Correlation Between George Putnam and Dow Jones
Can any of the company-specific risk be diversified away by investing in both George Putnam and Dow Jones 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 George Putnam and Dow Jones into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between George Putnam Fund and Dow Jones Industrial, you can compare the effects of market volatilities on George Putnam and Dow Jones 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 George Putnam with a short position of Dow Jones. Check out your portfolio center. Please also check ongoing floating volatility patterns of George Putnam and Dow Jones.
Diversification Opportunities for George Putnam and Dow Jones
0.82 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between George and Dow is 0.82. Overlapping area represents the amount of risk that can be diversified away by holding George Putnam Fund and Dow Jones Industrial in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Dow Jones Industrial and George Putnam 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 George Putnam Fund are associated (or correlated) with Dow Jones. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Dow Jones Industrial has no effect on the direction of George Putnam i.e., George Putnam and Dow Jones go up and down completely randomly.
Pair Corralation between George Putnam and Dow Jones
Assuming the 90 days horizon George Putnam is expected to generate 1.02 times less return on investment than Dow Jones. But when comparing it to its historical volatility, George Putnam Fund is 1.24 times less risky than Dow Jones. It trades about 0.11 of its potential returns per unit of risk. Dow Jones Industrial is currently generating about 0.09 of returns per unit of risk over similar time horizon. If you would invest 3,351,765 in Dow Jones Industrial on August 31, 2024 and sell it today you would earn a total of 1,139,300 from holding Dow Jones Industrial or generate 33.99% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Strong |
| Accuracy | 99.79% |
| Values | Daily Returns |
George Putnam Fund vs. Dow Jones Industrial
Performance |
| Timeline |
George Putnam and Dow Jones Volatility Contrast
Predicted Return Density |
| Returns |
George Putnam Fund
Pair trading matchups for George Putnam
Dow Jones Industrial
Pair trading matchups for Dow Jones
Pair Trading with George Putnam and Dow Jones
The main advantage of trading using opposite George Putnam and Dow Jones positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if George Putnam position performs unexpectedly, Dow Jones 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 Dow Jones will offset losses from the drop in Dow Jones' long position.| George Putnam vs. Jpmorgan Short Intermediate Municipal | George Putnam vs. T Rowe Price | George Putnam vs. Inflation Protected Bond Fund | George Putnam vs. Nuveen Arizona Municipal |
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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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