Correlation Between Matthews China and FT Cboe
Can any of the company-specific risk be diversified away by investing in both Matthews China and FT Cboe 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 Matthews China and FT Cboe into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Matthews China Discovery and FT Cboe Vest, you can compare the effects of market volatilities on Matthews China and FT Cboe 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 Matthews China with a short position of FT Cboe. Check out your portfolio center. Please also check ongoing floating volatility patterns of Matthews China and FT Cboe.
Diversification Opportunities for Matthews China and FT Cboe
0.58 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Matthews and DJUN is 0.58. Overlapping area represents the amount of risk that can be diversified away by holding Matthews China Discovery and FT Cboe Vest in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on FT Cboe Vest and Matthews China 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 Matthews China Discovery are associated (or correlated) with FT Cboe. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of FT Cboe Vest has no effect on the direction of Matthews China i.e., Matthews China and FT Cboe go up and down completely randomly.
Pair Corralation between Matthews China and FT Cboe
Given the investment horizon of 90 days Matthews China Discovery is expected to generate 3.54 times more return on investment than FT Cboe. However, Matthews China is 3.54 times more volatile than FT Cboe Vest. It trades about 0.09 of its potential returns per unit of risk. FT Cboe Vest is currently generating about 0.0 per unit of risk. If you would invest 2,558 in Matthews China Discovery on December 1, 2024 and sell it today you would earn a total of 222.00 from holding Matthews China Discovery or generate 8.68% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Matthews China Discovery vs. FT Cboe Vest
Performance |
Timeline |
Matthews China Discovery |
FT Cboe Vest |
Matthews China and FT Cboe Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Matthews China and FT Cboe
The main advantage of trading using opposite Matthews China and FT Cboe positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Matthews China position performs unexpectedly, FT Cboe 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 FT Cboe will offset losses from the drop in FT Cboe's long position.Matthews China vs. JPMorgan Fundamental Data | Matthews China vs. Vanguard Mid Cap Index | Matthews China vs. SPDR SP 400 | Matthews China vs. SPDR SP 400 |
FT Cboe vs. First Trust Exchange Traded | FT Cboe vs. FT Cboe Vest | FT Cboe vs. FT Cboe Vest | FT Cboe vs. FT Cboe Vest |
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 Idea Breakdown module to analyze constituents of all Macroaxis ideas. Macroaxis investment ideas are predefined, sector-focused investing themes.
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