Correlation Between Precious Metals and Energy Services
Can any of the company-specific risk be diversified away by investing in both Precious Metals and Energy Services 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 Precious Metals and Energy Services into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Precious Metals Fund and Energy Services Fund, you can compare the effects of market volatilities on Precious Metals and Energy Services 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 Precious Metals with a short position of Energy Services. Check out your portfolio center. Please also check ongoing floating volatility patterns of Precious Metals and Energy Services.
Diversification Opportunities for Precious Metals and Energy Services
-0.57 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Precious and Energy is -0.57. Overlapping area represents the amount of risk that can be diversified away by holding Precious Metals Fund and Energy Services Fund in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Energy Services and Precious Metals 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 Precious Metals Fund are associated (or correlated) with Energy Services. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Energy Services has no effect on the direction of Precious Metals i.e., Precious Metals and Energy Services go up and down completely randomly.
Pair Corralation between Precious Metals and Energy Services
Assuming the 90 days horizon Precious Metals Fund is expected to generate 1.14 times more return on investment than Energy Services. However, Precious Metals is 1.14 times more volatile than Energy Services Fund. It trades about 0.23 of its potential returns per unit of risk. Energy Services Fund is currently generating about -0.06 per unit of risk. If you would invest 11,178 in Precious Metals Fund on December 30, 2024 and sell it today you would earn a total of 3,331 from holding Precious Metals Fund or generate 29.8% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Precious Metals Fund vs. Energy Services Fund
Performance |
Timeline |
Precious Metals |
Energy Services |
Precious Metals and Energy Services Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Precious Metals and Energy Services
The main advantage of trading using opposite Precious Metals and Energy Services positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Precious Metals position performs unexpectedly, Energy Services 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 Energy Services will offset losses from the drop in Energy Services' long position.Precious Metals vs. Energy Fund Investor | Precious Metals vs. Energy Services Fund | Precious Metals vs. Basic Materials Fund | Precious Metals vs. Health Care Fund |
Energy Services vs. Energy Fund Investor | Energy Services vs. Basic Materials Fund | Energy Services vs. Electronics Fund Investor | Energy Services vs. Health Care Fund |
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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