Correlation Between Hong Kong and Solstad Offshore
Can any of the company-specific risk be diversified away by investing in both Hong Kong and Solstad 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 Hong Kong and Solstad Offshore into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Hong Kong Land and Solstad Offshore ASA, you can compare the effects of market volatilities on Hong Kong and Solstad 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 Hong Kong with a short position of Solstad Offshore. Check out your portfolio center. Please also check ongoing floating volatility patterns of Hong Kong and Solstad Offshore.
Diversification Opportunities for Hong Kong and Solstad Offshore
-0.12 | Correlation Coefficient |
Good diversification
The 3 months correlation between Hong and Solstad is -0.12. Overlapping area represents the amount of risk that can be diversified away by holding Hong Kong Land and Solstad Offshore ASA in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Solstad Offshore ASA and Hong Kong 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 Hong Kong Land are associated (or correlated) with Solstad Offshore. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Solstad Offshore ASA has no effect on the direction of Hong Kong i.e., Hong Kong and Solstad Offshore go up and down completely randomly.
Pair Corralation between Hong Kong and Solstad Offshore
Assuming the 90 days trading horizon Hong Kong Land is expected to generate 0.16 times more return on investment than Solstad Offshore. However, Hong Kong Land is 6.07 times less risky than Solstad Offshore. It trades about 0.13 of its potential returns per unit of risk. Solstad Offshore ASA is currently generating about -0.08 per unit of risk. If you would invest 724.00 in Hong Kong Land on December 25, 2024 and sell it today you would earn a total of 17.00 from holding Hong Kong Land or generate 2.35% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Hong Kong Land vs. Solstad Offshore ASA
Performance |
Timeline |
Hong Kong Land |
Solstad Offshore ASA |
Hong Kong and Solstad Offshore Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Hong Kong and Solstad Offshore
The main advantage of trading using opposite Hong Kong and Solstad Offshore positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Hong Kong position performs unexpectedly, Solstad 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 Solstad Offshore will offset losses from the drop in Solstad Offshore's long position.Hong Kong vs. China Pacific Insurance | Hong Kong vs. Software Circle plc | Hong Kong vs. Ashtead Technology Holdings | Hong Kong vs. Alfa Financial Software |
Solstad Offshore vs. Check Point Software | Solstad Offshore vs. Polar Capital Technology | Solstad Offshore vs. Software Circle plc | Solstad Offshore vs. Veolia Environnement VE |
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 Performance Analysis module to check effects of mean-variance optimization against your current asset allocation.
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