Correlation Between CPI Aerostructures and Austal
Can any of the company-specific risk be diversified away by investing in both CPI Aerostructures and Austal 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 CPI Aerostructures and Austal into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between CPI Aerostructures and Austal Limited, you can compare the effects of market volatilities on CPI Aerostructures and Austal 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 CPI Aerostructures with a short position of Austal. Check out your portfolio center. Please also check ongoing floating volatility patterns of CPI Aerostructures and Austal.
Diversification Opportunities for CPI Aerostructures and Austal
0.09 | Correlation Coefficient |
Significant diversification
The 3 months correlation between CPI and Austal is 0.09. Overlapping area represents the amount of risk that can be diversified away by holding CPI Aerostructures and Austal Limited in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Austal Limited and CPI Aerostructures 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 CPI Aerostructures are associated (or correlated) with Austal. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Austal Limited has no effect on the direction of CPI Aerostructures i.e., CPI Aerostructures and Austal go up and down completely randomly.
Pair Corralation between CPI Aerostructures and Austal
Considering the 90-day investment horizon CPI Aerostructures is expected to generate 0.87 times more return on investment than Austal. However, CPI Aerostructures is 1.16 times less risky than Austal. It trades about 0.08 of its potential returns per unit of risk. Austal Limited is currently generating about 0.07 per unit of risk. If you would invest 280.00 in CPI Aerostructures on November 3, 2024 and sell it today you would earn a total of 200.00 from holding CPI Aerostructures or generate 71.43% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Insignificant |
| Accuracy | 99.6% |
| Values | Daily Returns |
CPI Aerostructures vs. Austal Limited
Performance |
| Timeline |
| CPI Aerostructures |
| Austal Limited |
CPI Aerostructures and Austal Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with CPI Aerostructures and Austal
The main advantage of trading using opposite CPI Aerostructures and Austal positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if CPI Aerostructures position performs unexpectedly, Austal 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 Austal will offset losses from the drop in Austal's long position.| CPI Aerostructures vs. Ducommun Incorporated | CPI Aerostructures vs. SIFCO Industries | CPI Aerostructures vs. Innovative Solutions and | CPI Aerostructures vs. Air Industries Group |
| Austal vs. 808 Renewable Energy | Austal vs. Sky Harbour Group | Austal vs. VirTra Inc | Austal vs. Firan Technology 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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