Correlation Between OMX Stockholm and Alligator Bioscience
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By analyzing existing cross correlation between OMX Stockholm Mid and Alligator Bioscience AB, you can compare the effects of market volatilities on OMX Stockholm and Alligator Bioscience 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 OMX Stockholm with a short position of Alligator Bioscience. Check out your portfolio center. Please also check ongoing floating volatility patterns of OMX Stockholm and Alligator Bioscience.
Diversification Opportunities for OMX Stockholm and Alligator Bioscience
-0.27 | Correlation Coefficient |
Very good diversification
The 3 months correlation between OMX and Alligator is -0.27. Overlapping area represents the amount of risk that can be diversified away by holding OMX Stockholm Mid and Alligator Bioscience AB in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Alligator Bioscience and OMX Stockholm 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 OMX Stockholm Mid are associated (or correlated) with Alligator Bioscience. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Alligator Bioscience has no effect on the direction of OMX Stockholm i.e., OMX Stockholm and Alligator Bioscience go up and down completely randomly.
Pair Corralation between OMX Stockholm and Alligator Bioscience
Assuming the 90 days trading horizon OMX Stockholm is expected to generate 206.43 times less return on investment than Alligator Bioscience. But when comparing it to its historical volatility, OMX Stockholm Mid is 179.97 times less risky than Alligator Bioscience. It trades about 0.14 of its potential returns per unit of risk. Alligator Bioscience AB is currently generating about 0.16 of returns per unit of risk over similar time horizon. If you would invest 4.72 in Alligator Bioscience AB on November 29, 2024 and sell it today you would earn a total of 7.28 from holding Alligator Bioscience AB or generate 154.24% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
OMX Stockholm Mid vs. Alligator Bioscience AB
Performance |
Timeline |
OMX Stockholm and Alligator Bioscience Volatility Contrast
Predicted Return Density |
Returns |
OMX Stockholm Mid
Pair trading matchups for OMX Stockholm
Alligator Bioscience AB
Pair trading matchups for Alligator Bioscience
Pair Trading with OMX Stockholm and Alligator Bioscience
The main advantage of trading using opposite OMX Stockholm and Alligator Bioscience positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if OMX Stockholm position performs unexpectedly, Alligator Bioscience 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 Alligator Bioscience will offset losses from the drop in Alligator Bioscience's long position.OMX Stockholm vs. eEducation Albert AB | OMX Stockholm vs. Lime Technologies AB | OMX Stockholm vs. FormPipe Software AB | OMX Stockholm vs. Media and Games |
Alligator Bioscience vs. Cantargia AB | Alligator Bioscience vs. BioArctic AB | Alligator Bioscience vs. Oncopeptides AB | Alligator Bioscience vs. Hansa Biopharma AB |
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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