Correlation Between Direct Line and Jutal Offshore
Can any of the company-specific risk be diversified away by investing in both Direct Line and Jutal Offshore 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 Direct Line and Jutal Offshore into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Direct Line Insurance and Jutal Offshore Oil, you can compare the effects of market volatilities on Direct Line and Jutal Offshore 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 Direct Line with a short position of Jutal Offshore. Check out your portfolio center. Please also check ongoing floating volatility patterns of Direct Line and Jutal Offshore.
Diversification Opportunities for Direct Line and Jutal Offshore
-0.02 | Correlation Coefficient |
Good diversification
The 3 months correlation between Direct and Jutal is -0.02. Overlapping area represents the amount of risk that can be diversified away by holding Direct Line Insurance and Jutal Offshore Oil in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Jutal Offshore Oil and Direct Line 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 Direct Line Insurance are associated (or correlated) with Jutal Offshore. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Jutal Offshore Oil has no effect on the direction of Direct Line i.e., Direct Line and Jutal Offshore go up and down completely randomly.
Pair Corralation between Direct Line and Jutal Offshore
Assuming the 90 days horizon Direct Line Insurance is expected to generate 122.49 times more return on investment than Jutal Offshore. However, Direct Line is 122.49 times more volatile than Jutal Offshore Oil. It trades about 0.35 of its potential returns per unit of risk. Jutal Offshore Oil is currently generating about -0.21 per unit of risk. If you would invest 775.00 in Direct Line Insurance on September 21, 2024 and sell it today you would earn a total of 443.00 from holding Direct Line Insurance or generate 57.16% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 95.45% |
Values | Daily Returns |
Direct Line Insurance vs. Jutal Offshore Oil
Performance |
Timeline |
Direct Line Insurance |
Jutal Offshore Oil |
Direct Line and Jutal Offshore Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Direct Line and Jutal Offshore
The main advantage of trading using opposite Direct Line and Jutal Offshore positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Direct Line position performs unexpectedly, Jutal Offshore 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 Jutal Offshore will offset losses from the drop in Jutal Offshore's long position.Direct Line vs. Chipotle Mexican Grill | Direct Line vs. Kura Sushi USA | Direct Line vs. Playtika Holding Corp | Direct Line vs. Emerson Radio |
Jutal Offshore vs. GameStop Corp | Jutal Offshore vs. Direct Line Insurance | Jutal Offshore vs. SunOpta | Jutal Offshore vs. Sabre Insurance Group |
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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