Correlation Between Hennessy Technology and Mfs Emerging
Can any of the company-specific risk be diversified away by investing in both Hennessy Technology and Mfs Emerging 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 Hennessy Technology and Mfs Emerging into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Hennessy Technology Fund and Mfs Emerging Markets, you can compare the effects of market volatilities on Hennessy Technology and Mfs Emerging 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 Hennessy Technology with a short position of Mfs Emerging. Check out your portfolio center. Please also check ongoing floating volatility patterns of Hennessy Technology and Mfs Emerging.
Diversification Opportunities for Hennessy Technology and Mfs Emerging
-0.33 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Hennessy and Mfs is -0.33. Overlapping area represents the amount of risk that can be diversified away by holding Hennessy Technology Fund and Mfs Emerging Markets in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Mfs Emerging Markets and Hennessy Technology 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 Hennessy Technology Fund are associated (or correlated) with Mfs Emerging. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Mfs Emerging Markets has no effect on the direction of Hennessy Technology i.e., Hennessy Technology and Mfs Emerging go up and down completely randomly.
Pair Corralation between Hennessy Technology and Mfs Emerging
Assuming the 90 days horizon Hennessy Technology Fund is expected to under-perform the Mfs Emerging. In addition to that, Hennessy Technology is 3.75 times more volatile than Mfs Emerging Markets. It trades about -0.17 of its total potential returns per unit of risk. Mfs Emerging Markets is currently generating about -0.49 per unit of volatility. If you would invest 539.00 in Mfs Emerging Markets on October 8, 2024 and sell it today you would lose (15.00) from holding Mfs Emerging Markets or give up 2.78% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Hennessy Technology Fund vs. Mfs Emerging Markets
Performance |
Timeline |
Hennessy Technology |
Mfs Emerging Markets |
Hennessy Technology and Mfs Emerging Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Hennessy Technology and Mfs Emerging
The main advantage of trading using opposite Hennessy Technology and Mfs Emerging positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Hennessy Technology position performs unexpectedly, Mfs Emerging 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 Mfs Emerging will offset losses from the drop in Mfs Emerging's long position.Hennessy Technology vs. Fidelity Advisor Health | Hennessy Technology vs. Fidelity Advisor Financial | Hennessy Technology vs. Fidelity Advisor Equity | Hennessy Technology vs. HUMANA INC |
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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 Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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