Correlation Between Applied Graphene and G6 Materials
Can any of the company-specific risk be diversified away by investing in both Applied Graphene and G6 Materials 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 Applied Graphene and G6 Materials into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Applied Graphene Materials and G6 Materials Corp, you can compare the effects of market volatilities on Applied Graphene and G6 Materials 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 Applied Graphene with a short position of G6 Materials. Check out your portfolio center. Please also check ongoing floating volatility patterns of Applied Graphene and G6 Materials.
Diversification Opportunities for Applied Graphene and G6 Materials
-0.17 | Correlation Coefficient |
Good diversification
The 3 months correlation between Applied and GPHBF is -0.17. Overlapping area represents the amount of risk that can be diversified away by holding Applied Graphene Materials and G6 Materials Corp in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on G6 Materials Corp and Applied 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 Applied Graphene Materials are associated (or correlated) with G6 Materials. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of G6 Materials Corp has no effect on the direction of Applied Graphene i.e., Applied Graphene and G6 Materials go up and down completely randomly.
Pair Corralation between Applied Graphene and G6 Materials
Assuming the 90 days horizon Applied Graphene Materials is expected to generate 10.16 times more return on investment than G6 Materials. However, Applied Graphene is 10.16 times more volatile than G6 Materials Corp. It trades about 0.08 of its potential returns per unit of risk. G6 Materials Corp is currently generating about 0.01 per unit of risk. If you would invest 1.70 in Applied Graphene Materials on September 1, 2024 and sell it today you would lose (1.69) from holding Applied Graphene Materials or give up 99.41% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 81.75% |
Values | Daily Returns |
Applied Graphene Materials vs. G6 Materials Corp
Performance |
Timeline |
Applied Graphene Mat |
Risk-Adjusted Performance
0 of 100
Weak | Strong |
Very Weak
G6 Materials Corp |
Applied Graphene and G6 Materials Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Applied Graphene and G6 Materials
The main advantage of trading using opposite Applied Graphene and G6 Materials positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Applied Graphene position performs unexpectedly, G6 Materials 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 G6 Materials will offset losses from the drop in G6 Materials' long position.Applied Graphene vs. First Graphene | Applied Graphene vs. Haydale Graphene Industries | Applied Graphene vs. G6 Materials Corp | Applied Graphene vs. Versarien plc |
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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 Backtesting module to avoid under-diversification and over-optimization by backtesting your portfolios.
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