Correlation Between Scientific Games and DFS Furniture
Can any of the company-specific risk be diversified away by investing in both Scientific Games and DFS Furniture 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 Scientific Games and DFS Furniture into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Scientific Games and DFS Furniture PLC, you can compare the effects of market volatilities on Scientific Games and DFS Furniture 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 Scientific Games with a short position of DFS Furniture. Check out your portfolio center. Please also check ongoing floating volatility patterns of Scientific Games and DFS Furniture.
Diversification Opportunities for Scientific Games and DFS Furniture
0.1 | Correlation Coefficient |
Average diversification
The 3 months correlation between Scientific and DFS is 0.1. Overlapping area represents the amount of risk that can be diversified away by holding Scientific Games and DFS Furniture PLC in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on DFS Furniture PLC and Scientific Games 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 Scientific Games are associated (or correlated) with DFS Furniture. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of DFS Furniture PLC has no effect on the direction of Scientific Games i.e., Scientific Games and DFS Furniture go up and down completely randomly.
Pair Corralation between Scientific Games and DFS Furniture
Assuming the 90 days horizon Scientific Games is expected to generate 1.23 times more return on investment than DFS Furniture. However, Scientific Games is 1.23 times more volatile than DFS Furniture PLC. It trades about 0.14 of its potential returns per unit of risk. DFS Furniture PLC is currently generating about 0.02 per unit of risk. If you would invest 8,200 in Scientific Games on December 11, 2024 and sell it today you would earn a total of 1,300 from holding Scientific Games or generate 15.85% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Scientific Games vs. DFS Furniture PLC
Performance |
| Timeline |
| Scientific Games |
| DFS Furniture PLC |
Scientific Games and DFS Furniture Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Scientific Games and DFS Furniture
The main advantage of trading using opposite Scientific Games and DFS Furniture positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Scientific Games position performs unexpectedly, DFS Furniture 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 DFS Furniture will offset losses from the drop in DFS Furniture's long position.| Scientific Games vs. FAST RETAIL ADR | Scientific Games vs. SALESFORCE INC CDR | Scientific Games vs. CARSALESCOM | Scientific Games vs. ZhongAn Online P |
| DFS Furniture vs. Lendlease Group | DFS Furniture vs. LOANDEPOT INC A | DFS Furniture vs. Comba Telecom Systems | DFS Furniture vs. Major Drilling Group |
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 Performance Analysis module to check effects of mean-variance optimization against your current asset allocation.
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