Correlation Between Real Brands and Global Hemp
Can any of the company-specific risk be diversified away by investing in both Real Brands and Global Hemp 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 Real Brands and Global Hemp into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Real Brands and Global Hemp Group, you can compare the effects of market volatilities on Real Brands and Global Hemp 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 Real Brands with a short position of Global Hemp. Check out your portfolio center. Please also check ongoing floating volatility patterns of Real Brands and Global Hemp.
Diversification Opportunities for Real Brands and Global Hemp
0.3 | Correlation Coefficient |
Weak diversification
The 3 months correlation between Real and Global is 0.3. Overlapping area represents the amount of risk that can be diversified away by holding Real Brands and Global Hemp Group in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Global Hemp Group and Real 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 Real Brands are associated (or correlated) with Global Hemp. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Global Hemp Group has no effect on the direction of Real Brands i.e., Real Brands and Global Hemp go up and down completely randomly.
Pair Corralation between Real Brands and Global Hemp
Given the investment horizon of 90 days Real Brands is expected to generate 3.09 times less return on investment than Global Hemp. But when comparing it to its historical volatility, Real Brands is 1.6 times less risky than Global Hemp. It trades about 0.07 of its potential returns per unit of risk. Global Hemp Group is currently generating about 0.13 of returns per unit of risk over similar time horizon. If you would invest 2.60 in Global Hemp Group on August 29, 2024 and sell it today you would lose (1.14) from holding Global Hemp Group or give up 43.85% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 99.52% |
| Values | Daily Returns |
Real Brands vs. Global Hemp Group
Performance |
| Timeline |
| Real Brands |
| Global Hemp Group |
Real Brands and Global Hemp Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Real Brands and Global Hemp
The main advantage of trading using opposite Real Brands and Global Hemp positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Real Brands position performs unexpectedly, Global Hemp 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 Global Hemp will offset losses from the drop in Global Hemp's long position.| Real Brands vs. American Premium Water | Real Brands vs. Puration | Real Brands vs. Kona Gold Solutions | Real Brands vs. Leafbuyer Technologies |
| Global Hemp vs. Greater Cannabis | Global Hemp vs. Cannabis Suisse Corp | Global Hemp vs. Maple Leaf Green | Global Hemp vs. Mc Endvrs |
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 Rebalancing module to analyze risk-adjusted returns against different time horizons to find asset-allocation targets.
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