Correlation Between Hapag-Lloyd and Dow Jones
Can any of the company-specific risk be diversified away by investing in both Hapag-Lloyd 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 Hapag-Lloyd and Dow Jones into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Hapag Lloyd AG and Dow Jones Industrial, you can compare the effects of market volatilities on Hapag-Lloyd 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 Hapag-Lloyd with a short position of Dow Jones. Check out your portfolio center. Please also check ongoing floating volatility patterns of Hapag-Lloyd and Dow Jones.
Diversification Opportunities for Hapag-Lloyd and Dow Jones
0.14 | Correlation Coefficient |
Average diversification
The 3 months correlation between Hapag-Lloyd and Dow is 0.14. Overlapping area represents the amount of risk that can be diversified away by holding Hapag Lloyd AG 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 Hapag-Lloyd 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 Hapag Lloyd AG 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 Hapag-Lloyd i.e., Hapag-Lloyd and Dow Jones go up and down completely randomly.
Pair Corralation between Hapag-Lloyd and Dow Jones
Assuming the 90 days trading horizon Hapag Lloyd AG is expected to generate 4.5 times more return on investment than Dow Jones. However, Hapag-Lloyd is 4.5 times more volatile than Dow Jones Industrial. It trades about 0.04 of its potential returns per unit of risk. Dow Jones Industrial is currently generating about 0.12 per unit of risk. If you would invest 14,700 in Hapag Lloyd AG on September 18, 2024 and sell it today you would earn a total of 820.00 from holding Hapag Lloyd AG or generate 5.58% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 96.92% |
Values | Daily Returns |
Hapag Lloyd AG vs. Dow Jones Industrial
Performance |
Timeline |
Hapag-Lloyd and Dow Jones Volatility Contrast
Predicted Return Density |
Returns |
Hapag Lloyd AG
Pair trading matchups for Hapag-Lloyd
Dow Jones Industrial
Pair trading matchups for Dow Jones
Pair Trading with Hapag-Lloyd and Dow Jones
The main advantage of trading using opposite Hapag-Lloyd and Dow Jones positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Hapag-Lloyd 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.Hapag-Lloyd vs. Superior Plus Corp | Hapag-Lloyd vs. SIVERS SEMICONDUCTORS AB | Hapag-Lloyd vs. Norsk Hydro ASA | Hapag-Lloyd vs. Reliance Steel Aluminum |
Dow Jones vs. Commonwealth Bank of | Dow Jones vs. AmTrust Financial Services | Dow Jones vs. Forsys Metals Corp | Dow Jones vs. Juniata Valley Financial |
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 Rebalancing module to analyze risk-adjusted returns against different time horizons to find asset-allocation targets.
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