Correlation Between ZEN Graphene and Brixton Metals
Can any of the company-specific risk be diversified away by investing in both ZEN Graphene and Brixton Metals 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 ZEN Graphene and Brixton Metals into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between ZEN Graphene Solutions and Brixton Metals, you can compare the effects of market volatilities on ZEN Graphene and Brixton Metals 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 ZEN Graphene with a short position of Brixton Metals. Check out your portfolio center. Please also check ongoing floating volatility patterns of ZEN Graphene and Brixton Metals.
Diversification Opportunities for ZEN Graphene and Brixton Metals
0.13 | Correlation Coefficient |
Average diversification
The 3 months correlation between ZEN and Brixton is 0.13. Overlapping area represents the amount of risk that can be diversified away by holding ZEN Graphene Solutions and Brixton Metals in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Brixton Metals and ZEN Graphene 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 ZEN Graphene Solutions are associated (or correlated) with Brixton Metals. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Brixton Metals has no effect on the direction of ZEN Graphene i.e., ZEN Graphene and Brixton Metals go up and down completely randomly.
Pair Corralation between ZEN Graphene and Brixton Metals
Given the investment horizon of 90 days ZEN Graphene Solutions is expected to under-perform the Brixton Metals. But the stock apears to be less risky and, when comparing its historical volatility, ZEN Graphene Solutions is 1.09 times less risky than Brixton Metals. The stock trades about -0.07 of its potential returns per unit of risk. The Brixton Metals is currently generating about 0.12 of returns per unit of risk over similar time horizon. If you would invest 4.70 in Brixton Metals on November 28, 2024 and sell it today you would earn a total of 1.60 from holding Brixton Metals or generate 34.04% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
ZEN Graphene Solutions vs. Brixton Metals
Performance |
Timeline |
ZEN Graphene Solutions |
Brixton Metals |
ZEN Graphene and Brixton Metals Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with ZEN Graphene and Brixton Metals
The main advantage of trading using opposite ZEN Graphene and Brixton Metals positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if ZEN Graphene position performs unexpectedly, Brixton Metals 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 Brixton Metals will offset losses from the drop in Brixton Metals' long position.ZEN Graphene vs. Milestone Scientific | ZEN Graphene vs. Pro Dex | ZEN Graphene vs. Top Glove | ZEN Graphene vs. Precision Optics, |
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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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