Correlation Between Aqr Long and Fidelity Series
Can any of the company-specific risk be diversified away by investing in both Aqr Long and Fidelity Series 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 Aqr Long and Fidelity Series into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Aqr Long Short Equity and Fidelity Series 1000, you can compare the effects of market volatilities on Aqr Long and Fidelity Series 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 Aqr Long with a short position of Fidelity Series. Check out your portfolio center. Please also check ongoing floating volatility patterns of Aqr Long and Fidelity Series.
Diversification Opportunities for Aqr Long and Fidelity Series
0.49 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Aqr and Fidelity is 0.49. Overlapping area represents the amount of risk that can be diversified away by holding Aqr Long Short Equity and Fidelity Series 1000 in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Fidelity Series 1000 and Aqr Long 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 Aqr Long Short Equity are associated (or correlated) with Fidelity Series. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Fidelity Series 1000 has no effect on the direction of Aqr Long i.e., Aqr Long and Fidelity Series go up and down completely randomly.
Pair Corralation between Aqr Long and Fidelity Series
Assuming the 90 days horizon Aqr Long Short Equity is expected to generate 0.66 times more return on investment than Fidelity Series. However, Aqr Long Short Equity is 1.51 times less risky than Fidelity Series. It trades about 0.2 of its potential returns per unit of risk. Fidelity Series 1000 is currently generating about 0.07 per unit of risk. If you would invest 1,034 in Aqr Long Short Equity on September 19, 2024 and sell it today you would earn a total of 654.00 from holding Aqr Long Short Equity or generate 63.25% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Aqr Long Short Equity vs. Fidelity Series 1000
Performance |
Timeline |
Aqr Long Short |
Fidelity Series 1000 |
Aqr Long and Fidelity Series Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Aqr Long and Fidelity Series
The main advantage of trading using opposite Aqr Long and Fidelity Series positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Aqr Long position performs unexpectedly, Fidelity Series 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 Fidelity Series will offset losses from the drop in Fidelity Series' long position.Aqr Long vs. Aqr Large Cap | Aqr Long vs. Aqr Large Cap | Aqr Long vs. Aqr International Defensive | Aqr Long vs. Aqr International Defensive |
Fidelity Series vs. Investec Emerging Markets | Fidelity Series vs. Aqr Long Short Equity | Fidelity Series vs. Ep Emerging Markets | Fidelity Series vs. Extended Market Index |
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 Price Transformation module to use Price Transformation models to analyze the depth of different equity instruments across global markets.
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