Correlation Between Dynagas LNG and Delek Logistics
Can any of the company-specific risk be diversified away by investing in both Dynagas LNG and Delek Logistics 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 Dynagas LNG and Delek Logistics into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Dynagas LNG Partners and Delek Logistics Partners, you can compare the effects of market volatilities on Dynagas LNG and Delek Logistics 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 Dynagas LNG with a short position of Delek Logistics. Check out your portfolio center. Please also check ongoing floating volatility patterns of Dynagas LNG and Delek Logistics.
Diversification Opportunities for Dynagas LNG and Delek Logistics
-0.23 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Dynagas and Delek is -0.23. Overlapping area represents the amount of risk that can be diversified away by holding Dynagas LNG Partners and Delek Logistics Partners in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Delek Logistics Partners and Dynagas LNG 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 Dynagas LNG Partners are associated (or correlated) with Delek Logistics. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Delek Logistics Partners has no effect on the direction of Dynagas LNG i.e., Dynagas LNG and Delek Logistics go up and down completely randomly.
Pair Corralation between Dynagas LNG and Delek Logistics
Given the investment horizon of 90 days Dynagas LNG Partners is expected to generate 3.1 times more return on investment than Delek Logistics. However, Dynagas LNG is 3.1 times more volatile than Delek Logistics Partners. It trades about 0.26 of its potential returns per unit of risk. Delek Logistics Partners is currently generating about 0.02 per unit of risk. If you would invest 288.00 in Dynagas LNG Partners on February 28, 2024 and sell it today you would earn a total of 110.00 from holding Dynagas LNG Partners or generate 38.19% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Dynagas LNG Partners vs. Delek Logistics Partners
Performance |
Timeline |
Dynagas LNG Partners |
Delek Logistics Partners |
Dynagas LNG and Delek Logistics Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Dynagas LNG and Delek Logistics
The main advantage of trading using opposite Dynagas LNG and Delek Logistics positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Dynagas LNG position performs unexpectedly, Delek Logistics 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 Delek Logistics will offset losses from the drop in Delek Logistics' long position.Dynagas LNG vs. Genesis Energy LP | Dynagas LNG vs. Western Midstream Partners | Dynagas LNG vs. Hess Midstream Partners | Dynagas LNG vs. Enterprise Products Partners |
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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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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