Correlation Between Hennessy Technology and Mfs Technology
Can any of the company-specific risk be diversified away by investing in both Hennessy Technology and Mfs Technology 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 Technology 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 Technology Fund, you can compare the effects of market volatilities on Hennessy Technology and Mfs Technology 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 Technology. Check out your portfolio center. Please also check ongoing floating volatility patterns of Hennessy Technology and Mfs Technology.
Diversification Opportunities for Hennessy Technology and Mfs Technology
0.75 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Hennessy and Mfs is 0.75. Overlapping area represents the amount of risk that can be diversified away by holding Hennessy Technology Fund and Mfs Technology Fund in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Mfs Technology 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 Technology. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Mfs Technology has no effect on the direction of Hennessy Technology i.e., Hennessy Technology and Mfs Technology go up and down completely randomly.
Pair Corralation between Hennessy Technology and Mfs Technology
Assuming the 90 days horizon Hennessy Technology Fund is expected to generate 0.93 times more return on investment than Mfs Technology. However, Hennessy Technology Fund is 1.08 times less risky than Mfs Technology. It trades about -0.07 of its potential returns per unit of risk. Mfs Technology Fund is currently generating about -0.12 per unit of risk. If you would invest 2,303 in Hennessy Technology Fund on December 21, 2024 and sell it today you would lose (145.00) from holding Hennessy Technology Fund or give up 6.3% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Hennessy Technology Fund vs. Mfs Technology Fund
Performance |
Timeline |
Hennessy Technology |
Mfs Technology |
Hennessy Technology and Mfs Technology Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Hennessy Technology and Mfs Technology
The main advantage of trading using opposite Hennessy Technology and Mfs Technology positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Hennessy Technology position performs unexpectedly, Mfs Technology 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 Technology will offset losses from the drop in Mfs Technology's long position.Hennessy Technology vs. Black Oak Emerging | Hennessy Technology vs. Hennessy Large Cap | Hennessy Technology vs. Hennessy Japan Fund | Hennessy Technology vs. Hennessy Small Cap |
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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 Price Transformation module to use Price Transformation models to analyze the depth of different equity instruments across global markets.
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