Correlation Between Genworth Financial and Ping An
Can any of the company-specific risk be diversified away by investing in both Genworth Financial and Ping An 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 Genworth Financial and Ping An into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Genworth Financial and Ping An Insurance, you can compare the effects of market volatilities on Genworth Financial and Ping An 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 Genworth Financial with a short position of Ping An. Check out your portfolio center. Please also check ongoing floating volatility patterns of Genworth Financial and Ping An.
Diversification Opportunities for Genworth Financial and Ping An
0.25 | Correlation Coefficient |
Modest diversification
The 3 months correlation between Genworth and Ping is 0.25. Overlapping area represents the amount of risk that can be diversified away by holding Genworth Financial and Ping An Insurance in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Ping An Insurance and Genworth Financial 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 Genworth Financial are associated (or correlated) with Ping An. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Ping An Insurance has no effect on the direction of Genworth Financial i.e., Genworth Financial and Ping An go up and down completely randomly.
Pair Corralation between Genworth Financial and Ping An
Considering the 90-day investment horizon Genworth Financial is expected to generate 0.38 times more return on investment than Ping An. However, Genworth Financial is 2.66 times less risky than Ping An. It trades about 0.18 of its potential returns per unit of risk. Ping An Insurance is currently generating about 0.05 per unit of risk. If you would invest 673.00 in Genworth Financial on August 26, 2024 and sell it today you would earn a total of 104.00 from holding Genworth Financial or generate 15.45% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Genworth Financial vs. Ping An Insurance
Performance |
| Timeline |
| Genworth Financial |
| Ping An Insurance |
Genworth Financial and Ping An Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Genworth Financial and Ping An
The main advantage of trading using opposite Genworth Financial and Ping An positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Genworth Financial position performs unexpectedly, Ping An 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 Ping An will offset losses from the drop in Ping An's long position.| Genworth Financial vs. Morningstar Unconstrained Allocation | Genworth Financial vs. Via Renewables | Genworth Financial vs. Sitka Gold Corp | Genworth Financial vs. MSCI ACWI exAUCONSUMER |
| Ping An vs. CNO Financial Group | Ping An vs. Genworth Financial | Ping An vs. MetLife Preferred Stock | Ping An vs. Prudential Public Limited |
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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