Correlation Between Ceragon Networks and Sif Holding
Can any of the company-specific risk be diversified away by investing in both Ceragon Networks and Sif Holding 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 Sif Holding into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Ceragon Networks and Sif Holding NV, you can compare the effects of market volatilities on Ceragon Networks and Sif Holding 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 Sif Holding. Check out your portfolio center. Please also check ongoing floating volatility patterns of Ceragon Networks and Sif Holding.
Diversification Opportunities for Ceragon Networks and Sif Holding
-0.58 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Ceragon and Sif is -0.58. Overlapping area represents the amount of risk that can be diversified away by holding Ceragon Networks and Sif Holding NV in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Sif Holding NV 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 Sif Holding. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Sif Holding NV has no effect on the direction of Ceragon Networks i.e., Ceragon Networks and Sif Holding go up and down completely randomly.
Pair Corralation between Ceragon Networks and Sif Holding
Given the investment horizon of 90 days Ceragon Networks is expected to generate 1.5 times more return on investment than Sif Holding. However, Ceragon Networks is 1.5 times more volatile than Sif Holding NV. It trades about 0.07 of its potential returns per unit of risk. Sif Holding NV is currently generating about 0.02 per unit of risk. If you would invest 193.00 in Ceragon Networks on September 12, 2024 and sell it today you would earn a total of 257.00 from holding Ceragon Networks or generate 133.16% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Very Weak |
| Accuracy | 98.02% |
| Values | Daily Returns |
Ceragon Networks vs. Sif Holding NV
Performance |
| Timeline |
| Ceragon Networks |
| Sif Holding NV |
Ceragon Networks and Sif Holding Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Ceragon Networks and Sif Holding
The main advantage of trading using opposite Ceragon Networks and Sif Holding positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Ceragon Networks position performs unexpectedly, Sif Holding 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 Sif Holding will offset losses from the drop in Sif Holding's long position.| Ceragon Networks vs. Cambium Networks Corp | Ceragon Networks vs. KVH Industries | Ceragon Networks vs. Knowles Cor | Ceragon Networks vs. AudioCodes |
| Sif Holding vs. Kendrion NV | Sif Holding vs. NV Nederlandsche Apparatenfabriek | Sif Holding vs. Brunel International NV | Sif Holding vs. TKH Group NV |
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 Equity Valuation module to check real value of public entities based on technical and fundamental data.
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