Correlation Between Electra Battery and Frontier Lithium
Can any of the company-specific risk be diversified away by investing in both Electra Battery and Frontier Lithium 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 Electra Battery and Frontier Lithium into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Electra Battery Materials and Frontier Lithium, you can compare the effects of market volatilities on Electra Battery and Frontier Lithium 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 Electra Battery with a short position of Frontier Lithium. Check out your portfolio center. Please also check ongoing floating volatility patterns of Electra Battery and Frontier Lithium.
Diversification Opportunities for Electra Battery and Frontier Lithium
0.71 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Electra and Frontier is 0.71. Overlapping area represents the amount of risk that can be diversified away by holding Electra Battery Materials and Frontier Lithium in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Frontier Lithium and Electra Battery 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 Electra Battery Materials are associated (or correlated) with Frontier Lithium. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Frontier Lithium has no effect on the direction of Electra Battery i.e., Electra Battery and Frontier Lithium go up and down completely randomly.
Pair Corralation between Electra Battery and Frontier Lithium
Given the investment horizon of 90 days Electra Battery Materials is expected to generate 1.1 times more return on investment than Frontier Lithium. However, Electra Battery is 1.1 times more volatile than Frontier Lithium. It trades about -0.1 of its potential returns per unit of risk. Frontier Lithium is currently generating about -0.14 per unit of risk. If you would invest 55.00 in Electra Battery Materials on August 24, 2024 and sell it today you would lose (4.60) from holding Electra Battery Materials or give up 8.36% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Electra Battery Materials vs. Frontier Lithium
Performance |
Timeline |
Electra Battery Materials |
Frontier Lithium |
Electra Battery and Frontier Lithium Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Electra Battery and Frontier Lithium
The main advantage of trading using opposite Electra Battery and Frontier Lithium positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Electra Battery position performs unexpectedly, Frontier Lithium 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 Frontier Lithium will offset losses from the drop in Frontier Lithium's long position.Electra Battery vs. Morningstar Unconstrained Allocation | Electra Battery vs. Knife River | Electra Battery vs. SEI Investments | Electra Battery vs. Goosehead Insurance |
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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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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