Correlation Between National Retail and Ross Stores
Can any of the company-specific risk be diversified away by investing in both National Retail and Ross Stores 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 National Retail and Ross Stores into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between National Retail Properties and Ross Stores, you can compare the effects of market volatilities on National Retail and Ross Stores 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 National Retail with a short position of Ross Stores. Check out your portfolio center. Please also check ongoing floating volatility patterns of National Retail and Ross Stores.
Diversification Opportunities for National Retail and Ross Stores
-0.22 | Correlation Coefficient |
Very good diversification
The 3 months correlation between National and Ross is -0.22. Overlapping area represents the amount of risk that can be diversified away by holding National Retail Properties and Ross Stores in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Ross Stores and National Retail 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 National Retail Properties are associated (or correlated) with Ross Stores. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Ross Stores has no effect on the direction of National Retail i.e., National Retail and Ross Stores go up and down completely randomly.
Pair Corralation between National Retail and Ross Stores
Assuming the 90 days trading horizon National Retail Properties is expected to under-perform the Ross Stores. But the stock apears to be less risky and, when comparing its historical volatility, National Retail Properties is 3.06 times less risky than Ross Stores. The stock trades about -0.5 of its potential returns per unit of risk. The Ross Stores is currently generating about 0.12 of returns per unit of risk over similar time horizon. If you would invest 13,560 in Ross Stores on September 22, 2024 and sell it today you would earn a total of 782.00 from holding Ross Stores or generate 5.77% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
National Retail Properties vs. Ross Stores
Performance |
Timeline |
National Retail Prop |
Ross Stores |
National Retail and Ross Stores Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with National Retail and Ross Stores
The main advantage of trading using opposite National Retail and Ross Stores positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if National Retail position performs unexpectedly, Ross Stores 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 Ross Stores will offset losses from the drop in Ross Stores' long position.National Retail vs. Apple Inc | National Retail vs. Apple Inc | National Retail vs. Apple Inc | National Retail vs. Apple Inc |
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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 My Watchlist Analysis module to analyze my current watchlist and to refresh optimization strategy. Macroaxis watchlist is based on self-learning algorithm to remember stocks you like.
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