Correlation Between Vy Jpmorgan and Lebenthal Lisanti
Can any of the company-specific risk be diversified away by investing in both Vy Jpmorgan and Lebenthal Lisanti 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 Vy Jpmorgan and Lebenthal Lisanti into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Vy Jpmorgan Small and Lebenthal Lisanti Small, you can compare the effects of market volatilities on Vy Jpmorgan and Lebenthal Lisanti 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 Vy Jpmorgan with a short position of Lebenthal Lisanti. Check out your portfolio center. Please also check ongoing floating volatility patterns of Vy Jpmorgan and Lebenthal Lisanti.
Diversification Opportunities for Vy Jpmorgan and Lebenthal Lisanti
0.93 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between IJSIX and Lebenthal is 0.93. Overlapping area represents the amount of risk that can be diversified away by holding Vy Jpmorgan Small and Lebenthal Lisanti Small in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Lebenthal Lisanti Small and Vy Jpmorgan 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 Vy Jpmorgan Small are associated (or correlated) with Lebenthal Lisanti. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Lebenthal Lisanti Small has no effect on the direction of Vy Jpmorgan i.e., Vy Jpmorgan and Lebenthal Lisanti go up and down completely randomly.
Pair Corralation between Vy Jpmorgan and Lebenthal Lisanti
Assuming the 90 days horizon Vy Jpmorgan is expected to generate 6.85 times less return on investment than Lebenthal Lisanti. But when comparing it to its historical volatility, Vy Jpmorgan Small is 1.14 times less risky than Lebenthal Lisanti. It trades about 0.01 of its potential returns per unit of risk. Lebenthal Lisanti Small is currently generating about 0.08 of returns per unit of risk over similar time horizon. If you would invest 2,041 in Lebenthal Lisanti Small on September 28, 2024 and sell it today you would earn a total of 132.00 from holding Lebenthal Lisanti Small or generate 6.47% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Vy Jpmorgan Small vs. Lebenthal Lisanti Small
Performance |
Timeline |
Vy Jpmorgan Small |
Lebenthal Lisanti Small |
Vy Jpmorgan and Lebenthal Lisanti Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Vy Jpmorgan and Lebenthal Lisanti
The main advantage of trading using opposite Vy Jpmorgan and Lebenthal Lisanti positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Vy Jpmorgan position performs unexpectedly, Lebenthal Lisanti 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 Lebenthal Lisanti will offset losses from the drop in Lebenthal Lisanti's long position.Vy Jpmorgan vs. Pace Large Value | Vy Jpmorgan vs. Dunham Large Cap | Vy Jpmorgan vs. Avantis Large Cap | Vy Jpmorgan vs. American Mutual Fund |
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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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