Correlation Between Sterling Capital and Small Company
Can any of the company-specific risk be diversified away by investing in both Sterling Capital and Small Company 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 Sterling Capital and Small Company into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Sterling Capital South and Small Pany Growth, you can compare the effects of market volatilities on Sterling Capital and Small Company 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 Sterling Capital with a short position of Small Company. Check out your portfolio center. Please also check ongoing floating volatility patterns of Sterling Capital and Small Company.
Diversification Opportunities for Sterling Capital and Small Company
-0.43 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Sterling and Small is -0.43. Overlapping area represents the amount of risk that can be diversified away by holding Sterling Capital South and Small Pany Growth in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Small Pany Growth and Sterling Capital 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 Sterling Capital South are associated (or correlated) with Small Company. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Small Pany Growth has no effect on the direction of Sterling Capital i.e., Sterling Capital and Small Company go up and down completely randomly.
Pair Corralation between Sterling Capital and Small Company
Assuming the 90 days horizon Sterling Capital South is expected to generate 0.07 times more return on investment than Small Company. However, Sterling Capital South is 13.5 times less risky than Small Company. It trades about 0.06 of its potential returns per unit of risk. Small Pany Growth is currently generating about -0.08 per unit of risk. If you would invest 1,035 in Sterling Capital South on December 20, 2024 and sell it today you would earn a total of 6.00 from holding Sterling Capital South or generate 0.58% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 98.33% |
Values | Daily Returns |
Sterling Capital South vs. Small Pany Growth
Performance |
Timeline |
Sterling Capital South |
Small Pany Growth |
Sterling Capital and Small Company Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Sterling Capital and Small Company
The main advantage of trading using opposite Sterling Capital and Small Company positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Sterling Capital position performs unexpectedly, Small Company 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 Company will offset losses from the drop in Small Company's long position.Sterling Capital vs. Auer Growth Fund | Sterling Capital vs. Aam Select Income | Sterling Capital vs. Artisan Mid Cap | Sterling Capital vs. Kirr Marbach Partners |
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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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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