Correlation Between Pakistan State and Pakistan Oilfields
Can any of the company-specific risk be diversified away by investing in both Pakistan State and Pakistan Oilfields 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 Pakistan State and Pakistan Oilfields into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Pakistan State Oil and Pakistan Oilfields, you can compare the effects of market volatilities on Pakistan State and Pakistan Oilfields 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 Pakistan State with a short position of Pakistan Oilfields. Check out your portfolio center. Please also check ongoing floating volatility patterns of Pakistan State and Pakistan Oilfields.
Diversification Opportunities for Pakistan State and Pakistan Oilfields
0.75 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Pakistan and Pakistan is 0.75. Overlapping area represents the amount of risk that can be diversified away by holding Pakistan State Oil and Pakistan Oilfields in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Pakistan Oilfields and Pakistan State 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 Pakistan State Oil are associated (or correlated) with Pakistan Oilfields. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Pakistan Oilfields has no effect on the direction of Pakistan State i.e., Pakistan State and Pakistan Oilfields go up and down completely randomly.
Pair Corralation between Pakistan State and Pakistan Oilfields
Assuming the 90 days trading horizon Pakistan State Oil is expected to generate 1.98 times more return on investment than Pakistan Oilfields. However, Pakistan State is 1.98 times more volatile than Pakistan Oilfields. It trades about 0.46 of its potential returns per unit of risk. Pakistan Oilfields is currently generating about 0.11 per unit of risk. If you would invest 30,534 in Pakistan State Oil on October 8, 2024 and sell it today you would earn a total of 13,027 from holding Pakistan State Oil or generate 42.66% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Pakistan State Oil vs. Pakistan Oilfields
Performance |
Timeline |
Pakistan State Oil |
Pakistan Oilfields |
Pakistan State and Pakistan Oilfields Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Pakistan State and Pakistan Oilfields
The main advantage of trading using opposite Pakistan State and Pakistan Oilfields positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Pakistan State position performs unexpectedly, Pakistan Oilfields 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 Pakistan Oilfields will offset losses from the drop in Pakistan Oilfields' long position.Pakistan State vs. Habib Bank | Pakistan State vs. National Bank of | Pakistan State vs. United Bank | Pakistan State vs. MCB Bank |
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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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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