Correlation Between Games Workshop and Dominos Pizza
Can any of the company-specific risk be diversified away by investing in both Games Workshop and Dominos Pizza 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 Games Workshop and Dominos Pizza into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Games Workshop Group and Dominos Pizza Group, you can compare the effects of market volatilities on Games Workshop and Dominos Pizza 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 Games Workshop with a short position of Dominos Pizza. Check out your portfolio center. Please also check ongoing floating volatility patterns of Games Workshop and Dominos Pizza.
Diversification Opportunities for Games Workshop and Dominos Pizza
0.66 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Games and Dominos is 0.66. Overlapping area represents the amount of risk that can be diversified away by holding Games Workshop Group and Dominos Pizza Group in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Dominos Pizza Group and Games Workshop 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 Games Workshop Group are associated (or correlated) with Dominos Pizza. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Dominos Pizza Group has no effect on the direction of Games Workshop i.e., Games Workshop and Dominos Pizza go up and down completely randomly.
Pair Corralation between Games Workshop and Dominos Pizza
Assuming the 90 days trading horizon Games Workshop Group is expected to generate 1.33 times more return on investment than Dominos Pizza. However, Games Workshop is 1.33 times more volatile than Dominos Pizza Group. It trades about 0.17 of its potential returns per unit of risk. Dominos Pizza Group is currently generating about 0.07 per unit of risk. If you would invest 1,043,562 in Games Workshop Group on September 20, 2024 and sell it today you would earn a total of 296,438 from holding Games Workshop Group or generate 28.41% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Games Workshop Group vs. Dominos Pizza Group
Performance |
Timeline |
Games Workshop Group |
Dominos Pizza Group |
Games Workshop and Dominos Pizza Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Games Workshop and Dominos Pizza
The main advantage of trading using opposite Games Workshop and Dominos Pizza positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Games Workshop position performs unexpectedly, Dominos Pizza 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 Dominos Pizza will offset losses from the drop in Dominos Pizza's long position.Games Workshop vs. Catalyst Media Group | Games Workshop vs. CATLIN GROUP | Games Workshop vs. Tamburi Investment Partners | Games Workshop vs. Magnora ASA |
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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 My Watchlist Analysis module to analyze my current watchlist and to refresh optimization strategy. Macroaxis watchlist is based on self-learning algorithm to remember stocks you like.
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