Correlation Between Century Insurance and Pak Datacom
Can any of the company-specific risk be diversified away by investing in both Century Insurance and Pak Datacom 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 Century Insurance and Pak Datacom into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Century Insurance and Pak Datacom, you can compare the effects of market volatilities on Century Insurance and Pak Datacom 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 Century Insurance with a short position of Pak Datacom. Check out your portfolio center. Please also check ongoing floating volatility patterns of Century Insurance and Pak Datacom.
Diversification Opportunities for Century Insurance and Pak Datacom
-0.24 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Century and Pak is -0.24. Overlapping area represents the amount of risk that can be diversified away by holding Century Insurance and Pak Datacom in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Pak Datacom and Century 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 Century Insurance are associated (or correlated) with Pak Datacom. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Pak Datacom has no effect on the direction of Century Insurance i.e., Century Insurance and Pak Datacom go up and down completely randomly.
Pair Corralation between Century Insurance and Pak Datacom
Assuming the 90 days trading horizon Century Insurance is expected to generate 0.76 times more return on investment than Pak Datacom. However, Century Insurance is 1.32 times less risky than Pak Datacom. It trades about 0.38 of its potential returns per unit of risk. Pak Datacom is currently generating about 0.17 per unit of risk. If you would invest 3,100 in Century Insurance on August 30, 2024 and sell it today you would earn a total of 620.00 from holding Century Insurance or generate 20.0% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 91.3% |
| Values | Daily Returns |
Century Insurance vs. Pak Datacom
Performance |
| Timeline |
| Century Insurance |
| Pak Datacom |
Century Insurance and Pak Datacom Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Century Insurance and Pak Datacom
The main advantage of trading using opposite Century Insurance and Pak Datacom positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Century Insurance position performs unexpectedly, Pak Datacom 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 Datacom will offset losses from the drop in Pak Datacom's long position.| Century Insurance vs. Quice Food Industries | Century Insurance vs. AKD Hospitality | Century Insurance vs. Ghandhara Automobile | Century Insurance vs. Air Link Communication |
| Pak Datacom vs. Shifa International Hospitals | Pak Datacom vs. Agritech | Pak Datacom vs. Century Insurance | Pak Datacom vs. Habib Insurance |
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 Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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