Correlation Between Vy(r) Franklin and Hennessy Technology
Can any of the company-specific risk be diversified away by investing in both Vy(r) Franklin and Hennessy 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 Vy(r) Franklin and Hennessy Technology into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Vy Franklin Income and Hennessy Technology Fund, you can compare the effects of market volatilities on Vy(r) Franklin and Hennessy 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 Vy(r) Franklin with a short position of Hennessy Technology. Check out your portfolio center. Please also check ongoing floating volatility patterns of Vy(r) Franklin and Hennessy Technology.
Diversification Opportunities for Vy(r) Franklin and Hennessy Technology
0.52 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Vy(r) and Hennessy is 0.52. Overlapping area represents the amount of risk that can be diversified away by holding Vy Franklin Income and Hennessy Technology Fund in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Hennessy Technology and Vy(r) Franklin 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 Vy Franklin Income are associated (or correlated) with Hennessy Technology. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Hennessy Technology has no effect on the direction of Vy(r) Franklin i.e., Vy(r) Franklin and Hennessy Technology go up and down completely randomly.
Pair Corralation between Vy(r) Franklin and Hennessy Technology
Assuming the 90 days horizon Vy Franklin Income is expected to generate 0.27 times more return on investment than Hennessy Technology. However, Vy Franklin Income is 3.73 times less risky than Hennessy Technology. It trades about 0.04 of its potential returns per unit of risk. Hennessy Technology Fund is currently generating about -0.07 per unit of risk. If you would invest 959.00 in Vy Franklin Income on December 21, 2024 and sell it today you would earn a total of 8.00 from holding Vy Franklin Income or generate 0.83% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Vy Franklin Income vs. Hennessy Technology Fund
Performance |
Timeline |
Vy Franklin Income |
Hennessy Technology |
Vy(r) Franklin and Hennessy Technology Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Vy(r) Franklin and Hennessy Technology
The main advantage of trading using opposite Vy(r) Franklin and Hennessy Technology positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Vy(r) Franklin position performs unexpectedly, Hennessy 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 Hennessy Technology will offset losses from the drop in Hennessy Technology's long position.Vy(r) Franklin vs. Pimco Capital Sec | Vy(r) Franklin vs. First Trust Specialty | Vy(r) Franklin vs. Goldman Sachs Trust | Vy(r) Franklin vs. 1919 Financial Services |
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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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