Correlation Between Habib Insurance and Pak Gulf
Can any of the company-specific risk be diversified away by investing in both Habib Insurance and Pak Gulf 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 Habib Insurance and Pak Gulf into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Habib Insurance and Pak Gulf Leasing, you can compare the effects of market volatilities on Habib Insurance and Pak Gulf 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 Habib Insurance with a short position of Pak Gulf. Check out your portfolio center. Please also check ongoing floating volatility patterns of Habib Insurance and Pak Gulf.
Diversification Opportunities for Habib Insurance and Pak Gulf
0.22 | Correlation Coefficient |
Modest diversification
The 3 months correlation between Habib and Pak is 0.22. Overlapping area represents the amount of risk that can be diversified away by holding Habib Insurance and Pak Gulf Leasing in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Pak Gulf Leasing and Habib Insurance 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 Habib Insurance are associated (or correlated) with Pak Gulf. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Pak Gulf Leasing has no effect on the direction of Habib Insurance i.e., Habib Insurance and Pak Gulf go up and down completely randomly.
Pair Corralation between Habib Insurance and Pak Gulf
Assuming the 90 days trading horizon Habib Insurance is expected to generate 3.31 times less return on investment than Pak Gulf. But when comparing it to its historical volatility, Habib Insurance is 1.56 times less risky than Pak Gulf. It trades about 0.1 of its potential returns per unit of risk. Pak Gulf Leasing is currently generating about 0.21 of returns per unit of risk over similar time horizon. If you would invest 865.00 in Pak Gulf Leasing on August 28, 2024 and sell it today you would earn a total of 206.00 from holding Pak Gulf Leasing or generate 23.82% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 80.95% |
| Values | Daily Returns |
Habib Insurance vs. Pak Gulf Leasing
Performance |
| Timeline |
| Habib Insurance |
| Pak Gulf Leasing |
Habib Insurance and Pak Gulf Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Habib Insurance and Pak Gulf
The main advantage of trading using opposite Habib Insurance and Pak Gulf positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Habib Insurance position performs unexpectedly, Pak Gulf 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 Pak Gulf will offset losses from the drop in Pak Gulf's long position.| Habib Insurance vs. MCB Investment Manag | Habib Insurance vs. AKD Hospitality | Habib Insurance vs. Air Link Communication | Habib Insurance vs. IBL HealthCare |
| Pak Gulf vs. Masood Textile Mills | Pak Gulf vs. Fauji Foods | Pak Gulf vs. KSB Pumps | Pak Gulf vs. Mari Petroleum |
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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