Correlation Between AerCap Holdings and PROG Holdings
Can any of the company-specific risk be diversified away by investing in both AerCap Holdings and PROG Holdings 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 AerCap Holdings and PROG Holdings into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between AerCap Holdings NV and PROG Holdings, you can compare the effects of market volatilities on AerCap Holdings and PROG Holdings 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 AerCap Holdings with a short position of PROG Holdings. Check out your portfolio center. Please also check ongoing floating volatility patterns of AerCap Holdings and PROG Holdings.
Diversification Opportunities for AerCap Holdings and PROG Holdings
0.9 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between AerCap and PROG is 0.9. Overlapping area represents the amount of risk that can be diversified away by holding AerCap Holdings NV and PROG Holdings in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on PROG Holdings and AerCap Holdings 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 AerCap Holdings NV are associated (or correlated) with PROG Holdings. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of PROG Holdings has no effect on the direction of AerCap Holdings i.e., AerCap Holdings and PROG Holdings go up and down completely randomly.
Pair Corralation between AerCap Holdings and PROG Holdings
Considering the 90-day investment horizon AerCap Holdings is expected to generate 1.27 times less return on investment than PROG Holdings. But when comparing it to its historical volatility, AerCap Holdings NV is 1.55 times less risky than PROG Holdings. It trades about 0.2 of its potential returns per unit of risk. PROG Holdings is currently generating about 0.17 of returns per unit of risk over similar time horizon. If you would invest 2,967 in PROG Holdings on February 23, 2024 and sell it today you would earn a total of 662.00 from holding PROG Holdings or generate 22.31% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Strong |
Accuracy | 100.0% |
Values | Daily Returns |
AerCap Holdings NV vs. PROG Holdings
Performance |
Timeline |
AerCap Holdings NV |
PROG Holdings |
AerCap Holdings and PROG Holdings Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with AerCap Holdings and PROG Holdings
The main advantage of trading using opposite AerCap Holdings and PROG Holdings positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if AerCap Holdings position performs unexpectedly, PROG Holdings 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 PROG Holdings will offset losses from the drop in PROG Holdings' long position.AerCap Holdings vs. Ryder System | AerCap Holdings vs. The Aarons | AerCap Holdings vs. Alta Equipment Group | AerCap Holdings vs. PROG Holdings |
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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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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