Correlation Between Retailors and Libra Insurance
Can any of the company-specific risk be diversified away by investing in both Retailors and Libra Insurance 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 Retailors and Libra Insurance into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Retailors and Libra Insurance, you can compare the effects of market volatilities on Retailors and Libra Insurance 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 Retailors with a short position of Libra Insurance. Check out your portfolio center. Please also check ongoing floating volatility patterns of Retailors and Libra Insurance.
Diversification Opportunities for Retailors and Libra Insurance
0.85 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Retailors and Libra is 0.85. Overlapping area represents the amount of risk that can be diversified away by holding Retailors and Libra Insurance in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Libra Insurance and Retailors 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 Retailors are associated (or correlated) with Libra Insurance. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Libra Insurance has no effect on the direction of Retailors i.e., Retailors and Libra Insurance go up and down completely randomly.
Pair Corralation between Retailors and Libra Insurance
Assuming the 90 days trading horizon Retailors is expected to generate 1.78 times less return on investment than Libra Insurance. But when comparing it to its historical volatility, Retailors is 1.18 times less risky than Libra Insurance. It trades about 0.33 of its potential returns per unit of risk. Libra Insurance is currently generating about 0.5 of returns per unit of risk over similar time horizon. If you would invest 73,046 in Libra Insurance on September 13, 2024 and sell it today you would earn a total of 29,254 from holding Libra Insurance or generate 40.05% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Strong |
| Accuracy | 100.0% |
| Values | Daily Returns |
Retailors vs. Libra Insurance
Performance |
| Timeline |
| Retailors |
| Libra Insurance |
Retailors and Libra Insurance Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Retailors and Libra Insurance
The main advantage of trading using opposite Retailors and Libra Insurance positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Retailors position performs unexpectedly, Libra Insurance 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 Libra Insurance will offset losses from the drop in Libra Insurance's long position.| Retailors vs. Nice | Retailors vs. The Gold Bond | Retailors vs. Bank Leumi Le Israel | Retailors vs. ICL Israel Chemicals |
| Libra Insurance vs. Payment Financial Technologies | Libra Insurance vs. Itay Financial AA | Libra Insurance vs. Blender Financial Technologies | Libra Insurance vs. Bank Leumi Le Israel |
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 Performance Analysis module to check effects of mean-variance optimization against your current asset allocation.
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