Correlation Between Ashtrom and Gilat Satellite
Can any of the company-specific risk be diversified away by investing in both Ashtrom and Gilat Satellite 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 Ashtrom and Gilat Satellite into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Ashtrom Group and Gilat Satellite Networks, you can compare the effects of market volatilities on Ashtrom and Gilat Satellite 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 Ashtrom with a short position of Gilat Satellite. Check out your portfolio center. Please also check ongoing floating volatility patterns of Ashtrom and Gilat Satellite.
Diversification Opportunities for Ashtrom and Gilat Satellite
0.02 | Correlation Coefficient |
Significant diversification
The 3 months correlation between Ashtrom and Gilat is 0.02. Overlapping area represents the amount of risk that can be diversified away by holding Ashtrom Group and Gilat Satellite Networks in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Gilat Satellite Networks and Ashtrom 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 Ashtrom Group are associated (or correlated) with Gilat Satellite. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Gilat Satellite Networks has no effect on the direction of Ashtrom i.e., Ashtrom and Gilat Satellite go up and down completely randomly.
Pair Corralation between Ashtrom and Gilat Satellite
Assuming the 90 days trading horizon Ashtrom is expected to generate 2.61 times less return on investment than Gilat Satellite. In addition to that, Ashtrom is 1.15 times more volatile than Gilat Satellite Networks. It trades about 0.01 of its total potential returns per unit of risk. Gilat Satellite Networks is currently generating about 0.04 per unit of volatility. If you would invest 199,800 in Gilat Satellite Networks on November 2, 2024 and sell it today you would earn a total of 53,500 from holding Gilat Satellite Networks or generate 26.78% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Insignificant |
| Accuracy | 99.74% |
| Values | Daily Returns |
Ashtrom Group vs. Gilat Satellite Networks
Performance |
| Timeline |
| Ashtrom Group |
| Gilat Satellite Networks |
Ashtrom and Gilat Satellite Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Ashtrom and Gilat Satellite
The main advantage of trading using opposite Ashtrom and Gilat Satellite positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Ashtrom position performs unexpectedly, Gilat Satellite 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 Gilat Satellite will offset losses from the drop in Gilat Satellite's long position.| Ashtrom vs. Shikun Binui | Ashtrom vs. Alony Hetz Properties | Ashtrom vs. Amot Investments | Ashtrom vs. Azrieli Group |
| Gilat Satellite vs. Elbit Systems | Gilat Satellite vs. Tower Semiconductor | Gilat Satellite vs. Kamada | Gilat Satellite vs. Delek 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 Price Transformation module to use Price Transformation models to analyze the depth of different equity instruments across global markets.
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