Correlation Between Melrose Industries and Procter Gamble
Can any of the company-specific risk be diversified away by investing in both Melrose Industries and Procter Gamble 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 Melrose Industries and Procter Gamble into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Melrose Industries PLC and Procter Gamble, you can compare the effects of market volatilities on Melrose Industries and Procter Gamble 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 Melrose Industries with a short position of Procter Gamble. Check out your portfolio center. Please also check ongoing floating volatility patterns of Melrose Industries and Procter Gamble.
Diversification Opportunities for Melrose Industries and Procter Gamble
0.44 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Melrose and Procter is 0.44. Overlapping area represents the amount of risk that can be diversified away by holding Melrose Industries PLC and Procter Gamble in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Procter Gamble and Melrose Industries 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 Melrose Industries PLC are associated (or correlated) with Procter Gamble. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Procter Gamble has no effect on the direction of Melrose Industries i.e., Melrose Industries and Procter Gamble go up and down completely randomly.
Pair Corralation between Melrose Industries and Procter Gamble
Assuming the 90 days horizon Melrose Industries PLC is expected to generate 4.53 times more return on investment than Procter Gamble. However, Melrose Industries is 4.53 times more volatile than Procter Gamble. It trades about 0.09 of its potential returns per unit of risk. Procter Gamble is currently generating about -0.01 per unit of risk. If you would invest 573.00 in Melrose Industries PLC on October 6, 2024 and sell it today you would earn a total of 121.00 from holding Melrose Industries PLC or generate 21.12% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Melrose Industries PLC vs. Procter Gamble
Performance |
Timeline |
Melrose Industries PLC |
Procter Gamble |
Melrose Industries and Procter Gamble Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Melrose Industries and Procter Gamble
The main advantage of trading using opposite Melrose Industries and Procter Gamble positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Melrose Industries position performs unexpectedly, Procter Gamble 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 Procter Gamble will offset losses from the drop in Procter Gamble's long position.Melrose Industries vs. Goosehead Insurance | Melrose Industries vs. Willamette Valley Vineyards | Melrose Industries vs. Scandinavian Tobacco Group | Melrose Industries vs. Palomar Holdings |
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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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