Correlation Between MicroSectors FANG and Virtus ETF
Can any of the company-specific risk be diversified away by investing in both MicroSectors FANG and Virtus ETF 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 MicroSectors FANG and Virtus ETF into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between MicroSectors FANG Index and Virtus ETF Trust, you can compare the effects of market volatilities on MicroSectors FANG and Virtus ETF 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 MicroSectors FANG with a short position of Virtus ETF. Check out your portfolio center. Please also check ongoing floating volatility patterns of MicroSectors FANG and Virtus ETF.
Diversification Opportunities for MicroSectors FANG and Virtus ETF
0.02 | Correlation Coefficient |
Significant diversification
The 3 months correlation between MicroSectors and Virtus is 0.02. Overlapping area represents the amount of risk that can be diversified away by holding MicroSectors FANG Index and Virtus ETF Trust in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Virtus ETF Trust and MicroSectors FANG 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 MicroSectors FANG Index are associated (or correlated) with Virtus ETF. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Virtus ETF Trust has no effect on the direction of MicroSectors FANG i.e., MicroSectors FANG and Virtus ETF go up and down completely randomly.
Pair Corralation between MicroSectors FANG and Virtus ETF
Given the investment horizon of 90 days MicroSectors FANG Index is expected to generate 25.12 times more return on investment than Virtus ETF. However, MicroSectors FANG is 25.12 times more volatile than Virtus ETF Trust. It trades about 0.12 of its potential returns per unit of risk. Virtus ETF Trust is currently generating about 0.05 per unit of risk. If you would invest 1,316 in MicroSectors FANG Index on December 30, 2024 and sell it today you would earn a total of 491.00 from holding MicroSectors FANG Index or generate 37.31% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
MicroSectors FANG Index vs. Virtus ETF Trust
Performance |
Timeline |
MicroSectors FANG Index |
Virtus ETF Trust |
MicroSectors FANG and Virtus ETF Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with MicroSectors FANG and Virtus ETF
The main advantage of trading using opposite MicroSectors FANG and Virtus ETF positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if MicroSectors FANG position performs unexpectedly, Virtus ETF 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 Virtus ETF will offset losses from the drop in Virtus ETF's long position.MicroSectors FANG vs. Direxion Daily Semiconductor | MicroSectors FANG vs. Direxion Daily Technology | MicroSectors FANG vs. Bank of Montreal | MicroSectors FANG vs. Direxion Daily SP |
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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 Equity Valuation module to check real value of public entities based on technical and fundamental data.
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