Correlation Between Ping An and Genworth Financial
Can any of the company-specific risk be diversified away by investing in both Ping An and Genworth Financial 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 Ping An and Genworth Financial into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Ping An Insurance and Genworth Financial, you can compare the effects of market volatilities on Ping An and Genworth Financial 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 Ping An with a short position of Genworth Financial. Check out your portfolio center. Please also check ongoing floating volatility patterns of Ping An and Genworth Financial.
Diversification Opportunities for Ping An and Genworth Financial
0.15 | Correlation Coefficient |
Average diversification
The 3 months correlation between Ping and Genworth is 0.15. Overlapping area represents the amount of risk that can be diversified away by holding Ping An Insurance and Genworth Financial in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Genworth Financial and Ping An 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 Ping An Insurance are associated (or correlated) with Genworth Financial. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Genworth Financial has no effect on the direction of Ping An i.e., Ping An and Genworth Financial go up and down completely randomly.
Pair Corralation between Ping An and Genworth Financial
Assuming the 90 days horizon Ping An Insurance is expected to generate 3.13 times more return on investment than Genworth Financial. However, Ping An is 3.13 times more volatile than Genworth Financial. It trades about 0.13 of its potential returns per unit of risk. Genworth Financial is currently generating about 0.11 per unit of risk. If you would invest 415.00 in Ping An Insurance on September 14, 2024 and sell it today you would earn a total of 177.00 from holding Ping An Insurance or generate 42.65% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 98.44% |
Values | Daily Returns |
Ping An Insurance vs. Genworth Financial
Performance |
Timeline |
Ping An Insurance |
Genworth Financial |
Ping An and Genworth Financial Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Ping An and Genworth Financial
The main advantage of trading using opposite Ping An and Genworth Financial positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Ping An position performs unexpectedly, Genworth Financial 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 Genworth Financial will offset losses from the drop in Genworth Financial's long position.Ping An vs. AIA Group Ltd | Ping An vs. China Life Insurance | Ping An vs. Sanlam Ltd PK | Ping An vs. Lincoln National |
Genworth Financial vs. MetLife Preferred Stock | Genworth Financial vs. Prudential PLC ADR | Genworth Financial vs. Primerica | Genworth Financial vs. CNO 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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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