Correlation Between SoFi Technologies and Mango Capital
Can any of the company-specific risk be diversified away by investing in both SoFi Technologies and Mango Capital 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 SoFi Technologies and Mango Capital into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between SoFi Technologies and Mango Capital, you can compare the effects of market volatilities on SoFi Technologies and Mango Capital 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 SoFi Technologies with a short position of Mango Capital. Check out your portfolio center. Please also check ongoing floating volatility patterns of SoFi Technologies and Mango Capital.
Diversification Opportunities for SoFi Technologies and Mango Capital
-0.49 | Correlation Coefficient |
Very good diversification
The 3 months correlation between SoFi and Mango is -0.49. Overlapping area represents the amount of risk that can be diversified away by holding SoFi Technologies and Mango Capital in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Mango Capital and SoFi Technologies 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 SoFi Technologies are associated (or correlated) with Mango Capital. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Mango Capital has no effect on the direction of SoFi Technologies i.e., SoFi Technologies and Mango Capital go up and down completely randomly.
Pair Corralation between SoFi Technologies and Mango Capital
Given the investment horizon of 90 days SoFi Technologies is expected to generate 3.57 times more return on investment than Mango Capital. However, SoFi Technologies is 3.57 times more volatile than Mango Capital. It trades about 0.09 of its potential returns per unit of risk. Mango Capital is currently generating about 0.03 per unit of risk. If you would invest 807.00 in SoFi Technologies on September 4, 2024 and sell it today you would earn a total of 781.00 from holding SoFi Technologies or generate 96.78% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Very Weak |
| Accuracy | 75.3% |
| Values | Daily Returns |
SoFi Technologies vs. Mango Capital
Performance |
| Timeline |
| SoFi Technologies |
| Mango Capital |
SoFi Technologies and Mango Capital Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with SoFi Technologies and Mango Capital
The main advantage of trading using opposite SoFi Technologies and Mango Capital positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if SoFi Technologies position performs unexpectedly, Mango Capital 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 Mango Capital will offset losses from the drop in Mango Capital's long position.| SoFi Technologies vs. Upstart Holdings | SoFi Technologies vs. Affirm Holdings | SoFi Technologies vs. Lucid Group | SoFi Technologies vs. Palantir Technologies Class |
| Mango Capital vs. Shopify | Mango Capital vs. Docebo Inc | Mango Capital vs. Unity Software | Mango Capital vs. Fastly 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 Performance Analysis module to check effects of mean-variance optimization against your current asset allocation.
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