Correlation Between Universal Insurance and Ping An
Can any of the company-specific risk be diversified away by investing in both Universal Insurance 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 Universal Insurance and Ping An into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Universal Insurance Holdings and Ping An Insurance, you can compare the effects of market volatilities on Universal Insurance 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 Universal Insurance with a short position of Ping An. Check out your portfolio center. Please also check ongoing floating volatility patterns of Universal Insurance and Ping An.
Diversification Opportunities for Universal Insurance and Ping An
-0.07 | Correlation Coefficient |
Good diversification
The 3 months correlation between Universal and Ping is -0.07. Overlapping area represents the amount of risk that can be diversified away by holding Universal Insurance Holdings 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 Universal Insurance 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 Universal Insurance Holdings 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 Universal Insurance i.e., Universal Insurance and Ping An go up and down completely randomly.
Pair Corralation between Universal Insurance and Ping An
Assuming the 90 days horizon Universal Insurance is expected to generate 2.27 times less return on investment than Ping An. But when comparing it to its historical volatility, Universal Insurance Holdings is 1.61 times less risky than Ping An. It trades about 0.06 of its potential returns per unit of risk. Ping An Insurance is currently generating about 0.08 of returns per unit of risk over similar time horizon. If you would invest 202.00 in Ping An Insurance on August 26, 2024 and sell it today you would earn a total of 344.00 from holding Ping An Insurance or generate 170.3% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Universal Insurance Holdings vs. Ping An Insurance
Performance |
| Timeline |
| Universal Insurance |
| Ping An Insurance |
Universal Insurance and Ping An Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Universal Insurance and Ping An
The main advantage of trading using opposite Universal Insurance and Ping An positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Universal Insurance 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.| Universal Insurance vs. Insurance Australia Group | Universal Insurance vs. Superior Plus Corp | Universal Insurance vs. NMI Holdings | Universal Insurance vs. Origin Agritech |
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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