Correlation Between Manning Napier and Banking Fund
Can any of the company-specific risk be diversified away by investing in both Manning Napier and Banking Fund 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 Manning Napier and Banking Fund into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Manning Napier Diversified and Banking Fund Class, you can compare the effects of market volatilities on Manning Napier and Banking Fund 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 Manning Napier with a short position of Banking Fund. Check out your portfolio center. Please also check ongoing floating volatility patterns of Manning Napier and Banking Fund.
Diversification Opportunities for Manning Napier and Banking Fund
0.24 | Correlation Coefficient |
Modest diversification
The 3 months correlation between Manning and Banking is 0.24. Overlapping area represents the amount of risk that can be diversified away by holding Manning Napier Diversified and Banking Fund Class in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Banking Fund Class and Manning Napier 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 Manning Napier Diversified are associated (or correlated) with Banking Fund. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Banking Fund Class has no effect on the direction of Manning Napier i.e., Manning Napier and Banking Fund go up and down completely randomly.
Pair Corralation between Manning Napier and Banking Fund
Assuming the 90 days horizon Manning Napier is expected to generate 27.78 times less return on investment than Banking Fund. But when comparing it to its historical volatility, Manning Napier Diversified is 8.86 times less risky than Banking Fund. It trades about 0.03 of its potential returns per unit of risk. Banking Fund Class is currently generating about 0.08 of returns per unit of risk over similar time horizon. If you would invest 6,954 in Banking Fund Class on October 9, 2024 and sell it today you would earn a total of 2,042 from holding Banking Fund Class or generate 29.36% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Manning Napier Diversified vs. Banking Fund Class
Performance |
Timeline |
Manning Napier Diver |
Banking Fund Class |
Manning Napier and Banking Fund Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Manning Napier and Banking Fund
The main advantage of trading using opposite Manning Napier and Banking Fund positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Manning Napier position performs unexpectedly, Banking Fund 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 Banking Fund will offset losses from the drop in Banking Fund's long position.Manning Napier vs. Manning Napier Callodine | Manning Napier vs. Manning Napier Callodine | Manning Napier vs. Manning Napier Callodine | Manning Napier vs. Pro Blend Extended Term |
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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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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