Correlation Between NVIDIA and Medical Properties
Can any of the company-specific risk be diversified away by investing in both NVIDIA and Medical Properties 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 NVIDIA and Medical Properties into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between NVIDIA and Medical Properties Trust, you can compare the effects of market volatilities on NVIDIA and Medical Properties 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 NVIDIA with a short position of Medical Properties. Check out your portfolio center. Please also check ongoing floating volatility patterns of NVIDIA and Medical Properties.
Diversification Opportunities for NVIDIA and Medical Properties
-0.51 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between NVIDIA and Medical is -0.51. Overlapping area represents the amount of risk that can be diversified away by holding NVIDIA and Medical Properties Trust in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Medical Properties Trust and NVIDIA 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 NVIDIA are associated (or correlated) with Medical Properties. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Medical Properties Trust has no effect on the direction of NVIDIA i.e., NVIDIA and Medical Properties go up and down completely randomly.
Pair Corralation between NVIDIA and Medical Properties
Given the investment horizon of 90 days NVIDIA is expected to generate 0.65 times more return on investment than Medical Properties. However, NVIDIA is 1.53 times less risky than Medical Properties. It trades about 0.11 of its potential returns per unit of risk. Medical Properties Trust is currently generating about -0.12 per unit of risk. If you would invest 13,956 in NVIDIA on August 24, 2024 and sell it today you would earn a total of 711.00 from holding NVIDIA or generate 5.09% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
NVIDIA vs. Medical Properties Trust
Performance |
| Timeline |
| NVIDIA |
| Medical Properties Trust |
NVIDIA and Medical Properties Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with NVIDIA and Medical Properties
The main advantage of trading using opposite NVIDIA and Medical Properties positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if NVIDIA position performs unexpectedly, Medical Properties 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 Medical Properties will offset losses from the drop in Medical Properties' long position.| NVIDIA vs. Intel | NVIDIA vs. Taiwan Semiconductor Manufacturing | NVIDIA vs. Marvell Technology Group | NVIDIA vs. Micron Technology |
| Medical Properties vs. Healthcare Realty Trust | Medical Properties vs. Welltower | Medical Properties vs. American Healthcare REIT, | Medical Properties vs. Diversified Healthcare Trust |
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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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