Correlation Between Lazard and Evercore Partners
Can any of the company-specific risk be diversified away by investing in both Lazard and Evercore Partners 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 Lazard and Evercore Partners into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Lazard and Evercore Partners, you can compare the effects of market volatilities on Lazard and Evercore Partners 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 Lazard with a short position of Evercore Partners. Check out your portfolio center. Please also check ongoing floating volatility patterns of Lazard and Evercore Partners.
Diversification Opportunities for Lazard and Evercore Partners
0.97 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between Lazard and Evercore is 0.97. Overlapping area represents the amount of risk that can be diversified away by holding Lazard and Evercore Partners in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Evercore Partners and Lazard 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 Lazard are associated (or correlated) with Evercore Partners. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Evercore Partners has no effect on the direction of Lazard i.e., Lazard and Evercore Partners go up and down completely randomly.
Pair Corralation between Lazard and Evercore Partners
Considering the 90-day investment horizon Lazard is expected to generate 1.18 times less return on investment than Evercore Partners. But when comparing it to its historical volatility, Lazard is 1.01 times less risky than Evercore Partners. It trades about 0.21 of its potential returns per unit of risk. Evercore Partners is currently generating about 0.24 of returns per unit of risk over similar time horizon. If you would invest 26,135 in Evercore Partners on August 28, 2024 and sell it today you would earn a total of 5,240 from holding Evercore Partners or generate 20.05% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Strong |
| Accuracy | 100.0% |
| Values | Daily Returns |
Lazard vs. Evercore Partners
Performance |
| Timeline |
| Lazard |
| Evercore Partners |
Lazard and Evercore Partners Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Lazard and Evercore Partners
The main advantage of trading using opposite Lazard and Evercore Partners positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Lazard position performs unexpectedly, Evercore Partners 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 Evercore Partners will offset losses from the drop in Evercore Partners' long position.| Lazard vs. PJT Partners | Lazard vs. Moelis Co | Lazard vs. Houlihan Lokey | Lazard vs. Piper Sandler Companies |
| Evercore Partners vs. PJT Partners | Evercore Partners vs. Moelis Co | Evercore Partners vs. Perella Weinberg Partners | Evercore Partners vs. Jefferies Financial Group |
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 Backtesting module to avoid under-diversification and over-optimization by backtesting your portfolios.
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