHNOLOGIES
Performance |
| Timeline |
| Apple Inc |
| SOFI TECHNOLOGIES |
Apple and SOFI TECHNOLOGIES Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Apple and SOFI TECHNOLOGIES
The main advantage of trading using opposite Apple and SOFI TECHNOLOGIES positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Apple position performs unexpectedly, SOFI 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 SOFI TECHNOLOGIES will offset losses from the drop in SOFI TECHNOLOGIES's long position.| Apple vs. FUYO GENERAL LEASE | Apple vs. United Rentals | Apple vs. Qurate Retail Series | Apple vs. National Retail Properties |
| SOFI TECHNOLOGIES vs. Apple Inc | SOFI TECHNOLOGIES vs. Apple Inc | SOFI TECHNOLOGIES vs. Apple Inc | SOFI TECHNOLOGIES vs. Apple Inc |
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 Equity Valuation module to check real value of public entities based on technical and fundamental data.
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