Correlation Between Optimum Small-mid and Optimum Large
Can any of the company-specific risk be diversified away by investing in both Optimum Small-mid and Optimum Large 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 Optimum Small-mid and Optimum Large into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Optimum Small Mid Cap and Optimum Large Cap, you can compare the effects of market volatilities on Optimum Small-mid and Optimum Large 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 Optimum Small-mid with a short position of Optimum Large. Check out your portfolio center. Please also check ongoing floating volatility patterns of Optimum Small-mid and Optimum Large.
Diversification Opportunities for Optimum Small-mid and Optimum Large
0.71 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Optimum and Optimum is 0.71. Overlapping area represents the amount of risk that can be diversified away by holding Optimum Small Mid Cap and Optimum Large Cap in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Optimum Large Cap and Optimum Small-mid 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 Optimum Small Mid Cap are associated (or correlated) with Optimum Large. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Optimum Large Cap has no effect on the direction of Optimum Small-mid i.e., Optimum Small-mid and Optimum Large go up and down completely randomly.
Pair Corralation between Optimum Small-mid and Optimum Large
Assuming the 90 days horizon Optimum Small Mid Cap is expected to under-perform the Optimum Large. In addition to that, Optimum Small-mid is 1.14 times more volatile than Optimum Large Cap. It trades about -0.31 of its total potential returns per unit of risk. Optimum Large Cap is currently generating about -0.06 per unit of volatility. If you would invest 2,454 in Optimum Large Cap on November 27, 2024 and sell it today you would lose (32.00) from holding Optimum Large Cap or give up 1.3% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Optimum Small Mid Cap vs. Optimum Large Cap
Performance |
| Timeline |
| Optimum Small Mid |
| Optimum Large Cap |
Optimum Small-mid and Optimum Large Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Optimum Small-mid and Optimum Large
The main advantage of trading using opposite Optimum Small-mid and Optimum Large positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Optimum Small-mid position performs unexpectedly, Optimum Large 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 Optimum Large will offset losses from the drop in Optimum Large's long position.| Optimum Small-mid vs. Blackrock Moderate Prepared | Optimum Small-mid vs. Tiaa Cref Lifestyle Moderate | Optimum Small-mid vs. Blackrock Retirement Income | Optimum Small-mid vs. Jp Morgan Smartretirement |
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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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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