Correlation Between Cameo Communications and Shan Loong
Can any of the company-specific risk be diversified away by investing in both Cameo Communications and Shan Loong 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 Cameo Communications and Shan Loong into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Cameo Communications and Shan Loong Transportation Co, you can compare the effects of market volatilities on Cameo Communications and Shan Loong 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 Cameo Communications with a short position of Shan Loong. Check out your portfolio center. Please also check ongoing floating volatility patterns of Cameo Communications and Shan Loong.
Diversification Opportunities for Cameo Communications and Shan Loong
-0.17 | Correlation Coefficient |
Good diversification
The 3 months correlation between Cameo and Shan is -0.17. Overlapping area represents the amount of risk that can be diversified away by holding Cameo Communications and Shan Loong Transportation Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Shan Loong Transport and Cameo Communications 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 Cameo Communications are associated (or correlated) with Shan Loong. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Shan Loong Transport has no effect on the direction of Cameo Communications i.e., Cameo Communications and Shan Loong go up and down completely randomly.
Pair Corralation between Cameo Communications and Shan Loong
Assuming the 90 days trading horizon Cameo Communications is expected to generate 3.13 times more return on investment than Shan Loong. However, Cameo Communications is 3.13 times more volatile than Shan Loong Transportation Co. It trades about 0.02 of its potential returns per unit of risk. Shan Loong Transportation Co is currently generating about -0.42 per unit of risk. If you would invest 1,120 in Cameo Communications on October 9, 2024 and sell it today you would earn a total of 0.00 from holding Cameo Communications or generate 0.0% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Cameo Communications vs. Shan Loong Transportation Co
Performance |
Timeline |
Cameo Communications |
Shan Loong Transport |
Cameo Communications and Shan Loong Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Cameo Communications and Shan Loong
The main advantage of trading using opposite Cameo Communications and Shan Loong positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Cameo Communications position performs unexpectedly, Shan Loong 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 Shan Loong will offset losses from the drop in Shan Loong's long position.Cameo Communications vs. Gemtek Technology Co | Cameo Communications vs. CyberTAN Technology | Cameo Communications vs. Alpha Networks | Cameo Communications vs. D Link Corp |
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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 Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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