Correlation Between GM and Soligenix
Can any of the company-specific risk be diversified away by investing in both GM and Soligenix 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 GM and Soligenix into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between General Motors and Soligenix, you can compare the effects of market volatilities on GM and Soligenix 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 GM with a short position of Soligenix. Check out your portfolio center. Please also check ongoing floating volatility patterns of GM and Soligenix.
Diversification Opportunities for GM and Soligenix
Excellent diversification
The 3 months correlation between GM and Soligenix is -0.51. Overlapping area represents the amount of risk that can be diversified away by holding General Motors and Soligenix in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Soligenix and GM 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 General Motors are associated (or correlated) with Soligenix. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Soligenix has no effect on the direction of GM i.e., GM and Soligenix go up and down completely randomly.
Pair Corralation between GM and Soligenix
Allowing for the 90-day total investment horizon GM is expected to generate 2.67 times less return on investment than Soligenix. But when comparing it to its historical volatility, General Motors is 8.45 times less risky than Soligenix. It trades about 0.07 of its potential returns per unit of risk. Soligenix is currently generating about 0.02 of returns per unit of risk over similar time horizon. If you would invest 1,144 in Soligenix on September 2, 2024 and sell it today you would lose (809.00) from holding Soligenix or give up 70.72% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
General Motors vs. Soligenix
Performance |
| Timeline |
| General Motors |
| Soligenix |
GM and Soligenix Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with GM and Soligenix
The main advantage of trading using opposite GM and Soligenix positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if GM position performs unexpectedly, Soligenix 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 Soligenix will offset losses from the drop in Soligenix's long position.The idea behind General Motors and Soligenix pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.| Soligenix vs. Zura Bio Limited | Soligenix vs. Phio Pharmaceuticals Corp | Soligenix vs. Immix Biopharma | Soligenix vs. Addex Therapeutics |
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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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