Correlation Between Baltic Sea and Kmc Properties
Can any of the company-specific risk be diversified away by investing in both Baltic Sea and Kmc Properties 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 Baltic Sea and Kmc Properties into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Baltic Sea Properties and Kmc Properties ASA, you can compare the effects of market volatilities on Baltic Sea and Kmc Properties 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 Baltic Sea with a short position of Kmc Properties. Check out your portfolio center. Please also check ongoing floating volatility patterns of Baltic Sea and Kmc Properties.
Diversification Opportunities for Baltic Sea and Kmc Properties
0.17 | Correlation Coefficient |
Average diversification
The 3 months correlation between Baltic and Kmc is 0.17. Overlapping area represents the amount of risk that can be diversified away by holding Baltic Sea Properties and Kmc Properties ASA in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Kmc Properties ASA and Baltic Sea 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 Baltic Sea Properties are associated (or correlated) with Kmc Properties. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Kmc Properties ASA has no effect on the direction of Baltic Sea i.e., Baltic Sea and Kmc Properties go up and down completely randomly.
Pair Corralation between Baltic Sea and Kmc Properties
Assuming the 90 days trading horizon Baltic Sea Properties is expected to generate 0.19 times more return on investment than Kmc Properties. However, Baltic Sea Properties is 5.37 times less risky than Kmc Properties. It trades about 0.04 of its potential returns per unit of risk. Kmc Properties ASA is currently generating about -0.22 per unit of risk. If you would invest 4,900 in Baltic Sea Properties on September 1, 2024 and sell it today you would earn a total of 100.00 from holding Baltic Sea Properties or generate 2.04% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Insignificant |
| Accuracy | 95.65% |
| Values | Daily Returns |
Baltic Sea Properties vs. Kmc Properties ASA
Performance |
| Timeline |
| Baltic Sea Properties |
| Kmc Properties ASA |
Baltic Sea and Kmc Properties Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Baltic Sea and Kmc Properties
The main advantage of trading using opposite Baltic Sea and Kmc Properties positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Baltic Sea position performs unexpectedly, Kmc Properties 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 Kmc Properties will offset losses from the drop in Kmc Properties' long position.| Baltic Sea vs. Eidesvik Offshore ASA | Baltic Sea vs. Nordic Mining ASA | Baltic Sea vs. Norwegian Air Shuttle | Baltic Sea vs. Shelf Drilling |
| Kmc Properties vs. Entra ASA | Kmc Properties vs. Selvaag Bolig ASA | Kmc Properties vs. Baltic Sea Properties |
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 Price Transformation module to use Price Transformation models to analyze the depth of different equity instruments across global markets.
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