Correlation Between Pak Gulf and Habib Insurance
Can any of the company-specific risk be diversified away by investing in both Pak Gulf and Habib 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 Pak Gulf and Habib Insurance into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Pak Gulf Leasing and Habib Insurance, you can compare the effects of market volatilities on Pak Gulf and Habib 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 Pak Gulf with a short position of Habib Insurance. Check out your portfolio center. Please also check ongoing floating volatility patterns of Pak Gulf and Habib Insurance.
Diversification Opportunities for Pak Gulf and Habib Insurance
0.3 | Correlation Coefficient |
Weak diversification
The 3 months correlation between Pak and Habib is 0.3. Overlapping area represents the amount of risk that can be diversified away by holding Pak Gulf Leasing and Habib Insurance in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Habib Insurance and Pak Gulf 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 Pak Gulf Leasing are associated (or correlated) with Habib Insurance. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Habib Insurance has no effect on the direction of Pak Gulf i.e., Pak Gulf and Habib Insurance go up and down completely randomly.
Pair Corralation between Pak Gulf and Habib Insurance
Assuming the 90 days trading horizon Pak Gulf Leasing is expected to under-perform the Habib Insurance. In addition to that, Pak Gulf is 1.97 times more volatile than Habib Insurance. It trades about -0.01 of its total potential returns per unit of risk. Habib Insurance is currently generating about 0.1 per unit of volatility. If you would invest 786.00 in Habib Insurance on December 27, 2024 and sell it today you would earn a total of 136.00 from holding Habib Insurance or generate 17.3% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Pak Gulf Leasing vs. Habib Insurance
Performance |
Timeline |
Pak Gulf Leasing |
Habib Insurance |
Pak Gulf and Habib Insurance Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Pak Gulf and Habib Insurance
The main advantage of trading using opposite Pak Gulf and Habib Insurance positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Pak Gulf position performs unexpectedly, Habib 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 Habib Insurance will offset losses from the drop in Habib Insurance's long position.Pak Gulf vs. Orient Rental Modaraba | Pak Gulf vs. Nimir Industrial Chemical | Pak Gulf vs. Fauji Foods | Pak Gulf vs. Agritech |
Habib Insurance vs. IGI Life Insurance | Habib Insurance vs. Mughal Iron Steel | Habib Insurance vs. Crescent Steel Allied | Habib Insurance vs. Metropolitan Steel Corp |
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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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