Correlation Between Basic Materials and Energy Fund
Can any of the company-specific risk be diversified away by investing in both Basic Materials and Energy Fund 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 Basic Materials and Energy Fund into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Basic Materials Fund and Energy Fund Class, you can compare the effects of market volatilities on Basic Materials and Energy Fund 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 Basic Materials with a short position of Energy Fund. Check out your portfolio center. Please also check ongoing floating volatility patterns of Basic Materials and Energy Fund.
Diversification Opportunities for Basic Materials and Energy Fund
0.38 | Correlation Coefficient |
Weak diversification
The 3 months correlation between Basic and Energy is 0.38. Overlapping area represents the amount of risk that can be diversified away by holding Basic Materials Fund and Energy Fund Class in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Energy Fund Class and Basic Materials 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 Basic Materials Fund are associated (or correlated) with Energy Fund. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Energy Fund Class has no effect on the direction of Basic Materials i.e., Basic Materials and Energy Fund go up and down completely randomly.
Pair Corralation between Basic Materials and Energy Fund
Assuming the 90 days horizon Basic Materials Fund is expected to generate 0.86 times more return on investment than Energy Fund. However, Basic Materials Fund is 1.16 times less risky than Energy Fund. It trades about 0.04 of its potential returns per unit of risk. Energy Fund Class is currently generating about 0.0 per unit of risk. If you would invest 8,683 in Basic Materials Fund on August 28, 2024 and sell it today you would earn a total of 411.00 from holding Basic Materials Fund or generate 4.73% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Basic Materials Fund vs. Energy Fund Class
Performance |
Timeline |
Basic Materials |
Energy Fund Class |
Basic Materials and Energy Fund Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Basic Materials and Energy Fund
The main advantage of trading using opposite Basic Materials and Energy Fund positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Basic Materials position performs unexpectedly, Energy Fund 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 Fund will offset losses from the drop in Energy Fund's long position.Basic Materials vs. Energy Fund Investor | Basic Materials vs. Energy Services Fund | Basic Materials vs. Health Care Fund | Basic Materials vs. Banking Fund Investor |
Energy Fund vs. Franklin Natural Resources | Energy Fund vs. Gmo Resources | Energy Fund vs. World Energy Fund | Energy Fund vs. Fidelity Advisor Energy |
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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