Correlation Between UBS Fund and GraniteShares
Can any of the company-specific risk be diversified away by investing in both UBS Fund and GraniteShares 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 UBS Fund and GraniteShares into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between UBS Fund Solutions and GraniteShares 3x Short, you can compare the effects of market volatilities on UBS Fund and GraniteShares 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 UBS Fund with a short position of GraniteShares. Check out your portfolio center. Please also check ongoing floating volatility patterns of UBS Fund and GraniteShares.
Diversification Opportunities for UBS Fund and GraniteShares
-0.87 | Correlation Coefficient |
Pay attention - limited upside
The 3 months correlation between UBS and GraniteShares is -0.87. Overlapping area represents the amount of risk that can be diversified away by holding UBS Fund Solutions and GraniteShares 3x Short in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on GraniteShares 3x Short and UBS Fund 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 UBS Fund Solutions are associated (or correlated) with GraniteShares. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of GraniteShares 3x Short has no effect on the direction of UBS Fund i.e., UBS Fund and GraniteShares go up and down completely randomly.
Pair Corralation between UBS Fund and GraniteShares
Assuming the 90 days trading horizon UBS Fund Solutions is expected to generate 0.09 times more return on investment than GraniteShares. However, UBS Fund Solutions is 11.14 times less risky than GraniteShares. It trades about 0.19 of its potential returns per unit of risk. GraniteShares 3x Short is currently generating about -0.03 per unit of risk. If you would invest 122,870 in UBS Fund Solutions on September 2, 2024 and sell it today you would earn a total of 2,810 from holding UBS Fund Solutions or generate 2.29% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
UBS Fund Solutions vs. GraniteShares 3x Short
Performance |
| Timeline |
| UBS Fund Solutions |
| GraniteShares 3x Short |
UBS Fund and GraniteShares Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with UBS Fund and GraniteShares
The main advantage of trading using opposite UBS Fund and GraniteShares positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if UBS Fund position performs unexpectedly, GraniteShares 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 GraniteShares will offset losses from the drop in GraniteShares' long position.| UBS Fund vs. UBS ETF | UBS Fund vs. UBS ETF plc | UBS Fund vs. UBS ETF plc | UBS Fund vs. UBS Barclays Liquid |
| GraniteShares vs. GraniteShares 3x Short | GraniteShares vs. GraniteShares 3x Long | GraniteShares vs. GraniteShares 3x Long | GraniteShares vs. GraniteShares 1x Short |
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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