Correlation Between Calvert High and Baillie Gifford
Can any of the company-specific risk be diversified away by investing in both Calvert High and Baillie Gifford 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 Calvert High and Baillie Gifford into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Calvert High Yield and Baillie Gifford Emerging, you can compare the effects of market volatilities on Calvert High and Baillie Gifford 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 Calvert High with a short position of Baillie Gifford. Check out your portfolio center. Please also check ongoing floating volatility patterns of Calvert High and Baillie Gifford.
Diversification Opportunities for Calvert High and Baillie Gifford
-0.06 | Correlation Coefficient |
Good diversification
The 3 months correlation between Calvert and Baillie is -0.06. Overlapping area represents the amount of risk that can be diversified away by holding Calvert High Yield and Baillie Gifford Emerging in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Baillie Gifford Emerging and Calvert High 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 Calvert High Yield are associated (or correlated) with Baillie Gifford. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Baillie Gifford Emerging has no effect on the direction of Calvert High i.e., Calvert High and Baillie Gifford go up and down completely randomly.
Pair Corralation between Calvert High and Baillie Gifford
Assuming the 90 days horizon Calvert High Yield is expected to generate 0.13 times more return on investment than Baillie Gifford. However, Calvert High Yield is 7.66 times less risky than Baillie Gifford. It trades about 0.15 of its potential returns per unit of risk. Baillie Gifford Emerging is currently generating about -0.06 per unit of risk. If you would invest 2,411 in Calvert High Yield on October 7, 2024 and sell it today you would earn a total of 69.00 from holding Calvert High Yield or generate 2.86% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Calvert High Yield vs. Baillie Gifford Emerging
Performance |
Timeline |
Calvert High Yield |
Baillie Gifford Emerging |
Calvert High and Baillie Gifford Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Calvert High and Baillie Gifford
The main advantage of trading using opposite Calvert High and Baillie Gifford positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Calvert High position performs unexpectedly, Baillie Gifford 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 Baillie Gifford will offset losses from the drop in Baillie Gifford's long position.Calvert High vs. Ashmore Emerging Markets | Calvert High vs. Alphacentric Hedged Market | Calvert High vs. Kinetics Market Opportunities | Calvert High vs. Artisan Developing World |
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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 Volatility Analysis module to get historical volatility and risk analysis based on latest market data.
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