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
-0.2 | Correlation Coefficient |
Good diversification
The 3 months correlation between Retail and Dicker is -0.2. 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 1.73 times more return on investment than Dicker Data. However, Retail Food is 1.73 times more volatile than Dicker Data. It trades about 0.02 of its potential returns per unit of risk. Dicker Data is currently generating about -0.01 per unit of risk. If you would invest 7.00 in Retail Food Group on August 26, 2024 and sell it today you would earn a total of 0.20 from holding Retail Food Group or generate 2.86% return on investment 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
Performance |
| Timeline |
| Retail Food Group |
| Dicker Data |
Retail Food and Dicker Data Volatility Contrast
Predicted Return Density |
| Returns |
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.| Retail Food vs. Summit Resources Limited | Retail Food vs. Ecofibre | Retail Food vs. iShares Global Healthcare | Retail Food vs. Adriatic Metals Plc |
| Dicker Data vs. Greenvale Energy | Dicker Data vs. Summit Resources Limited | Dicker Data vs. Ecofibre | Dicker Data vs. iShares Global Healthcare |
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 Portfolio Diagnostics module to use generated alerts and portfolio events aggregator to diagnose current holdings.
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