Correlation Between Baillie Gifford and Long Term
Can any of the company-specific risk be diversified away by investing in both Baillie Gifford and Long Term 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 Baillie Gifford and Long Term into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Baillie Gifford China and The Long Term, you can compare the effects of market volatilities on Baillie Gifford and Long Term 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 Baillie Gifford with a short position of Long Term. Check out your portfolio center. Please also check ongoing floating volatility patterns of Baillie Gifford and Long Term.
Diversification Opportunities for Baillie Gifford and Long Term
0.77 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Baillie and Long is 0.77. Overlapping area represents the amount of risk that can be diversified away by holding Baillie Gifford China and The Long Term in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Long Term and Baillie Gifford 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 Baillie Gifford China are associated (or correlated) with Long Term. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Long Term has no effect on the direction of Baillie Gifford i.e., Baillie Gifford and Long Term go up and down completely randomly.
Pair Corralation between Baillie Gifford and Long Term
Assuming the 90 days horizon Baillie Gifford China is expected to under-perform the Long Term. In addition to that, Baillie Gifford is 1.55 times more volatile than The Long Term. It trades about -0.18 of its total potential returns per unit of risk. The Long Term is currently generating about 0.23 per unit of volatility. If you would invest 3,194 in The Long Term on August 27, 2024 and sell it today you would earn a total of 187.00 from holding The Long Term or generate 5.85% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Baillie Gifford China vs. The Long Term
Performance |
Timeline |
Baillie Gifford China |
Long Term |
Baillie Gifford and Long Term Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Baillie Gifford and Long Term
The main advantage of trading using opposite Baillie Gifford and Long Term positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Baillie Gifford position performs unexpectedly, Long Term 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 Long Term will offset losses from the drop in Long Term's long position.Baillie Gifford vs. The Eafe Pure | Baillie Gifford vs. The Long Term | Baillie Gifford vs. Baillie Gifford International | Baillie Gifford vs. Baillie Gifford International |
Long Term vs. The Eafe Pure | Long Term vs. Baillie Gifford International | Long Term vs. Baillie Gifford International | Long Term vs. Baillie Gifford China |
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 Suggestion module to get suggestions outside of your existing asset allocation including your own model portfolios.
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