Correlation Between Hooker Furniture and Where Food
Can any of the company-specific risk be diversified away by investing in both Hooker Furniture and Where Food 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 Hooker Furniture and Where Food into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Hooker Furniture and Where Food Comes, you can compare the effects of market volatilities on Hooker Furniture and Where Food 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 Hooker Furniture with a short position of Where Food. Check out your portfolio center. Please also check ongoing floating volatility patterns of Hooker Furniture and Where Food.
Diversification Opportunities for Hooker Furniture and Where Food
0.16 | Correlation Coefficient |
Average diversification
The 3 months correlation between Hooker and Where is 0.16. Overlapping area represents the amount of risk that can be diversified away by holding Hooker Furniture and Where Food Comes in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Where Food Comes and Hooker Furniture 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 Hooker Furniture are associated (or correlated) with Where Food. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Where Food Comes has no effect on the direction of Hooker Furniture i.e., Hooker Furniture and Where Food go up and down completely randomly.
Pair Corralation between Hooker Furniture and Where Food
Given the investment horizon of 90 days Hooker Furniture is expected to generate 3.12 times less return on investment than Where Food. In addition to that, Hooker Furniture is 1.64 times more volatile than Where Food Comes. It trades about 0.02 of its total potential returns per unit of risk. Where Food Comes is currently generating about 0.12 per unit of volatility. If you would invest 1,089 in Where Food Comes on September 16, 2024 and sell it today you would earn a total of 157.00 from holding Where Food Comes or generate 14.42% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Hooker Furniture vs. Where Food Comes
Performance |
Timeline |
Hooker Furniture |
Where Food Comes |
Hooker Furniture and Where Food Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Hooker Furniture and Where Food
The main advantage of trading using opposite Hooker Furniture and Where Food positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Hooker Furniture position performs unexpectedly, Where Food 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 Where Food will offset losses from the drop in Where Food's long position.Hooker Furniture vs. Natuzzi SpA | Hooker Furniture vs. Hamilton Beach Brands | Hooker Furniture vs. La Z Boy Incorporated | Hooker Furniture vs. MasterBrand |
Where Food vs. Swvl Holdings Corp | Where Food vs. Guardforce AI Co | Where Food vs. Thayer Ventures Acquisition |
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 Idea Optimizer module to use advanced portfolio builder with pre-computed micro ideas to build optimal portfolio .
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