Correlation Between NEWELL RUBBERMAID and Designer Brands
Can any of the company-specific risk be diversified away by investing in both NEWELL RUBBERMAID and Designer Brands 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 NEWELL RUBBERMAID and Designer Brands into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between NEWELL RUBBERMAID and Designer Brands, you can compare the effects of market volatilities on NEWELL RUBBERMAID and Designer Brands 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 NEWELL RUBBERMAID with a short position of Designer Brands. Check out your portfolio center. Please also check ongoing floating volatility patterns of NEWELL RUBBERMAID and Designer Brands.
Diversification Opportunities for NEWELL RUBBERMAID and Designer Brands
0.82 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between NEWELL and Designer is 0.82. Overlapping area represents the amount of risk that can be diversified away by holding NEWELL RUBBERMAID and Designer Brands in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Designer Brands and NEWELL RUBBERMAID 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 NEWELL RUBBERMAID are associated (or correlated) with Designer Brands. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Designer Brands has no effect on the direction of NEWELL RUBBERMAID i.e., NEWELL RUBBERMAID and Designer Brands go up and down completely randomly.
Pair Corralation between NEWELL RUBBERMAID and Designer Brands
Assuming the 90 days trading horizon NEWELL RUBBERMAID is expected to under-perform the Designer Brands. But the stock apears to be less risky and, when comparing its historical volatility, NEWELL RUBBERMAID is 1.18 times less risky than Designer Brands. The stock trades about -0.18 of its potential returns per unit of risk. The Designer Brands is currently generating about -0.13 of returns per unit of risk over similar time horizon. If you would invest 515.00 in Designer Brands on December 22, 2024 and sell it today you would lose (177.00) from holding Designer Brands or give up 34.37% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
NEWELL RUBBERMAID vs. Designer Brands
Performance |
Timeline |
NEWELL RUBBERMAID |
Designer Brands |
NEWELL RUBBERMAID and Designer Brands Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with NEWELL RUBBERMAID and Designer Brands
The main advantage of trading using opposite NEWELL RUBBERMAID and Designer Brands positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if NEWELL RUBBERMAID position performs unexpectedly, Designer Brands 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 Designer Brands will offset losses from the drop in Designer Brands' long position.NEWELL RUBBERMAID vs. Yunnan Water Investment | NEWELL RUBBERMAID vs. Beijing Media | NEWELL RUBBERMAID vs. ALLFUNDS GROUP EO 0025 | NEWELL RUBBERMAID vs. JLF INVESTMENT |
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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 Rebalancing module to analyze risk-adjusted returns against different time horizons to find asset-allocation targets.
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