Correlation Between First Majestic and Neo Battery
Can any of the company-specific risk be diversified away by investing in both First Majestic and Neo Battery 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 First Majestic and Neo Battery into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between First Majestic Silver and Neo Battery Materials, you can compare the effects of market volatilities on First Majestic and Neo Battery 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 First Majestic with a short position of Neo Battery. Check out your portfolio center. Please also check ongoing floating volatility patterns of First Majestic and Neo Battery.
Diversification Opportunities for First Majestic and Neo Battery
0.52 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between First and Neo is 0.52. Overlapping area represents the amount of risk that can be diversified away by holding First Majestic Silver and Neo Battery Materials in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Neo Battery Materials and First Majestic 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 First Majestic Silver are associated (or correlated) with Neo Battery. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Neo Battery Materials has no effect on the direction of First Majestic i.e., First Majestic and Neo Battery go up and down completely randomly.
Pair Corralation between First Majestic and Neo Battery
Assuming the 90 days horizon First Majestic Silver is expected to under-perform the Neo Battery. But the stock apears to be less risky and, when comparing its historical volatility, First Majestic Silver is 3.4 times less risky than Neo Battery. The stock trades about -0.35 of its potential returns per unit of risk. The Neo Battery Materials is currently generating about 0.44 of returns per unit of risk over similar time horizon. If you would invest 40.00 in Neo Battery Materials on August 31, 2024 and sell it today you would earn a total of 45.00 from holding Neo Battery Materials or generate 112.5% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
First Majestic Silver vs. Neo Battery Materials
Performance |
| Timeline |
| First Majestic Silver |
| Neo Battery Materials |
First Majestic and Neo Battery Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with First Majestic and Neo Battery
The main advantage of trading using opposite First Majestic and Neo Battery positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if First Majestic position performs unexpectedly, Neo Battery 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 Neo Battery will offset losses from the drop in Neo Battery's long position.| First Majestic vs. Nova Leap Health | First Majestic vs. Leveljump Healthcare Corp | First Majestic vs. Perseus Mining | First Majestic vs. CVS HEALTH CDR |
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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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