Correlation Between Unilever Pakistan and Dow Jones
Can any of the company-specific risk be diversified away by investing in both Unilever Pakistan and Dow Jones 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 Unilever Pakistan and Dow Jones into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Unilever Pakistan Foods and Dow Jones Industrial, you can compare the effects of market volatilities on Unilever Pakistan and Dow Jones 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 Unilever Pakistan with a short position of Dow Jones. Check out your portfolio center. Please also check ongoing floating volatility patterns of Unilever Pakistan and Dow Jones.
Diversification Opportunities for Unilever Pakistan and Dow Jones
0.02 | Correlation Coefficient |
Significant diversification
The 3 months correlation between Unilever and Dow is 0.02. Overlapping area represents the amount of risk that can be diversified away by holding Unilever Pakistan Foods and Dow Jones Industrial in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Dow Jones Industrial and Unilever Pakistan 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 Unilever Pakistan Foods are associated (or correlated) with Dow Jones. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Dow Jones Industrial has no effect on the direction of Unilever Pakistan i.e., Unilever Pakistan and Dow Jones go up and down completely randomly.
Pair Corralation between Unilever Pakistan and Dow Jones
Assuming the 90 days trading horizon Unilever Pakistan Foods is expected to generate 1.18 times more return on investment than Dow Jones. However, Unilever Pakistan is 1.18 times more volatile than Dow Jones Industrial. It trades about 0.21 of its potential returns per unit of risk. Dow Jones Industrial is currently generating about -0.03 per unit of risk. If you would invest 2,076,741 in Unilever Pakistan Foods on December 25, 2024 and sell it today you would earn a total of 275,809 from holding Unilever Pakistan Foods or generate 13.28% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 98.36% |
Values | Daily Returns |
Unilever Pakistan Foods vs. Dow Jones Industrial
Performance |
Timeline |
Unilever Pakistan and Dow Jones Volatility Contrast
Predicted Return Density |
Returns |
Unilever Pakistan Foods
Pair trading matchups for Unilever Pakistan
Dow Jones Industrial
Pair trading matchups for Dow Jones
Pair Trading with Unilever Pakistan and Dow Jones
The main advantage of trading using opposite Unilever Pakistan and Dow Jones positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Unilever Pakistan position performs unexpectedly, Dow Jones 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 Dow Jones will offset losses from the drop in Dow Jones' long position.Unilever Pakistan vs. Apna Microfinance Bank | Unilever Pakistan vs. Habib Insurance | Unilever Pakistan vs. Standard Chartered Bank | Unilever Pakistan vs. Silkbank |
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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 Price Transformation module to use Price Transformation models to analyze the depth of different equity instruments across global markets.
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