Correlation Between College Retirement and Fidelity China
Can any of the company-specific risk be diversified away by investing in both College Retirement and Fidelity 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 College Retirement and Fidelity China into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between College Retirement Equities and Fidelity China Region, you can compare the effects of market volatilities on College Retirement and Fidelity 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 College Retirement with a short position of Fidelity China. Check out your portfolio center. Please also check ongoing floating volatility patterns of College Retirement and Fidelity China.
Diversification Opportunities for College Retirement and Fidelity China
0.1 | Correlation Coefficient |
Average diversification
The 3 months correlation between College and Fidelity is 0.1. Overlapping area represents the amount of risk that can be diversified away by holding College Retirement Equities and Fidelity China Region in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Fidelity China Region and College Retirement 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 College Retirement Equities are associated (or correlated) with Fidelity China. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Fidelity China Region has no effect on the direction of College Retirement i.e., College Retirement and Fidelity China go up and down completely randomly.
Pair Corralation between College Retirement and Fidelity China
Assuming the 90 days trading horizon College Retirement Equities is expected to generate 0.52 times more return on investment than Fidelity China. However, College Retirement Equities is 1.93 times less risky than Fidelity China. It trades about 0.11 of its potential returns per unit of risk. Fidelity China Region is currently generating about 0.05 per unit of risk. If you would invest 51,436 in College Retirement Equities on September 14, 2024 and sell it today you would earn a total of 658.00 from holding College Retirement Equities or generate 1.28% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
College Retirement Equities vs. Fidelity China Region
Performance |
Timeline |
College Retirement |
Fidelity China Region |
College Retirement and Fidelity China Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with College Retirement and Fidelity China
The main advantage of trading using opposite College Retirement and Fidelity China positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if College Retirement position performs unexpectedly, Fidelity 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 Fidelity China will offset losses from the drop in Fidelity China's long position.College Retirement vs. T Rowe Price | College Retirement vs. Scout E Bond | College Retirement vs. Ft 7934 Corporate | College Retirement vs. T Rowe Price |
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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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