Correlation Between Harbor ETF and Global X
Can any of the company-specific risk be diversified away by investing in both Harbor ETF and Global X 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 Harbor ETF and Global X into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Harbor ETF Trust and Global X Cybersecurity, you can compare the effects of market volatilities on Harbor ETF and Global X 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 Harbor ETF with a short position of Global X. Check out your portfolio center. Please also check ongoing floating volatility patterns of Harbor ETF and Global X.
Diversification Opportunities for Harbor ETF and Global X
0.93 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between Harbor and Global is 0.93. Overlapping area represents the amount of risk that can be diversified away by holding Harbor ETF Trust and Global X Cybersecurity in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Global X Cybersecurity and Harbor 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 Harbor ETF Trust are associated (or correlated) with Global X. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Global X Cybersecurity has no effect on the direction of Harbor ETF i.e., Harbor ETF and Global X go up and down completely randomly.
Pair Corralation between Harbor ETF and Global X
Given the investment horizon of 90 days Harbor ETF is expected to generate 1.61 times less return on investment than Global X. But when comparing it to its historical volatility, Harbor ETF Trust is 2.19 times less risky than Global X. It trades about 0.02 of its potential returns per unit of risk. Global X Cybersecurity is currently generating about 0.02 of returns per unit of risk over similar time horizon. If you would invest 3,363 in Global X Cybersecurity on December 3, 2024 and sell it today you would earn a total of 24.00 from holding Global X Cybersecurity or generate 0.71% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Harbor ETF Trust vs. Global X Cybersecurity
Performance |
Timeline |
Harbor ETF Trust |
Global X Cybersecurity |
Harbor ETF and Global X Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Harbor ETF and Global X
The main advantage of trading using opposite Harbor ETF and Global X positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Harbor ETF position performs unexpectedly, Global X 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 Global X will offset losses from the drop in Global X's long position.Harbor ETF vs. Tidal Trust II | Harbor ETF vs. Draco Evolution AI | Harbor ETF vs. First Trust Alternative | Harbor ETF vs. The Advisors Inner |
Global X vs. iShares Cybersecurity and | Global X vs. First Trust NASDAQ | Global X vs. Global X Cloud | Global X vs. Amplify ETF Trust |
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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