Correlation Between Global Core and Mid Cap
Can any of the company-specific risk be diversified away by investing in both Global Core and Mid Cap 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 Core and Mid Cap into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Global E Portfolio and Mid Cap Growth, you can compare the effects of market volatilities on Global Core and Mid Cap 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 Core with a short position of Mid Cap. Check out your portfolio center. Please also check ongoing floating volatility patterns of Global Core and Mid Cap.
Diversification Opportunities for Global Core and Mid Cap
0.89 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Global and Mid is 0.89. Overlapping area represents the amount of risk that can be diversified away by holding Global E Portfolio and Mid Cap Growth in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Mid Cap Growth and Global Core 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 E Portfolio are associated (or correlated) with Mid Cap. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Mid Cap Growth has no effect on the direction of Global Core i.e., Global Core and Mid Cap go up and down completely randomly.
Pair Corralation between Global Core and Mid Cap
Assuming the 90 days horizon Global E Portfolio is expected to under-perform the Mid Cap. But the mutual fund apears to be less risky and, when comparing its historical volatility, Global E Portfolio is 1.78 times less risky than Mid Cap. The mutual fund trades about -0.04 of its potential returns per unit of risk. The Mid Cap Growth is currently generating about -0.02 of returns per unit of risk over similar time horizon. If you would invest 2,176 in Mid Cap Growth on December 28, 2024 and sell it today you would lose (85.00) from holding Mid Cap Growth or give up 3.91% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 98.36% |
Values | Daily Returns |
Global E Portfolio vs. Mid Cap Growth
Performance |
Timeline |
Global E Portfolio |
Mid Cap Growth |
Global Core and Mid Cap Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Global Core and Mid Cap
The main advantage of trading using opposite Global Core and Mid Cap positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Global Core position performs unexpectedly, Mid Cap 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 Mid Cap will offset losses from the drop in Mid Cap's long position.Global Core vs. Pace High Yield | Global Core vs. Western Asset High | Global Core vs. Chartwell Short Duration | Global Core vs. Metropolitan West High |
Mid Cap vs. Growth Portfolio Class | Mid Cap vs. Small Pany Growth | Mid Cap vs. Emerging Markets Portfolio | Mid Cap vs. Morgan Stanley Multi |
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 My Watchlist Analysis module to analyze my current watchlist and to refresh optimization strategy. Macroaxis watchlist is based on self-learning algorithm to remember stocks you like.
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