Correlation Between JPM BetaBuilders and JPM China
Can any of the company-specific risk be diversified away by investing in both JPM BetaBuilders and JPM China 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 JPM BetaBuilders and JPM China into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between JPM BetaBuilders UK and JPM China A, you can compare the effects of market volatilities on JPM BetaBuilders and JPM China 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 JPM BetaBuilders with a short position of JPM China. Check out your portfolio center. Please also check ongoing floating volatility patterns of JPM BetaBuilders and JPM China.
Diversification Opportunities for JPM BetaBuilders and JPM China
-0.26 | Correlation Coefficient |
Very good diversification
The 3 months correlation between JPM and JPM is -0.26. Overlapping area represents the amount of risk that can be diversified away by holding JPM BetaBuilders UK and JPM China A in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on JPM China A and JPM BetaBuilders 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 JPM BetaBuilders UK are associated (or correlated) with JPM China. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of JPM China A has no effect on the direction of JPM BetaBuilders i.e., JPM BetaBuilders and JPM China go up and down completely randomly.
Pair Corralation between JPM BetaBuilders and JPM China
Assuming the 90 days trading horizon JPM BetaBuilders UK is expected to generate 2.63 times more return on investment than JPM China. However, JPM BetaBuilders is 2.63 times more volatile than JPM China A. It trades about 0.13 of its potential returns per unit of risk. JPM China A is currently generating about -0.02 per unit of risk. If you would invest 6,626 in JPM BetaBuilders UK on October 25, 2024 and sell it today you would earn a total of 2,724 from holding JPM BetaBuilders UK or generate 41.11% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 98.39% |
Values | Daily Returns |
JPM BetaBuilders UK vs. JPM China A
Performance |
Timeline |
JPM BetaBuilders |
JPM China A |
JPM BetaBuilders and JPM China Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with JPM BetaBuilders and JPM China
The main advantage of trading using opposite JPM BetaBuilders and JPM China positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if JPM BetaBuilders position performs unexpectedly, JPM China 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 JPM China will offset losses from the drop in JPM China's long position.JPM BetaBuilders vs. JPM BetaBuilders China | JPM BetaBuilders vs. JPM AC Asia | JPM BetaBuilders vs. JPM BetaBuilders Treasury | JPM BetaBuilders vs. JPM Research Enhanced |
JPM China vs. JPM BetaBuilders China | JPM China vs. JPM AC Asia | JPM China vs. JPM BetaBuilders Treasury | JPM China vs. JPM Research Enhanced |
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 Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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