Correlation Between Duluth Holdings and Victorias Secret
Can any of the company-specific risk be diversified away by investing in both Duluth Holdings and Victorias Secret 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 Duluth Holdings and Victorias Secret into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Duluth Holdings and Victorias Secret Co, you can compare the effects of market volatilities on Duluth Holdings and Victorias Secret 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 Duluth Holdings with a short position of Victorias Secret. Check out your portfolio center. Please also check ongoing floating volatility patterns of Duluth Holdings and Victorias Secret.
Diversification Opportunities for Duluth Holdings and Victorias Secret
0.52 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Duluth and Victorias is 0.52. Overlapping area represents the amount of risk that can be diversified away by holding Duluth Holdings and Victorias Secret Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Victorias Secret and Duluth Holdings 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 Duluth Holdings are associated (or correlated) with Victorias Secret. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Victorias Secret has no effect on the direction of Duluth Holdings i.e., Duluth Holdings and Victorias Secret go up and down completely randomly.
Pair Corralation between Duluth Holdings and Victorias Secret
Given the investment horizon of 90 days Duluth Holdings is expected to under-perform the Victorias Secret. But the stock apears to be less risky and, when comparing its historical volatility, Duluth Holdings is 1.29 times less risky than Victorias Secret. The stock trades about -0.2 of its potential returns per unit of risk. The Victorias Secret Co is currently generating about -0.15 of returns per unit of risk over similar time horizon. If you would invest 3,884 in Victorias Secret Co on November 29, 2024 and sell it today you would lose (1,049) from holding Victorias Secret Co or give up 27.01% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Duluth Holdings vs. Victorias Secret Co
Performance |
Timeline |
Duluth Holdings |
Victorias Secret |
Duluth Holdings and Victorias Secret Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Duluth Holdings and Victorias Secret
The main advantage of trading using opposite Duluth Holdings and Victorias Secret positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Duluth Holdings position performs unexpectedly, Victorias Secret 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 Victorias Secret will offset losses from the drop in Victorias Secret's long position.Duluth Holdings vs. Zumiez Inc | Duluth Holdings vs. JJill Inc | Duluth Holdings vs. Shoe Carnival | Duluth Holdings vs. Cato Corporation |
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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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