Correlation Between DFS Furniture and Invesco Physical
Can any of the company-specific risk be diversified away by investing in both DFS Furniture and Invesco Physical 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 DFS Furniture and Invesco Physical into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between DFS Furniture PLC and Invesco Physical Silver, you can compare the effects of market volatilities on DFS Furniture and Invesco Physical 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 DFS Furniture with a short position of Invesco Physical. Check out your portfolio center. Please also check ongoing floating volatility patterns of DFS Furniture and Invesco Physical.
Diversification Opportunities for DFS Furniture and Invesco Physical
-0.27 | Correlation Coefficient |
Very good diversification
The 3 months correlation between DFS and Invesco is -0.27. Overlapping area represents the amount of risk that can be diversified away by holding DFS Furniture PLC and Invesco Physical Silver in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Invesco Physical Silver and DFS Furniture 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 DFS Furniture PLC are associated (or correlated) with Invesco Physical. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Invesco Physical Silver has no effect on the direction of DFS Furniture i.e., DFS Furniture and Invesco Physical go up and down completely randomly.
Pair Corralation between DFS Furniture and Invesco Physical
Assuming the 90 days trading horizon DFS Furniture is expected to generate 1.05 times less return on investment than Invesco Physical. In addition to that, DFS Furniture is 1.13 times more volatile than Invesco Physical Silver. It trades about 0.05 of its total potential returns per unit of risk. Invesco Physical Silver is currently generating about 0.06 per unit of volatility. If you would invest 2,203 in Invesco Physical Silver on October 5, 2024 and sell it today you would earn a total of 616.00 from holding Invesco Physical Silver or generate 27.96% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
DFS Furniture PLC vs. Invesco Physical Silver
Performance |
Timeline |
DFS Furniture PLC |
Invesco Physical Silver |
DFS Furniture and Invesco Physical Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with DFS Furniture and Invesco Physical
The main advantage of trading using opposite DFS Furniture and Invesco Physical positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if DFS Furniture position performs unexpectedly, Invesco Physical 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 Invesco Physical will offset losses from the drop in Invesco Physical's long position.DFS Furniture vs. Volkswagen AG | DFS Furniture vs. Volkswagen AG Non Vtg | DFS Furniture vs. Deutsche Post AG | DFS Furniture vs. Compass Group PLC |
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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 Portfolio Rebalancing module to analyze risk-adjusted returns against different time horizons to find asset-allocation targets.
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