Correlation Between IShares ETF and Dow Jones
Can any of the company-specific risk be diversified away by investing in both IShares ETF and Dow Jones 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 IShares ETF and Dow Jones into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between iShares ETF Trust and Dow Jones Industrial, you can compare the effects of market volatilities on IShares ETF and Dow Jones 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 IShares ETF with a short position of Dow Jones. Check out your portfolio center. Please also check ongoing floating volatility patterns of IShares ETF and Dow Jones.
Diversification Opportunities for IShares ETF and Dow Jones
0.93 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between IShares and Dow is 0.93. Overlapping area represents the amount of risk that can be diversified away by holding iShares ETF Trust and Dow Jones Industrial in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Dow Jones Industrial and IShares ETF 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 iShares ETF Trust are associated (or correlated) with Dow Jones. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Dow Jones Industrial has no effect on the direction of IShares ETF i.e., IShares ETF and Dow Jones go up and down completely randomly.
Pair Corralation between IShares ETF and Dow Jones
Given the investment horizon of 90 days IShares ETF is expected to generate 8.31 times less return on investment than Dow Jones. But when comparing it to its historical volatility, iShares ETF Trust is 8.23 times less risky than Dow Jones. It trades about 0.22 of its potential returns per unit of risk. Dow Jones Industrial is currently generating about 0.22 of returns per unit of risk over similar time horizon. If you would invest 4,238,757 in Dow Jones Industrial on August 27, 2024 and sell it today you would earn a total of 190,894 from holding Dow Jones Industrial or generate 4.5% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Strong |
| Accuracy | 100.0% |
| Values | Daily Returns |
iShares ETF Trust vs. Dow Jones Industrial
Performance |
| Timeline |
IShares ETF and Dow Jones Volatility Contrast
Predicted Return Density |
| Returns |
iShares ETF Trust
Pair trading matchups for IShares ETF
Dow Jones Industrial
Pair trading matchups for Dow Jones
Pair Trading with IShares ETF and Dow Jones
The main advantage of trading using opposite IShares ETF and Dow Jones positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if IShares ETF position performs unexpectedly, Dow Jones 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 Dow Jones will offset losses from the drop in Dow Jones' long position.| IShares ETF vs. First Trust Low | IShares ETF vs. First Trust Senior | IShares ETF vs. First Trust TCW | IShares ETF vs. First Trust Tactical |
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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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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