Correlation Between Woolworths and Dicker Data

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

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

Diversification Opportunities for Woolworths and Dicker Data

0.62

Correlation Coefficient

Woolworths  Dicker Data

Poor diversification

The 3 months correlation between Woolworths and Dicker is 0.62. Overlapping area represents the amount of risk that can be diversified away by holding Woolworths and Dicker Data in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Dicker Data and Woolworths 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 Woolworths 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 Woolworths i.e., Woolworths and Dicker Data go up and down completely randomly.

Pair Corralation between Woolworths and Dicker Data

Assuming the 90 days trading horizon Woolworths is expected to under-perform the Dicker Data. But the stock apears to be less risky and, when comparing its historical volatility, Woolworths is 1.14 times less risky than Dicker Data. The stock trades about -0.16 of its potential returns per unit of risk. The Dicker Data is currently generating about -0.06 of returns per unit of risk over similar time horizon. If you would invest  893.00  in Dicker Data on September 12, 2024 and sell it today you would lose (54.00) from holding Dicker Data or give up 6.05% of portfolio value over 90 days.

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

Woolworths  vs.  Dicker Data

Woolworths

Risk-Adjusted Performance

0 of 100

Very Weak

Over the last 90 days Woolworths 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.

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 comparatively stable basic indicators, Dicker Data is not utilizing all of its potentials. The newest stock price uproar, may contribute to short-horizon losses for the private investors.

Pair Trading with Woolworths and Dicker Data

The main advantage of trading using opposite Woolworths and Dicker Data positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Woolworths 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 Woolworths 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 Volatility Analysis module to get historical volatility and risk analysis based on latest market data.