Correlation Between Greenhill and AGBA Acquisition
Can any of the company-specific risk be diversified away by investing in both Greenhill and AGBA Acquisition 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 Greenhill and AGBA Acquisition into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Greenhill Co and AGBA Acquisition, you can compare the effects of market volatilities on Greenhill and AGBA Acquisition 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 Greenhill with a short position of AGBA Acquisition. Check out your portfolio center. Please also check ongoing floating volatility patterns of Greenhill and AGBA Acquisition.
Diversification Opportunities for Greenhill and AGBA Acquisition
-0.29 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Greenhill and AGBA is -0.29. Overlapping area represents the amount of risk that can be diversified away by holding Greenhill Co and AGBA Acquisition in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on AGBA Acquisition and Greenhill 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 Greenhill Co are associated (or correlated) with AGBA Acquisition. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of AGBA Acquisition has no effect on the direction of Greenhill i.e., Greenhill and AGBA Acquisition go up and down completely randomly.
Pair Corralation between Greenhill and AGBA Acquisition
Considering the 90-day investment horizon Greenhill is expected to generate 13.48 times less return on investment than AGBA Acquisition. But when comparing it to its historical volatility, Greenhill Co is 105.4 times less risky than AGBA Acquisition. It trades about 0.28 of its potential returns per unit of risk. AGBA Acquisition is currently generating about 0.04 of returns per unit of risk over similar time horizon. If you would invest 660.00 in AGBA Acquisition on August 31, 2024 and sell it today you would lose (100.00) from holding AGBA Acquisition or give up 15.15% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 9.36% |
Values | Daily Returns |
Greenhill Co vs. AGBA Acquisition
Performance |
Timeline |
Greenhill |
Risk-Adjusted Performance
0 of 100
Weak | Strong |
Very Weak
AGBA Acquisition |
Risk-Adjusted Performance
0 of 100
Weak | Strong |
Very Weak
Greenhill and AGBA Acquisition Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Greenhill and AGBA Acquisition
The main advantage of trading using opposite Greenhill and AGBA Acquisition positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Greenhill position performs unexpectedly, AGBA Acquisition 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 AGBA Acquisition will offset losses from the drop in AGBA Acquisition's long position.Greenhill vs. Magic Empire Global | Greenhill vs. Applied Blockchain | Greenhill vs. Zhong Yang Financial | Greenhill vs. Netcapital |
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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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