Correlation Between Discipline Fund and EA Series
Can any of the company-specific risk be diversified away by investing in both Discipline Fund and EA Series 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 Discipline Fund and EA Series into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Discipline Fund ETF and EA Series Trust, you can compare the effects of market volatilities on Discipline Fund and EA Series 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 Discipline Fund with a short position of EA Series. Check out your portfolio center. Please also check ongoing floating volatility patterns of Discipline Fund and EA Series.
Diversification Opportunities for Discipline Fund and EA Series
0.01 | Correlation Coefficient |
Significant diversification
The 3 months correlation between Discipline and DRAI is 0.01. Overlapping area represents the amount of risk that can be diversified away by holding Discipline Fund ETF and EA Series Trust in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on EA Series Trust and Discipline Fund 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 Discipline Fund ETF are associated (or correlated) with EA Series. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of EA Series Trust has no effect on the direction of Discipline Fund i.e., Discipline Fund and EA Series go up and down completely randomly.
Pair Corralation between Discipline Fund and EA Series
Given the investment horizon of 90 days Discipline Fund ETF is expected to generate 0.36 times more return on investment than EA Series. However, Discipline Fund ETF is 2.75 times less risky than EA Series. It trades about 0.08 of its potential returns per unit of risk. EA Series Trust is currently generating about 0.02 per unit of risk. If you would invest 2,297 in Discipline Fund ETF on September 12, 2024 and sell it today you would earn a total of 13.00 from holding Discipline Fund ETF or generate 0.57% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Discipline Fund ETF vs. EA Series Trust
Performance |
| Timeline |
| Discipline Fund ETF |
| EA Series Trust |
Discipline Fund and EA Series Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Discipline Fund and EA Series
The main advantage of trading using opposite Discipline Fund and EA Series positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Discipline Fund position performs unexpectedly, EA Series 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 EA Series will offset losses from the drop in EA Series' long position.| Discipline Fund vs. ATAC Rotation ETF | Discipline Fund vs. Amplify BlackSwan ISWN | Discipline Fund vs. Tidal ETF Trust | Discipline Fund vs. Aptus Defined Risk |
| EA Series vs. Vanguard Total Stock | EA Series vs. SPDR SP 500 | EA Series vs. iShares Core SP | EA Series vs. Vanguard Total Bond |
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 Headlines Timeline module to stay connected to all market stories and filter out noise. Drill down to analyze hype elasticity.
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