Correlation Between Basic Materials and Energy Services
Can any of the company-specific risk be diversified away by investing in both Basic Materials 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 Basic Materials and Energy Services 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 Services Fund, you can compare the effects of market volatilities on Basic Materials 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 Basic Materials with a short position of Energy Services. Check out your portfolio center. Please also check ongoing floating volatility patterns of Basic Materials and Energy Services.
Diversification Opportunities for Basic Materials and Energy Services
0.43 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Basic and Energy is 0.43. Overlapping area represents the amount of risk that can be diversified away by holding Basic Materials 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 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 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 Basic Materials i.e., Basic Materials and Energy Services go up and down completely randomly.
Pair Corralation between Basic Materials and Energy Services
Assuming the 90 days horizon Basic Materials Fund is expected to under-perform the Energy Services. In addition to that, Basic Materials is 1.05 times more volatile than Energy Services Fund. It trades about -0.11 of its total potential returns per unit of risk. Energy Services Fund is currently generating about -0.01 per unit of volatility. If you would invest 18,591 in Energy Services Fund on November 1, 2024 and sell it today you would lose (438.00) from holding Energy Services Fund or give up 2.36% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Basic Materials Fund vs. Energy Services Fund
Performance |
Timeline |
Basic Materials |
Energy Services |
Basic Materials and Energy Services Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Basic Materials and Energy Services
The main advantage of trading using opposite Basic Materials and Energy Services positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Basic Materials 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.Basic Materials vs. Energy Fund Class | Basic Materials vs. Energy Services Fund | Basic Materials vs. Health Care Fund | Basic Materials vs. Banking Fund Class |
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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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