Correlation Between Large-cap Growth and Us Government
Can any of the company-specific risk be diversified away by investing in both Large-cap Growth and Us Government 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 Large-cap Growth and Us Government into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Large Cap Growth Profund and Us Government Securities, you can compare the effects of market volatilities on Large-cap Growth and Us Government 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 Large-cap Growth with a short position of Us Government. Check out your portfolio center. Please also check ongoing floating volatility patterns of Large-cap Growth and Us Government.
Diversification Opportunities for Large-cap Growth and Us Government
-0.65 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Large-cap and UGSCX is -0.65. Overlapping area represents the amount of risk that can be diversified away by holding Large Cap Growth Profund and Us Government Securities in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Us Government Securities and Large-cap 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 Large Cap Growth Profund are associated (or correlated) with Us Government. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Us Government Securities has no effect on the direction of Large-cap Growth i.e., Large-cap Growth and Us Government go up and down completely randomly.
Pair Corralation between Large-cap Growth and Us Government
Assuming the 90 days horizon Large Cap Growth Profund is expected to under-perform the Us Government. In addition to that, Large-cap Growth is 4.44 times more volatile than Us Government Securities. It trades about -0.11 of its total potential returns per unit of risk. Us Government Securities is currently generating about 0.15 per unit of volatility. If you would invest 1,157 in Us Government Securities on December 20, 2024 and sell it today you would earn a total of 34.00 from holding Us Government Securities or generate 2.94% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Large Cap Growth Profund vs. Us Government Securities
Performance |
Timeline |
Large Cap Growth |
Us Government Securities |
Large-cap Growth and Us Government Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Large-cap Growth and Us Government
The main advantage of trading using opposite Large-cap Growth and Us Government positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Large-cap Growth position performs unexpectedly, Us Government 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 Us Government will offset losses from the drop in Us Government's long position.Large-cap Growth vs. Siit Ultra Short | Large-cap Growth vs. Vanguard Intermediate Term Bond | Large-cap Growth vs. Legg Mason Partners | Large-cap Growth vs. Intermediate Bond Fund |
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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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