Correlation Between Boston Partners and Dow Jones
Can any of the company-specific risk be diversified away by investing in both Boston Partners 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 Boston Partners and Dow Jones into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Boston Partners Longshort and Dow Jones Industrial, you can compare the effects of market volatilities on Boston Partners 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 Boston Partners with a short position of Dow Jones. Check out your portfolio center. Please also check ongoing floating volatility patterns of Boston Partners and Dow Jones.
Diversification Opportunities for Boston Partners and Dow Jones
0.46 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Boston and Dow is 0.46. Overlapping area represents the amount of risk that can be diversified away by holding Boston Partners Longshort 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 Boston Partners 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 Boston Partners Longshort 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 Boston Partners i.e., Boston Partners and Dow Jones go up and down completely randomly.
Pair Corralation between Boston Partners and Dow Jones
Assuming the 90 days horizon Boston Partners Longshort is expected to under-perform the Dow Jones. In addition to that, Boston Partners is 4.21 times more volatile than Dow Jones Industrial. It trades about -0.25 of its total potential returns per unit of risk. Dow Jones Industrial is currently generating about 0.07 per unit of volatility. If you would invest 4,338,960 in Dow Jones Industrial on September 18, 2024 and sell it today you would earn a total of 32,788 from holding Dow Jones Industrial or generate 0.76% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Boston Partners Longshort vs. Dow Jones Industrial
Performance |
| Timeline |
Boston Partners and Dow Jones Volatility Contrast
Predicted Return Density |
| Returns |
Boston Partners Longshort
Pair trading matchups for Boston Partners
Dow Jones Industrial
Pair trading matchups for Dow Jones
Pair Trading with Boston Partners and Dow Jones
The main advantage of trading using opposite Boston Partners and Dow Jones positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Boston Partners 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.| Boston Partners vs. Blackrock Midcap Index | Boston Partners vs. The Arbitrage Fund | Boston Partners vs. Calamos Market Neutral | Boston Partners vs. Diamond Hill Long Short |
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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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