Correlation Between Shifa International and TPL Insurance
Can any of the company-specific risk be diversified away by investing in both Shifa International 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 Shifa International and TPL Insurance into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Shifa International Hospitals and TPL Insurance, you can compare the effects of market volatilities on Shifa International 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 Shifa International with a short position of TPL Insurance. Check out your portfolio center. Please also check ongoing floating volatility patterns of Shifa International and TPL Insurance.
Diversification Opportunities for Shifa International and TPL Insurance
-0.62 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Shifa and TPL is -0.62. Overlapping area represents the amount of risk that can be diversified away by holding Shifa International Hospitals and TPL Insurance in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on TPL Insurance and Shifa International 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 Shifa International Hospitals 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 Shifa International i.e., Shifa International and TPL Insurance go up and down completely randomly.
Pair Corralation between Shifa International and TPL Insurance
Assuming the 90 days trading horizon Shifa International Hospitals is expected to generate 1.0 times more return on investment than TPL Insurance. However, Shifa International is 1.0 times more volatile than TPL Insurance. It trades about 0.17 of its potential returns per unit of risk. TPL Insurance is currently generating about -0.01 per unit of risk. If you would invest 13,269 in Shifa International Hospitals on December 4, 2024 and sell it today you would earn a total of 29,832 from holding Shifa International Hospitals or generate 224.82% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Weak |
Accuracy | 96.67% |
Values | Daily Returns |
Shifa International Hospitals vs. TPL Insurance
Performance |
Timeline |
Shifa International |
TPL Insurance |
Shifa International and TPL Insurance Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Shifa International and TPL Insurance
The main advantage of trading using opposite Shifa International and TPL Insurance positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Shifa International 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.Shifa International vs. Shaheen Insurance | Shifa International vs. TPL Insurance | Shifa International vs. IBL HealthCare | Shifa International vs. Arpak International Investment |
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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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