Correlation Between Ceragon Networks and God Bless
Can any of the company-specific risk be diversified away by investing in both Ceragon Networks and God Bless 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 Ceragon Networks and God Bless into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Ceragon Networks and God Bless America, you can compare the effects of market volatilities on Ceragon Networks and God Bless 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 Ceragon Networks with a short position of God Bless. Check out your portfolio center. Please also check ongoing floating volatility patterns of Ceragon Networks and God Bless.
Diversification Opportunities for Ceragon Networks and God Bless
0.6 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Ceragon and God is 0.6. Overlapping area represents the amount of risk that can be diversified away by holding Ceragon Networks and God Bless America in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on God Bless America and Ceragon Networks 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 Ceragon Networks are associated (or correlated) with God Bless. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of God Bless America has no effect on the direction of Ceragon Networks i.e., Ceragon Networks and God Bless go up and down completely randomly.
Pair Corralation between Ceragon Networks and God Bless
Given the investment horizon of 90 days Ceragon Networks is expected to generate 5.25 times more return on investment than God Bless. However, Ceragon Networks is 5.25 times more volatile than God Bless America. It trades about 0.49 of its potential returns per unit of risk. God Bless America is currently generating about 0.35 per unit of risk. If you would invest 242.00 in Ceragon Networks on September 5, 2024 and sell it today you would earn a total of 195.00 from holding Ceragon Networks or generate 80.58% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Ceragon Networks vs. God Bless America
Performance |
| Timeline |
| Ceragon Networks |
| God Bless America |
Ceragon Networks and God Bless Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Ceragon Networks and God Bless
The main advantage of trading using opposite Ceragon Networks and God Bless positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Ceragon Networks position performs unexpectedly, God Bless 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 God Bless will offset losses from the drop in God Bless' long position.| Ceragon Networks vs. Cambium Networks Corp | Ceragon Networks vs. KVH Industries | Ceragon Networks vs. Knowles Cor | Ceragon Networks vs. AudioCodes |
| God Bless vs. Vanguard Total Stock | God Bless vs. SPDR SP 500 | God Bless vs. iShares Core SP | God Bless vs. Vanguard Dividend Appreciation |
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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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