Correlation Between Retail Food and Dicker Data

Can any of the company-specific risk be diversified away by investing in both Retail Food and Dicker Data 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 Retail Food and Dicker Data into the same portfolio, which is an essential part of the fundamental portfolio management process.

By analyzing existing cross correlation between Retail Food Group and Dicker Data, you can compare the effects of market volatilities on Retail Food and Dicker Data 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 Retail Food with a short position of Dicker Data. Check out your portfolio center. Please also check ongoing floating volatility patterns of Retail Food and Dicker Data.

Diversification Opportunities for Retail Food and Dicker Data

-0.07

Correlation Coefficient

Retail Food  Dicker Data

Good diversification

The 3 months correlation between Retail and Dicker is -0.07. Overlapping area represents the amount of risk that can be diversified away by holding Retail Food Group and Dicker Data in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Dicker Data and Retail Food 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 Retail Food Group are associated (or correlated) with Dicker Data. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Dicker Data has no effect on the direction of Retail Food i.e., Retail Food and Dicker Data go up and down completely randomly.

Pair Corralation between Retail Food and Dicker Data

Assuming the 90 days trading horizon Retail Food Group is expected to generate 1.88 times more return on investment than Dicker Data. However, Retail Food is 1.88 times more volatile than Dicker Data. It trades about -0.01 of its potential returns per unit of risk. Dicker Data is currently generating about -0.12 per unit of risk. If you would invest  260.00  in Retail Food Group on October 10, 2024 and sell it today you would lose (8.00) from holding Retail Food Group or give up 3.08% of portfolio value over 90 days.

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

Retail Food Group  vs.  Dicker Data

Retail Food Group

Risk-Adjusted Performance

0 of 100

Very Weak

Over the last 90 days Retail Food Group has generated negative risk-adjusted returns adding no value to investors with long positions. In spite of comparatively stable technical and fundamental indicators, Retail Food is not utilizing all of its potentials. The newest stock price uproar, may contribute to short-horizon losses for the private investors.

Dicker Data

Risk-Adjusted Performance

0 of 100

Very Weak

Over the last 90 days Dicker Data has generated negative risk-adjusted returns adding no value to investors with long positions. In spite of latest uncertain performance, the Stock's basic indicators remain stable and the newest uproar on Wall Street may also be a sign of mid-term gains for the firm private investors.

Pair Trading with Retail Food and Dicker Data

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

The idea behind Retail Food Group and Dicker Data 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 Portfolio Dashboard module to portfolio dashboard that provides centralized access to all your investments.