Correlation Between Elong Power and NVent Electric
Can any of the company-specific risk be diversified away by investing in both Elong Power and NVent Electric 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 Elong Power and NVent Electric into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Elong Power Holding and nVent Electric PLC, you can compare the effects of market volatilities on Elong Power and NVent Electric 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 Elong Power with a short position of NVent Electric. Check out your portfolio center. Please also check ongoing floating volatility patterns of Elong Power and NVent Electric.
Diversification Opportunities for Elong Power and NVent Electric
0.2 | Correlation Coefficient |
Modest diversification
The 3 months correlation between Elong and NVent is 0.2. Overlapping area represents the amount of risk that can be diversified away by holding Elong Power Holding and nVent Electric PLC in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on nVent Electric PLC and Elong Power 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 Elong Power Holding are associated (or correlated) with NVent Electric. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of nVent Electric PLC has no effect on the direction of Elong Power i.e., Elong Power and NVent Electric go up and down completely randomly.
Pair Corralation between Elong Power and NVent Electric
Given the investment horizon of 90 days Elong Power Holding is expected to generate 5.19 times more return on investment than NVent Electric. However, Elong Power is 5.19 times more volatile than nVent Electric PLC. It trades about 0.04 of its potential returns per unit of risk. nVent Electric PLC is currently generating about 0.21 per unit of risk. If you would invest 107.00 in Elong Power Holding on October 22, 2024 and sell it today you would earn a total of 2.00 from holding Elong Power Holding or generate 1.87% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Elong Power Holding vs. nVent Electric PLC
Performance |
| Timeline |
| Elong Power Holding |
| nVent Electric PLC |
Elong Power and NVent Electric Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Elong Power and NVent Electric
The main advantage of trading using opposite Elong Power and NVent Electric positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Elong Power position performs unexpectedly, NVent Electric 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 NVent Electric will offset losses from the drop in NVent Electric's long position.| Elong Power vs. CVR Partners LP | Elong Power vs. Encore Capital Group | Elong Power vs. Glacier Bancorp | Elong Power vs. Barings BDC |
| NVent Electric vs. Hubbell | NVent Electric vs. Advanced Energy Industries | NVent Electric vs. Vertiv Holdings Co | NVent Electric vs. Energizer Holdings |
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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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