Correlation Between Income Fund and American Funds
Can any of the company-specific risk be diversified away by investing in both Income Fund and American Funds 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 Income Fund and American Funds into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Income Fund Of and American Funds 2015, you can compare the effects of market volatilities on Income Fund and American Funds 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 Income Fund with a short position of American Funds. Check out your portfolio center. Please also check ongoing floating volatility patterns of Income Fund and American Funds.
Diversification Opportunities for Income Fund and American Funds
0.81 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Income and American is 0.81. Overlapping area represents the amount of risk that can be diversified away by holding Income Fund Of and American Funds 2015 in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on American Funds 2015 and Income Fund 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 Income Fund Of are associated (or correlated) with American Funds. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of American Funds 2015 has no effect on the direction of Income Fund i.e., Income Fund and American Funds go up and down completely randomly.
Pair Corralation between Income Fund and American Funds
Assuming the 90 days horizon Income Fund Of is expected to generate 0.78 times more return on investment than American Funds. However, Income Fund Of is 1.28 times less risky than American Funds. It trades about -0.16 of its potential returns per unit of risk. American Funds 2015 is currently generating about -0.17 per unit of risk. If you would invest 2,567 in Income Fund Of on October 16, 2024 and sell it today you would lose (140.00) from holding Income Fund Of or give up 5.45% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Income Fund Of vs. American Funds 2015
Performance |
Timeline |
Income Fund |
American Funds 2015 |
Income Fund and American Funds Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Income Fund and American Funds
The main advantage of trading using opposite Income Fund and American Funds positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Income Fund position performs unexpectedly, American Funds 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 American Funds will offset losses from the drop in American Funds' long position.Income Fund vs. Capital Income Builder | Income Fund vs. Capital World Growth | Income Fund vs. American Balanced | Income Fund vs. American Funds Fundamental |
American Funds vs. American Funds 2055 | American Funds vs. Wisdomtree Floating Rate | American Funds vs. American Funds 2010 | American Funds vs. Fidelity Advisor Emerging |
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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