Correlation Between NEM INSURANCE and Dow Jones
Can any of the company-specific risk be diversified away by investing in both NEM INSURANCE 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 NEM INSURANCE and Dow Jones into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between NEM INSURANCE PLC and Dow Jones Industrial, you can compare the effects of market volatilities on NEM INSURANCE 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 NEM INSURANCE with a short position of Dow Jones. Check out your portfolio center. Please also check ongoing floating volatility patterns of NEM INSURANCE and Dow Jones.
Diversification Opportunities for NEM INSURANCE and Dow Jones
0.54 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between NEM and Dow is 0.54. Overlapping area represents the amount of risk that can be diversified away by holding NEM INSURANCE PLC 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 NEM INSURANCE 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 NEM INSURANCE PLC 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 NEM INSURANCE i.e., NEM INSURANCE and Dow Jones go up and down completely randomly.
Pair Corralation between NEM INSURANCE and Dow Jones
Assuming the 90 days trading horizon NEM INSURANCE PLC is expected to generate 4.28 times more return on investment than Dow Jones. However, NEM INSURANCE is 4.28 times more volatile than Dow Jones Industrial. It trades about 0.2 of its potential returns per unit of risk. Dow Jones Industrial is currently generating about 0.14 per unit of risk. If you would invest 750.00 in NEM INSURANCE PLC on September 13, 2024 and sell it today you would earn a total of 320.00 from holding NEM INSURANCE PLC or generate 42.67% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 98.41% |
Values | Daily Returns |
NEM INSURANCE PLC vs. Dow Jones Industrial
Performance |
Timeline |
NEM INSURANCE and Dow Jones Volatility Contrast
Predicted Return Density |
Returns |
NEM INSURANCE PLC
Pair trading matchups for NEM INSURANCE
Dow Jones Industrial
Pair trading matchups for Dow Jones
Pair Trading with NEM INSURANCE and Dow Jones
The main advantage of trading using opposite NEM INSURANCE and Dow Jones positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if NEM INSURANCE 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.NEM INSURANCE vs. GUINEA INSURANCE PLC | NEM INSURANCE vs. SECURE ELECTRONIC TECHNOLOGY | NEM INSURANCE vs. VFD GROUP | NEM INSURANCE vs. IKEJA HOTELS PLC |
Dow Jones vs. ChampionX | Dow Jones vs. Highway Holdings Limited | Dow Jones vs. Westinghouse Air Brake | Dow Jones vs. Cementos Pacasmayo SAA |
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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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