Correlation Between Viva Wine and Fastighetsbolaget
Can any of the company-specific risk be diversified away by investing in both Viva Wine and Fastighetsbolaget 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 Viva Wine and Fastighetsbolaget into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Viva Wine Group and Fastighetsbolaget Emilshus AB, you can compare the effects of market volatilities on Viva Wine and Fastighetsbolaget 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 Viva Wine with a short position of Fastighetsbolaget. Check out your portfolio center. Please also check ongoing floating volatility patterns of Viva Wine and Fastighetsbolaget.
Diversification Opportunities for Viva Wine and Fastighetsbolaget
-0.15 | Correlation Coefficient |
Good diversification
The 3 months correlation between Viva and Fastighetsbolaget is -0.15. Overlapping area represents the amount of risk that can be diversified away by holding Viva Wine Group and Fastighetsbolaget Emilshus AB in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Fastighetsbolaget and Viva Wine 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 Viva Wine Group are associated (or correlated) with Fastighetsbolaget. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Fastighetsbolaget has no effect on the direction of Viva Wine i.e., Viva Wine and Fastighetsbolaget go up and down completely randomly.
Pair Corralation between Viva Wine and Fastighetsbolaget
Assuming the 90 days trading horizon Viva Wine Group is expected to under-perform the Fastighetsbolaget. But the stock apears to be less risky and, when comparing its historical volatility, Viva Wine Group is 1.67 times less risky than Fastighetsbolaget. The stock trades about -0.14 of its potential returns per unit of risk. The Fastighetsbolaget Emilshus AB is currently generating about 0.15 of returns per unit of risk over similar time horizon. If you would invest 4,430 in Fastighetsbolaget Emilshus AB on September 5, 2024 and sell it today you would earn a total of 380.00 from holding Fastighetsbolaget Emilshus AB or generate 8.58% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Viva Wine Group vs. Fastighetsbolaget Emilshus AB
Performance |
Timeline |
Viva Wine Group |
Fastighetsbolaget |
Viva Wine and Fastighetsbolaget Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Viva Wine and Fastighetsbolaget
The main advantage of trading using opposite Viva Wine and Fastighetsbolaget positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Viva Wine position performs unexpectedly, Fastighetsbolaget 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 Fastighetsbolaget will offset losses from the drop in Fastighetsbolaget's long position.Viva Wine vs. Cint Group AB | Viva Wine vs. Nordic Waterproofing Holding | Viva Wine vs. Synsam AB | Viva Wine vs. Inwido AB |
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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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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