Correlation Between Akanda Corp and NGK Insulators
Can any of the company-specific risk be diversified away by investing in both Akanda Corp and NGK Insulators 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 Akanda Corp and NGK Insulators into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Akanda Corp and NGK Insulators, you can compare the effects of market volatilities on Akanda Corp and NGK Insulators 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 Akanda Corp with a short position of NGK Insulators. Check out your portfolio center. Please also check ongoing floating volatility patterns of Akanda Corp and NGK Insulators.
Diversification Opportunities for Akanda Corp and NGK Insulators
-0.67 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Akanda and NGK is -0.67. Overlapping area represents the amount of risk that can be diversified away by holding Akanda Corp and NGK Insulators in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on NGK Insulators and Akanda Corp 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 Akanda Corp are associated (or correlated) with NGK Insulators. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of NGK Insulators has no effect on the direction of Akanda Corp i.e., Akanda Corp and NGK Insulators go up and down completely randomly.
Pair Corralation between Akanda Corp and NGK Insulators
Given the investment horizon of 90 days Akanda Corp is expected to under-perform the NGK Insulators. In addition to that, Akanda Corp is 4.53 times more volatile than NGK Insulators. It trades about -0.08 of its total potential returns per unit of risk. NGK Insulators is currently generating about 0.02 per unit of volatility. If you would invest 1,246 in NGK Insulators on September 14, 2024 and sell it today you would earn a total of 44.00 from holding NGK Insulators or generate 3.53% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Weak |
| Accuracy | 75.84% |
| Values | Daily Returns |
Akanda Corp vs. NGK Insulators
Performance |
| Timeline |
| Akanda Corp |
| NGK Insulators |
Akanda Corp and NGK Insulators Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Akanda Corp and NGK Insulators
The main advantage of trading using opposite Akanda Corp and NGK Insulators positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Akanda Corp position performs unexpectedly, NGK Insulators 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 NGK Insulators will offset losses from the drop in NGK Insulators' long position.| Akanda Corp vs. Puma Biotechnology | Akanda Corp vs. Iovance Biotherapeutics | Akanda Corp vs. Day One Biopharmaceuticals | Akanda Corp vs. Inozyme Pharma |
| NGK Insulators vs. CECO Environmental Corp | NGK Insulators vs. Akanda Corp | NGK Insulators vs. Newpark Resources | NGK Insulators vs. Everus Construction Group |
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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