Correlation Between Penn National and Lamar Advertising
Can any of the company-specific risk be diversified away by investing in both Penn National and Lamar Advertising 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 Lamar Advertising 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 Lamar Advertising, you can compare the effects of market volatilities on Penn National and Lamar Advertising 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 Lamar Advertising. Check out your portfolio center. Please also check ongoing floating volatility patterns of Penn National and Lamar Advertising.
Diversification Opportunities for Penn National and Lamar Advertising
0.03 | Correlation Coefficient |
Significant diversification
The 3 months correlation between Penn and Lamar is 0.03. Overlapping area represents the amount of risk that can be diversified away by holding Penn National Gaming and Lamar Advertising in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Lamar Advertising 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 Lamar Advertising. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Lamar Advertising has no effect on the direction of Penn National i.e., Penn National and Lamar Advertising go up and down completely randomly.
Pair Corralation between Penn National and Lamar Advertising
Assuming the 90 days horizon Penn National Gaming is expected to generate 2.12 times more return on investment than Lamar Advertising. However, Penn National is 2.12 times more volatile than Lamar Advertising. It trades about 0.08 of its potential returns per unit of risk. Lamar Advertising is currently generating about -0.05 per unit of risk. If you would invest 1,724 in Penn National Gaming on October 23, 2024 and sell it today you would earn a total of 205.00 from holding Penn National Gaming or generate 11.89% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Penn National Gaming vs. Lamar Advertising
Performance |
Timeline |
Penn National Gaming |
Lamar Advertising |
Penn National and Lamar Advertising Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Penn National and Lamar Advertising
The main advantage of trading using opposite Penn National and Lamar Advertising positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Penn National position performs unexpectedly, Lamar Advertising 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 Lamar Advertising will offset losses from the drop in Lamar Advertising's long position.Penn National vs. Apollo Medical Holdings | Penn National vs. Datadog | Penn National vs. MICRONIC MYDATA | Penn National vs. Northern Data AG |
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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 Center module to all portfolio management and optimization tools to improve performance of your portfolios.
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