Correlation Between Pakistan Petroleum and Aisha Steel
Can any of the company-specific risk be diversified away by investing in both Pakistan Petroleum and Aisha Steel 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 Petroleum and Aisha Steel into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Pakistan Petroleum and Aisha Steel Mills, you can compare the effects of market volatilities on Pakistan Petroleum and Aisha Steel 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 Petroleum with a short position of Aisha Steel. Check out your portfolio center. Please also check ongoing floating volatility patterns of Pakistan Petroleum and Aisha Steel.
Diversification Opportunities for Pakistan Petroleum and Aisha Steel
0.39 | Correlation Coefficient |
Weak diversification
The 3 months correlation between Pakistan and Aisha is 0.39. Overlapping area represents the amount of risk that can be diversified away by holding Pakistan Petroleum and Aisha Steel Mills in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Aisha Steel Mills and Pakistan Petroleum 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 Petroleum are associated (or correlated) with Aisha Steel. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Aisha Steel Mills has no effect on the direction of Pakistan Petroleum i.e., Pakistan Petroleum and Aisha Steel go up and down completely randomly.
Pair Corralation between Pakistan Petroleum and Aisha Steel
Assuming the 90 days trading horizon Pakistan Petroleum is expected to generate 1.07 times less return on investment than Aisha Steel. But when comparing it to its historical volatility, Pakistan Petroleum is 1.84 times less risky than Aisha Steel. It trades about 0.44 of its potential returns per unit of risk. Aisha Steel Mills is currently generating about 0.26 of returns per unit of risk over similar time horizon. If you would invest 697.00 in Aisha Steel Mills on August 24, 2024 and sell it today you would earn a total of 160.00 from holding Aisha Steel Mills or generate 22.96% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Pakistan Petroleum vs. Aisha Steel Mills
Performance |
Timeline |
Pakistan Petroleum |
Aisha Steel Mills |
Pakistan Petroleum and Aisha Steel Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Pakistan Petroleum and Aisha Steel
The main advantage of trading using opposite Pakistan Petroleum and Aisha Steel positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Pakistan Petroleum position performs unexpectedly, Aisha Steel 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 Aisha Steel will offset losses from the drop in Aisha Steel's long position.Pakistan Petroleum vs. East West Insurance | Pakistan Petroleum vs. Pakistan Telecommunication | Pakistan Petroleum vs. Crescent Star Insurance | Pakistan Petroleum vs. WorldCall Telecom |
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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 Headlines Timeline module to stay connected to all market stories and filter out noise. Drill down to analyze hype elasticity.
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