Correlation Between Needham Growth and Buffalo High
Can any of the company-specific risk be diversified away by investing in both Needham Growth and Buffalo High 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 Needham Growth and Buffalo High into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Needham Growth and Buffalo High Yield, you can compare the effects of market volatilities on Needham Growth and Buffalo High 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 Needham Growth with a short position of Buffalo High. Check out your portfolio center. Please also check ongoing floating volatility patterns of Needham Growth and Buffalo High.
Diversification Opportunities for Needham Growth and Buffalo High
-0.32 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Needham and Buffalo is -0.32. Overlapping area represents the amount of risk that can be diversified away by holding Needham Growth and Buffalo High Yield in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Buffalo High Yield and Needham Growth 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 Needham Growth are associated (or correlated) with Buffalo High. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Buffalo High Yield has no effect on the direction of Needham Growth i.e., Needham Growth and Buffalo High go up and down completely randomly.
Pair Corralation between Needham Growth and Buffalo High
Assuming the 90 days horizon Needham Growth is expected to under-perform the Buffalo High. In addition to that, Needham Growth is 4.51 times more volatile than Buffalo High Yield. It trades about -0.12 of its total potential returns per unit of risk. Buffalo High Yield is currently generating about -0.19 per unit of volatility. If you would invest 1,082 in Buffalo High Yield on September 24, 2024 and sell it today you would lose (13.00) from holding Buffalo High Yield or give up 1.2% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Needham Growth vs. Buffalo High Yield
Performance |
Timeline |
Needham Growth |
Buffalo High Yield |
Needham Growth and Buffalo High Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Needham Growth and Buffalo High
The main advantage of trading using opposite Needham Growth and Buffalo High positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Needham Growth position performs unexpectedly, Buffalo High 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 Buffalo High will offset losses from the drop in Buffalo High's long position.Needham Growth vs. Buffalo High Yield | Needham Growth vs. Janus High Yield Fund | Needham Growth vs. Inverse High Yield | Needham Growth vs. Neuberger Berman Income |
Buffalo High vs. Buffalo Flexible Income | Buffalo High vs. Buffalo Growth Fund | Buffalo High vs. Buffalo Large Cap | Buffalo High vs. Buffalo Mid Cap |
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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