Correlation Between K Electric and National Refinery
Can any of the company-specific risk be diversified away by investing in both K Electric and National Refinery 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 K Electric and National Refinery into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between K Electric and National Refinery, you can compare the effects of market volatilities on K Electric and National Refinery 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 K Electric with a short position of National Refinery. Check out your portfolio center. Please also check ongoing floating volatility patterns of K Electric and National Refinery.
Diversification Opportunities for K Electric and National Refinery
0.87 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between KEL and National is 0.87. Overlapping area represents the amount of risk that can be diversified away by holding K Electric and National Refinery in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on National Refinery and K Electric 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 K Electric are associated (or correlated) with National Refinery. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of National Refinery has no effect on the direction of K Electric i.e., K Electric and National Refinery go up and down completely randomly.
Pair Corralation between K Electric and National Refinery
Assuming the 90 days trading horizon K Electric is expected to under-perform the National Refinery. In addition to that, K Electric is 1.07 times more volatile than National Refinery. It trades about -0.11 of its total potential returns per unit of risk. National Refinery is currently generating about -0.07 per unit of volatility. If you would invest 29,649 in National Refinery on December 30, 2024 and sell it today you would lose (3,944) from holding National Refinery or give up 13.3% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
K Electric vs. National Refinery
Performance |
Timeline |
K Electric |
National Refinery |
K Electric and National Refinery Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with K Electric and National Refinery
The main advantage of trading using opposite K Electric and National Refinery positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if K Electric position performs unexpectedly, National Refinery 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 National Refinery will offset losses from the drop in National Refinery's long position.K Electric vs. Pakistan Synthetics | K Electric vs. TPL Insurance | K Electric vs. Air Link Communication | K Electric vs. Adamjee Insurance |
National Refinery vs. Mughal Iron Steel | National Refinery vs. Amreli Steels | National Refinery vs. Atlas Insurance | National Refinery vs. Askari Bank |
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 Technical Analysis module to check basic technical indicators and analysis based on most latest market data.
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