Correlation Between Global X and TappAlpha SPY
Can any of the company-specific risk be diversified away by investing in both Global X and TappAlpha SPY 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 Global X and TappAlpha SPY into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Global X NASDAQ and TappAlpha SPY Growth, you can compare the effects of market volatilities on Global X and TappAlpha SPY 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 Global X with a short position of TappAlpha SPY. Check out your portfolio center. Please also check ongoing floating volatility patterns of Global X and TappAlpha SPY.
Diversification Opportunities for Global X and TappAlpha SPY
0.96 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between Global and TappAlpha is 0.96. Overlapping area represents the amount of risk that can be diversified away by holding Global X NASDAQ and TappAlpha SPY Growth in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on TappAlpha SPY Growth and Global X 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 Global X NASDAQ are associated (or correlated) with TappAlpha SPY. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of TappAlpha SPY Growth has no effect on the direction of Global X i.e., Global X and TappAlpha SPY go up and down completely randomly.
Pair Corralation between Global X and TappAlpha SPY
Given the investment horizon of 90 days Global X is expected to generate 2.65 times less return on investment than TappAlpha SPY. But when comparing it to its historical volatility, Global X NASDAQ is 1.27 times less risky than TappAlpha SPY. It trades about 0.15 of its potential returns per unit of risk. TappAlpha SPY Growth is currently generating about 0.31 of returns per unit of risk over similar time horizon. If you would invest 2,490 in TappAlpha SPY Growth on September 4, 2024 and sell it today you would earn a total of 140.00 from holding TappAlpha SPY Growth or generate 5.62% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Strong |
| Accuracy | 100.0% |
| Values | Daily Returns |
Global X NASDAQ vs. TappAlpha SPY Growth
Performance |
| Timeline |
| Global X NASDAQ |
| TappAlpha SPY Growth |
Global X and TappAlpha SPY Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Global X and TappAlpha SPY
The main advantage of trading using opposite Global X and TappAlpha SPY positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Global X position performs unexpectedly, TappAlpha SPY 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 TappAlpha SPY will offset losses from the drop in TappAlpha SPY's long position.| Global X vs. Global X Russell | Global X vs. JPMorgan Equity Premium | Global X vs. Global X SP | Global X vs. NEOS ETF Trust |
| TappAlpha SPY vs. Global X SP | TappAlpha SPY vs. Global X NASDAQ | TappAlpha SPY vs. NEOS ETF Trust | TappAlpha SPY vs. JPMorgan Equity Premium |
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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