Correlation Between Tile Shop and Haverty Furniture
Can any of the company-specific risk be diversified away by investing in both Tile Shop and Haverty Furniture 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 Tile Shop and Haverty Furniture into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Tile Shop Holdings and Haverty Furniture Companies, you can compare the effects of market volatilities on Tile Shop and Haverty Furniture 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 Tile Shop with a short position of Haverty Furniture. Check out your portfolio center. Please also check ongoing floating volatility patterns of Tile Shop and Haverty Furniture.
Diversification Opportunities for Tile Shop and Haverty Furniture
0.41 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Tile and Haverty is 0.41. Overlapping area represents the amount of risk that can be diversified away by holding Tile Shop Holdings and Haverty Furniture Companies in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Haverty Furniture and Tile Shop 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 Tile Shop Holdings are associated (or correlated) with Haverty Furniture. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Haverty Furniture has no effect on the direction of Tile Shop i.e., Tile Shop and Haverty Furniture go up and down completely randomly.
Pair Corralation between Tile Shop and Haverty Furniture
Given the investment horizon of 90 days Tile Shop Holdings is expected to under-perform the Haverty Furniture. But the stock apears to be less risky and, when comparing its historical volatility, Tile Shop Holdings is 1.11 times less risky than Haverty Furniture. The stock trades about -0.03 of its potential returns per unit of risk. The Haverty Furniture Companies is currently generating about -0.02 of returns per unit of risk over similar time horizon. If you would invest 2,166 in Haverty Furniture Companies on December 28, 2024 and sell it today you would lose (91.00) from holding Haverty Furniture Companies or give up 4.2% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Tile Shop Holdings vs. Haverty Furniture Companies
Performance |
Timeline |
Tile Shop Holdings |
Haverty Furniture |
Tile Shop and Haverty Furniture Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Tile Shop and Haverty Furniture
The main advantage of trading using opposite Tile Shop and Haverty Furniture positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Tile Shop position performs unexpectedly, Haverty Furniture 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 Haverty Furniture will offset losses from the drop in Haverty Furniture's long position.Tile Shop vs. Kingfisher PLC ADR | Tile Shop vs. Haverty Furniture Companies | Tile Shop vs. Arhaus Inc | Tile Shop vs. Kirklands |
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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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