Correlation Between Penn National and URBAN OUTFITTERS
Can any of the company-specific risk be diversified away by investing in both Penn National and URBAN OUTFITTERS 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 Penn National and URBAN OUTFITTERS into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Penn National Gaming and URBAN OUTFITTERS, you can compare the effects of market volatilities on Penn National and URBAN OUTFITTERS 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 Penn National with a short position of URBAN OUTFITTERS. Check out your portfolio center. Please also check ongoing floating volatility patterns of Penn National and URBAN OUTFITTERS.
Diversification Opportunities for Penn National and URBAN OUTFITTERS
0.69 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Penn and URBAN is 0.69. Overlapping area represents the amount of risk that can be diversified away by holding Penn National Gaming and URBAN OUTFITTERS in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on URBAN OUTFITTERS and Penn National 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 Penn National Gaming are associated (or correlated) with URBAN OUTFITTERS. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of URBAN OUTFITTERS has no effect on the direction of Penn National i.e., Penn National and URBAN OUTFITTERS go up and down completely randomly.
Pair Corralation between Penn National and URBAN OUTFITTERS
Assuming the 90 days horizon Penn National Gaming is expected to under-perform the URBAN OUTFITTERS. But the stock apears to be less risky and, when comparing its historical volatility, Penn National Gaming is 1.47 times less risky than URBAN OUTFITTERS. The stock trades about -0.04 of its potential returns per unit of risk. The URBAN OUTFITTERS is currently generating about 0.4 of returns per unit of risk over similar time horizon. If you would invest 3,600 in URBAN OUTFITTERS on September 20, 2024 and sell it today you would earn a total of 1,650 from holding URBAN OUTFITTERS or generate 45.83% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Penn National Gaming vs. URBAN OUTFITTERS
Performance |
Timeline |
Penn National Gaming |
URBAN OUTFITTERS |
Penn National and URBAN OUTFITTERS Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Penn National and URBAN OUTFITTERS
The main advantage of trading using opposite Penn National and URBAN OUTFITTERS positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Penn National position performs unexpectedly, URBAN OUTFITTERS 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 URBAN OUTFITTERS will offset losses from the drop in URBAN OUTFITTERS's long position.Penn National vs. Superior Plus Corp | Penn National vs. SIVERS SEMICONDUCTORS AB | Penn National vs. Norsk Hydro ASA | Penn National vs. Reliance Steel Aluminum |
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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 Price Transformation module to use Price Transformation models to analyze the depth of different equity instruments across global markets.
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