Correlation Between Health Care and Technology Fund
Can any of the company-specific risk be diversified away by investing in both Health Care and Technology Fund 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 Health Care and Technology Fund into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Health Care Fund and Technology Fund Investor, you can compare the effects of market volatilities on Health Care and Technology Fund 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 Health Care with a short position of Technology Fund. Check out your portfolio center. Please also check ongoing floating volatility patterns of Health Care and Technology Fund.
Diversification Opportunities for Health Care and Technology Fund
-0.65 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Health and Technology is -0.65. Overlapping area represents the amount of risk that can be diversified away by holding Health Care Fund and Technology Fund Investor in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Technology Fund Investor and Health Care 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 Health Care Fund are associated (or correlated) with Technology Fund. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Technology Fund Investor has no effect on the direction of Health Care i.e., Health Care and Technology Fund go up and down completely randomly.
Pair Corralation between Health Care and Technology Fund
Assuming the 90 days horizon Health Care Fund is expected to under-perform the Technology Fund. But the mutual fund apears to be less risky and, when comparing its historical volatility, Health Care Fund is 1.33 times less risky than Technology Fund. The mutual fund trades about -0.11 of its potential returns per unit of risk. The Technology Fund Investor is currently generating about 0.15 of returns per unit of risk over similar time horizon. If you would invest 21,705 in Technology Fund Investor on September 13, 2024 and sell it today you would earn a total of 776.00 from holding Technology Fund Investor or generate 3.58% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Health Care Fund vs. Technology Fund Investor
Performance |
Timeline |
Health Care Fund |
Technology Fund Investor |
Health Care and Technology Fund Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Health Care and Technology Fund
The main advantage of trading using opposite Health Care and Technology Fund positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Health Care position performs unexpectedly, Technology Fund 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 Technology Fund will offset losses from the drop in Technology Fund's long position.Health Care vs. Basic Materials Fund | Health Care vs. Basic Materials Fund | Health Care vs. Banking Fund Class | Health Care vs. Basic Materials Fund |
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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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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