Correlation Between Beta Shares and Betashares Asia
Can any of the company-specific risk be diversified away by investing in both Beta Shares and Betashares Asia 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 Beta Shares and Betashares Asia into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Beta Shares SPASX and Betashares Asia Technology, you can compare the effects of market volatilities on Beta Shares and Betashares Asia 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 Beta Shares with a short position of Betashares Asia. Check out your portfolio center. Please also check ongoing floating volatility patterns of Beta Shares and Betashares Asia.
Diversification Opportunities for Beta Shares and Betashares Asia
0.06 | Correlation Coefficient |
Significant diversification
The 3 months correlation between Beta and Betashares is 0.06. Overlapping area represents the amount of risk that can be diversified away by holding Beta Shares SPASX and Betashares Asia Technology in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Betashares Asia Tech and Beta Shares 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 Beta Shares SPASX are associated (or correlated) with Betashares Asia. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Betashares Asia Tech has no effect on the direction of Beta Shares i.e., Beta Shares and Betashares Asia go up and down completely randomly.
Pair Corralation between Beta Shares and Betashares Asia
Assuming the 90 days trading horizon Beta Shares is expected to generate 1.08 times less return on investment than Betashares Asia. But when comparing it to its historical volatility, Beta Shares SPASX is 1.37 times less risky than Betashares Asia. It trades about 0.09 of its potential returns per unit of risk. Betashares Asia Technology is currently generating about 0.07 of returns per unit of risk over similar time horizon. If you would invest 672.00 in Betashares Asia Technology on September 24, 2024 and sell it today you would earn a total of 343.00 from holding Betashares Asia Technology or generate 51.04% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 99.8% |
Values | Daily Returns |
Beta Shares SPASX vs. Betashares Asia Technology
Performance |
Timeline |
Beta Shares SPASX |
Betashares Asia Tech |
Beta Shares and Betashares Asia Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Beta Shares and Betashares Asia
The main advantage of trading using opposite Beta Shares and Betashares Asia positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Beta Shares position performs unexpectedly, Betashares Asia 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 Betashares Asia will offset losses from the drop in Betashares Asia's long position.Beta Shares vs. iSharesGlobal 100 | Beta Shares vs. iShares Core SP | Beta Shares vs. Vanguard Total Market | Beta Shares vs. SPDR SP 500 |
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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 Headlines Timeline module to stay connected to all market stories and filter out noise. Drill down to analyze hype elasticity.
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