Correlation Between Dow Jones and High Yield

Can any of the company-specific risk be diversified away by investing in both Dow Jones and High Yield 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 Dow Jones and High Yield into the same portfolio, which is an essential part of the fundamental portfolio management process.

By analyzing existing cross correlation between Dow Jones Industrial and High Yield Fund R6, you can compare the effects of market volatilities on Dow Jones and High Yield 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 Dow Jones with a short position of High Yield. Check out your portfolio center. Please also check ongoing floating volatility patterns of Dow Jones and High Yield.

Diversification Opportunities for Dow Jones and High Yield

0.56

Correlation Coefficient

Dow Jones  High Yield

Very weak diversification

The 3 months correlation between Dow and High is 0.56. Overlapping area represents the amount of risk that can be diversified away by holding Dow Jones Industrial and High Yield Fund R6 in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on High Yield Fund and Dow Jones 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 Dow Jones Industrial are associated (or correlated) with High Yield. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of High Yield Fund has no effect on the direction of Dow Jones i.e., Dow Jones and High Yield go up and down completely randomly.

Pair Corralation between Dow Jones and High Yield

Assuming the 90 days trading horizon Dow Jones Industrial is expected to generate 4.64 times more return on investment than High Yield. However, Dow Jones is 4.64 times more volatile than High Yield Fund R6. It trades about 0.13 of its potential returns per unit of risk. High Yield Fund R6 is currently generating about 0.06 per unit of risk. If you would invest  4,139,378  in Dow Jones Industrial on September 13, 2024 and sell it today you would earn a total of  252,034  from holding Dow Jones Industrial or generate 6.09% return on investment over 90 days.

Time Period	3 Months [change]
Direction	Moves Together
Strength	Weak
Accuracy	100.0%
Values	Daily Returns

Dow Jones Industrial  vs.  High Yield Fund R6

Pair Trading with Dow Jones and High Yield

The main advantage of trading using opposite Dow Jones and High Yield positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Dow Jones position performs unexpectedly, High Yield 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 High Yield will offset losses from the drop in High Yield's long position.

The idea behind Dow Jones Industrial and High Yield Fund R6 pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.

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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.