Correlation Between JAPAN AIRLINES and Ping An
Can any of the company-specific risk be diversified away by investing in both JAPAN AIRLINES 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 JAPAN AIRLINES and Ping An into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between JAPAN AIRLINES and Ping An Insurance, you can compare the effects of market volatilities on JAPAN AIRLINES 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 JAPAN AIRLINES with a short position of Ping An. Check out your portfolio center. Please also check ongoing floating volatility patterns of JAPAN AIRLINES and Ping An.
Diversification Opportunities for JAPAN AIRLINES and Ping An
-0.21 | Correlation Coefficient |
Very good diversification
The 3 months correlation between JAPAN and Ping is -0.21. Overlapping area represents the amount of risk that can be diversified away by holding JAPAN AIRLINES 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 JAPAN AIRLINES 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 JAPAN AIRLINES 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 JAPAN AIRLINES i.e., JAPAN AIRLINES and Ping An go up and down completely randomly.
Pair Corralation between JAPAN AIRLINES and Ping An
Assuming the 90 days trading horizon JAPAN AIRLINES is expected to under-perform the Ping An. But the stock apears to be less risky and, when comparing its historical volatility, JAPAN AIRLINES is 3.45 times less risky than Ping An. The stock trades about -0.02 of its potential returns per unit of risk. The Ping An Insurance is currently generating about 0.11 of returns per unit of risk over similar time horizon. If you would invest 194.00 in Ping An Insurance on September 20, 2024 and sell it today you would earn a total of 363.00 from holding Ping An Insurance or generate 187.11% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
JAPAN AIRLINES vs. Ping An Insurance
Performance |
Timeline |
JAPAN AIRLINES |
Ping An Insurance |
JAPAN AIRLINES and Ping An Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with JAPAN AIRLINES and Ping An
The main advantage of trading using opposite JAPAN AIRLINES and Ping An positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if JAPAN AIRLINES 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.JAPAN AIRLINES vs. DeVry Education Group | JAPAN AIRLINES vs. Grand Canyon Education | JAPAN AIRLINES vs. TAL Education Group | JAPAN AIRLINES vs. Corporate Office Properties |
Ping An vs. SOUTHWEST AIRLINES | Ping An vs. Charoen Pokphand Foods | Ping An vs. JAPAN AIRLINES | Ping An vs. The Boston Beer |
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 Rebalancing module to analyze risk-adjusted returns against different time horizons to find asset-allocation targets.
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