Correlation Between Dow Jones and Shift4 Payments

Can any of the company-specific risk be diversified away by investing in both Dow Jones and Shift4 Payments 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 Shift4 Payments 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 Shift4 Payments, you can compare the effects of market volatilities on Dow Jones and Shift4 Payments 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 Shift4 Payments. Check out your portfolio center. Please also check ongoing floating volatility patterns of Dow Jones and Shift4 Payments.

Diversification Opportunities for Dow Jones and Shift4 Payments

0.93

Correlation Coefficient

Dow Jones  Shift4 Payments

Almost no diversification

The 3 months correlation between Dow and Shift4 is 0.93. Overlapping area represents the amount of risk that can be diversified away by holding Dow Jones Industrial and Shift4 Payments in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Shift4 Payments 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 Shift4 Payments. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Shift4 Payments has no effect on the direction of Dow Jones i.e., Dow Jones and Shift4 Payments go up and down completely randomly.

Pair Corralation between Dow Jones and Shift4 Payments

Assuming the 90 days trading horizon Dow Jones Industrial is expected to generate 0.14 times more return on investment than Shift4 Payments. However, Dow Jones Industrial is 6.9 times less risky than Shift4 Payments. It trades about -0.01 of its potential returns per unit of risk. Shift4 Payments is currently generating about -0.06 per unit of risk. If you would invest  4,429,313  in Dow Jones Industrial on September 12, 2024 and sell it today you would lose (4,530) from holding Dow Jones Industrial or give up 0.1% of portfolio value over 90 days.

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

Dow Jones Industrial  vs.  Shift4 Payments

Pair Trading with Dow Jones and Shift4 Payments

The main advantage of trading using opposite Dow Jones and Shift4 Payments positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Dow Jones position performs unexpectedly, Shift4 Payments 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 Shift4 Payments will offset losses from the drop in Shift4 Payments' long position.

The idea behind Dow Jones Industrial and Shift4 Payments 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 Valuation module to check real value of public entities based on technical and fundamental data.