Correlation Between Pax Balanced and Green Century
Can any of the company-specific risk be diversified away by investing in both Pax Balanced and Green Century 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 Pax Balanced and Green Century into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Pax Balanced Fund and Green Century Balanced, you can compare the effects of market volatilities on Pax Balanced and Green Century 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 Pax Balanced with a short position of Green Century. Check out your portfolio center. Please also check ongoing floating volatility patterns of Pax Balanced and Green Century.
Diversification Opportunities for Pax Balanced and Green Century
0.64 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Pax and GREEN is 0.64. Overlapping area represents the amount of risk that can be diversified away by holding Pax Balanced Fund and Green Century Balanced in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Green Century Balanced and Pax Balanced 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 Pax Balanced Fund are associated (or correlated) with Green Century. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Green Century Balanced has no effect on the direction of Pax Balanced i.e., Pax Balanced and Green Century go up and down completely randomly.
Pair Corralation between Pax Balanced and Green Century
Assuming the 90 days horizon Pax Balanced Fund is expected to generate 0.55 times more return on investment than Green Century. However, Pax Balanced Fund is 1.82 times less risky than Green Century. It trades about -0.05 of its potential returns per unit of risk. Green Century Balanced is currently generating about -0.14 per unit of risk. If you would invest 2,598 in Pax Balanced Fund on December 27, 2024 and sell it today you would lose (45.00) from holding Pax Balanced Fund or give up 1.73% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Pax Balanced Fund vs. Green Century Balanced
Performance |
Timeline |
Pax Balanced |
Green Century Balanced |
Pax Balanced and Green Century Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Pax Balanced and Green Century
The main advantage of trading using opposite Pax Balanced and Green Century positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Pax Balanced position performs unexpectedly, Green Century 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 Green Century will offset losses from the drop in Green Century's long position.Pax Balanced vs. Pax Esg Beta | Pax Balanced vs. Pax High Yield | Pax Balanced vs. Domini Impact Equity | Pax Balanced vs. Neuberger Berman Socially |
Green Century vs. Green Century Equity | Green Century vs. Portfolio 21 Global | Green Century vs. New Alternatives Fund | Green Century vs. Pax Balanced Fund |
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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