Correlation Between Great West and Small Midcap
Can any of the company-specific risk be diversified away by investing in both Great West and Small Midcap 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 Great West and Small Midcap into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Great West Loomis Sayles and Small Midcap Dividend Income, you can compare the effects of market volatilities on Great West and Small Midcap 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 Great West with a short position of Small Midcap. Check out your portfolio center. Please also check ongoing floating volatility patterns of Great West and Small Midcap.
Diversification Opportunities for Great West and Small Midcap
0.98 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between Great and Small is 0.98. Overlapping area represents the amount of risk that can be diversified away by holding Great West Loomis Sayles and Small Midcap Dividend Income in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Small Midcap Dividend and Great West 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 Great West Loomis Sayles are associated (or correlated) with Small Midcap. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Small Midcap Dividend has no effect on the direction of Great West i.e., Great West and Small Midcap go up and down completely randomly.
Pair Corralation between Great West and Small Midcap
Assuming the 90 days horizon Great West Loomis Sayles is expected to generate 1.35 times more return on investment than Small Midcap. However, Great West is 1.35 times more volatile than Small Midcap Dividend Income. It trades about 0.11 of its potential returns per unit of risk. Small Midcap Dividend Income is currently generating about 0.1 per unit of risk. If you would invest 3,887 in Great West Loomis Sayles on September 13, 2024 and sell it today you would earn a total of 231.00 from holding Great West Loomis Sayles or generate 5.94% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Strong |
| Accuracy | 100.0% |
| Values | Daily Returns |
Great West Loomis Sayles vs. Small Midcap Dividend Income
Performance |
| Timeline |
| Great West Loomis |
| Small Midcap Dividend |
Great West and Small Midcap Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Great West and Small Midcap
The main advantage of trading using opposite Great West and Small Midcap positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Great West position performs unexpectedly, Small Midcap 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 Small Midcap will offset losses from the drop in Small Midcap's long position.| Great West vs. Great West Securefoundation Balanced | Great West vs. Great West Lifetime 2020 | Great West vs. Great West Lifetime 2020 | Great West vs. Great West Lifetime 2020 |
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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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