Correlation Between FAT Brands and Soluna Holdings
Can any of the company-specific risk be diversified away by investing in both FAT Brands and Soluna Holdings 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 FAT Brands and Soluna Holdings into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between FAT Brands and Soluna Holdings Preferred, you can compare the effects of market volatilities on FAT Brands and Soluna Holdings 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 FAT Brands with a short position of Soluna Holdings. Check out your portfolio center. Please also check ongoing floating volatility patterns of FAT Brands and Soluna Holdings.
Diversification Opportunities for FAT Brands and Soluna Holdings
-0.55 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between FAT and Soluna is -0.55. Overlapping area represents the amount of risk that can be diversified away by holding FAT Brands and Soluna Holdings Preferred in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Soluna Holdings Preferred and FAT Brands 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 FAT Brands are associated (or correlated) with Soluna Holdings. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Soluna Holdings Preferred has no effect on the direction of FAT Brands i.e., FAT Brands and Soluna Holdings go up and down completely randomly.
Pair Corralation between FAT Brands and Soluna Holdings
Assuming the 90 days horizon FAT Brands is expected to generate 0.18 times more return on investment than Soluna Holdings. However, FAT Brands is 5.57 times less risky than Soluna Holdings. It trades about 0.29 of its potential returns per unit of risk. Soluna Holdings Preferred is currently generating about -0.04 per unit of risk. If you would invest 918.00 in FAT Brands on August 31, 2024 and sell it today you would earn a total of 60.00 from holding FAT Brands or generate 6.54% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
FAT Brands vs. Soluna Holdings Preferred
Performance |
| Timeline |
| FAT Brands |
| Soluna Holdings Preferred |
FAT Brands and Soluna Holdings Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with FAT Brands and Soluna Holdings
The main advantage of trading using opposite FAT Brands and Soluna Holdings positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if FAT Brands position performs unexpectedly, Soluna Holdings 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 Soluna Holdings will offset losses from the drop in Soluna Holdings' long position.The idea behind FAT Brands and Soluna Holdings Preferred 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.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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