Correlation Between Habib Insurance and TPL Insurance
Can any of the company-specific risk be diversified away by investing in both Habib Insurance and TPL 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 Habib Insurance and TPL Insurance into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Habib Insurance and TPL Insurance, you can compare the effects of market volatilities on Habib Insurance and TPL 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 Habib Insurance with a short position of TPL Insurance. Check out your portfolio center. Please also check ongoing floating volatility patterns of Habib Insurance and TPL Insurance.
Diversification Opportunities for Habib Insurance and TPL Insurance
-0.43 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Habib and TPL is -0.43. Overlapping area represents the amount of risk that can be diversified away by holding Habib Insurance and TPL Insurance in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on TPL Insurance 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 TPL Insurance. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of TPL Insurance has no effect on the direction of Habib Insurance i.e., Habib Insurance and TPL Insurance go up and down completely randomly.
Pair Corralation between Habib Insurance and TPL Insurance
Assuming the 90 days trading horizon Habib Insurance is expected to generate 1.24 times more return on investment than TPL Insurance. However, Habib Insurance is 1.24 times more volatile than TPL Insurance. It trades about 0.07 of its potential returns per unit of risk. TPL Insurance is currently generating about -0.13 per unit of risk. If you would invest 841.00 in Habib Insurance on December 29, 2024 and sell it today you would earn a total of 86.00 from holding Habib Insurance or generate 10.23% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 98.41% |
Values | Daily Returns |
Habib Insurance vs. TPL Insurance
Performance |
Timeline |
Habib Insurance |
TPL Insurance |
Habib Insurance and TPL Insurance Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Habib Insurance and TPL Insurance
The main advantage of trading using opposite Habib Insurance and TPL Insurance positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Habib Insurance position performs unexpectedly, TPL 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 TPL Insurance will offset losses from the drop in TPL Insurance's long position.Habib Insurance vs. Aisha Steel Mills | Habib Insurance vs. Honda Atlas Cars | Habib Insurance vs. Ghandhara Automobile | Habib Insurance vs. Air Link Communication |
TPL Insurance vs. Masood Textile Mills | TPL Insurance vs. Fauji Foods | TPL Insurance vs. KSB Pumps | TPL Insurance 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 Portfolio Backtesting module to avoid under-diversification and over-optimization by backtesting your portfolios.
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