Correlation Between Cavanal Hill and Dow Jones

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

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

Diversification Opportunities for Cavanal Hill and Dow Jones

0.91

Correlation Coefficient

Cavanal Hill  Dow Jones

Almost no diversification

The 3 months correlation between Cavanal and Dow is 0.91. Overlapping area represents the amount of risk that can be diversified away by holding Cavanal Hill Hedged 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 Cavanal Hill 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 Cavanal Hill Hedged 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 Cavanal Hill i.e., Cavanal Hill and Dow Jones go up and down completely randomly.

Pair Corralation between Cavanal Hill and Dow Jones

Assuming the 90 days horizon Cavanal Hill Hedged is expected to under-perform the Dow Jones. But the mutual fund apears to be less risky and, when comparing its historical volatility, Cavanal Hill Hedged is 1.12 times less risky than Dow Jones. The mutual fund trades about -0.07 of its potential returns per unit of risk. The Dow Jones Industrial is currently generating about -0.04 of returns per unit of risk over similar time horizon. If you would invest  4,257,373  in Dow Jones Industrial on December 28, 2024 and sell it today you would lose (98,983) from holding Dow Jones Industrial or give up 2.32% of portfolio value over 90 days.

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

Cavanal Hill Hedged  vs.  Dow Jones Industrial

Pair Trading with Cavanal Hill and Dow Jones

The main advantage of trading using opposite Cavanal Hill and Dow Jones positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Cavanal Hill 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.

The idea behind Cavanal Hill Hedged and Dow Jones Industrial 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.

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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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.