Correlation Between Nordic Aqua and Hoegh Autoliners
Can any of the company-specific risk be diversified away by investing in both Nordic Aqua and Hoegh Autoliners 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 Nordic Aqua and Hoegh Autoliners into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Nordic Aqua Partners and Hoegh Autoliners ASA, you can compare the effects of market volatilities on Nordic Aqua and Hoegh Autoliners 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 Nordic Aqua with a short position of Hoegh Autoliners. Check out your portfolio center. Please also check ongoing floating volatility patterns of Nordic Aqua and Hoegh Autoliners.
Diversification Opportunities for Nordic Aqua and Hoegh Autoliners
-0.68 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Nordic and Hoegh is -0.68. Overlapping area represents the amount of risk that can be diversified away by holding Nordic Aqua Partners and Hoegh Autoliners ASA in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Hoegh Autoliners ASA and Nordic Aqua 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 Nordic Aqua Partners are associated (or correlated) with Hoegh Autoliners. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Hoegh Autoliners ASA has no effect on the direction of Nordic Aqua i.e., Nordic Aqua and Hoegh Autoliners go up and down completely randomly.
Pair Corralation between Nordic Aqua and Hoegh Autoliners
Assuming the 90 days trading horizon Nordic Aqua Partners is expected to under-perform the Hoegh Autoliners. But the stock apears to be less risky and, when comparing its historical volatility, Nordic Aqua Partners is 1.12 times less risky than Hoegh Autoliners. The stock trades about -0.03 of its potential returns per unit of risk. The Hoegh Autoliners ASA is currently generating about 0.27 of returns per unit of risk over similar time horizon. If you would invest 7,013 in Hoegh Autoliners ASA on April 23, 2025 and sell it today you would earn a total of 2,832 from holding Hoegh Autoliners ASA or generate 40.38% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Nordic Aqua Partners vs. Hoegh Autoliners ASA
Performance |
Timeline |
Nordic Aqua Partners |
Hoegh Autoliners ASA |
Nordic Aqua and Hoegh Autoliners Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Nordic Aqua and Hoegh Autoliners
The main advantage of trading using opposite Nordic Aqua and Hoegh Autoliners positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Nordic Aqua position performs unexpectedly, Hoegh Autoliners 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 Hoegh Autoliners will offset losses from the drop in Hoegh Autoliners' long position.Nordic Aqua vs. Grong Sparebank | Nordic Aqua vs. SpareBank 1 stlandet | Nordic Aqua vs. Nordic Semiconductor ASA | Nordic Aqua vs. Golden Energy Offshore |
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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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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