Correlation Between Mast Global and USCF Gold
Can any of the company-specific risk be diversified away by investing in both Mast Global and USCF Gold 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 Mast Global and USCF Gold into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Mast Global Battery and USCF Gold Strategy, you can compare the effects of market volatilities on Mast Global and USCF Gold 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 Mast Global with a short position of USCF Gold. Check out your portfolio center. Please also check ongoing floating volatility patterns of Mast Global and USCF Gold.
Diversification Opportunities for Mast Global and USCF Gold
0.64 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Mast and USCF is 0.64. Overlapping area represents the amount of risk that can be diversified away by holding Mast Global Battery and USCF Gold Strategy in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on USCF Gold Strategy and Mast Global 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 Mast Global Battery are associated (or correlated) with USCF Gold. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of USCF Gold Strategy has no effect on the direction of Mast Global i.e., Mast Global and USCF Gold go up and down completely randomly.
Pair Corralation between Mast Global and USCF Gold
Allowing for the 90-day total investment horizon Mast Global Battery is expected to generate 1.2 times more return on investment than USCF Gold. However, Mast Global is 1.2 times more volatile than USCF Gold Strategy. It trades about 0.0 of its potential returns per unit of risk. USCF Gold Strategy is currently generating about -0.11 per unit of risk. If you would invest 2,522 in Mast Global Battery on September 1, 2024 and sell it today you would lose (2.00) from holding Mast Global Battery or give up 0.08% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Mast Global Battery vs. USCF Gold Strategy
Performance |
| Timeline |
| Mast Global Battery |
| USCF Gold Strategy |
Mast Global and USCF Gold Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Mast Global and USCF Gold
The main advantage of trading using opposite Mast Global and USCF Gold positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Mast Global position performs unexpectedly, USCF Gold 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 USCF Gold will offset losses from the drop in USCF Gold's long position.| Mast Global vs. Freedom Day Dividend | Mast Global vs. iShares MSCI China | Mast Global vs. iShares Dividend and | Mast Global vs. SmartETFs Dividend Builder |
| USCF Gold vs. VictoryShares Small Cap | USCF Gold vs. SPDR Gold Shares | USCF Gold vs. First Trust Equity | USCF Gold vs. SPDR Nuveen Municipal |
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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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