Correlation Between Putnam High and Allianzgi Short
Can any of the company-specific risk be diversified away by investing in both Putnam High and Allianzgi Short 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 Putnam High and Allianzgi Short into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Putnam High Income and Allianzgi Short Duration, you can compare the effects of market volatilities on Putnam High and Allianzgi Short 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 Putnam High with a short position of Allianzgi Short. Check out your portfolio center. Please also check ongoing floating volatility patterns of Putnam High and Allianzgi Short.
Diversification Opportunities for Putnam High and Allianzgi Short
0.89 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Putnam and Allianzgi is 0.89. Overlapping area represents the amount of risk that can be diversified away by holding Putnam High Income and Allianzgi Short Duration in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Allianzgi Short Duration and Putnam 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 Putnam High Income are associated (or correlated) with Allianzgi Short. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Allianzgi Short Duration has no effect on the direction of Putnam High i.e., Putnam High and Allianzgi Short go up and down completely randomly.
Pair Corralation between Putnam High and Allianzgi Short
Considering the 90-day investment horizon Putnam High Income is expected to generate 4.9 times more return on investment than Allianzgi Short. However, Putnam High is 4.9 times more volatile than Allianzgi Short Duration. It trades about 0.18 of its potential returns per unit of risk. Allianzgi Short Duration is currently generating about 0.4 per unit of risk. If you would invest 660.00 in Putnam High Income on August 27, 2024 and sell it today you would earn a total of 12.00 from holding Putnam High Income or generate 1.82% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Putnam High Income vs. Allianzgi Short Duration
Performance |
Timeline |
Putnam High Income |
Allianzgi Short Duration |
Putnam High and Allianzgi Short Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Putnam High and Allianzgi Short
The main advantage of trading using opposite Putnam High and Allianzgi Short positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Putnam High position performs unexpectedly, Allianzgi Short 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 Allianzgi Short will offset losses from the drop in Allianzgi Short's long position.Putnam High vs. RiverNorthDoubleLine Strategic Opportunity | Putnam High vs. Cornerstone Strategic Return | Putnam High vs. Oxford Lane Capital | Putnam High vs. Horizon Technology Finance |
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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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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