Correlation Between Qurate Retail and Flow Traders
Can any of the company-specific risk be diversified away by investing in both Qurate Retail and Flow Traders 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 Qurate Retail and Flow Traders into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Qurate Retail Series and Flow Traders NV, you can compare the effects of market volatilities on Qurate Retail and Flow Traders 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 Qurate Retail with a short position of Flow Traders. Check out your portfolio center. Please also check ongoing floating volatility patterns of Qurate Retail and Flow Traders.
Diversification Opportunities for Qurate Retail and Flow Traders
-0.35 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Qurate and Flow is -0.35. Overlapping area represents the amount of risk that can be diversified away by holding Qurate Retail Series and Flow Traders NV in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Flow Traders NV and Qurate Retail 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 Qurate Retail Series are associated (or correlated) with Flow Traders. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Flow Traders NV has no effect on the direction of Qurate Retail i.e., Qurate Retail and Flow Traders go up and down completely randomly.
Pair Corralation between Qurate Retail and Flow Traders
Assuming the 90 days trading horizon Qurate Retail Series is expected to under-perform the Flow Traders. In addition to that, Qurate Retail is 3.72 times more volatile than Flow Traders NV. It trades about -0.17 of its total potential returns per unit of risk. Flow Traders NV is currently generating about 0.06 per unit of volatility. If you would invest 2,103 in Flow Traders NV on August 28, 2024 and sell it today you would earn a total of 34.00 from holding Flow Traders NV or generate 1.62% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Qurate Retail Series vs. Flow Traders NV
Performance |
| Timeline |
| Qurate Retail Series |
| Flow Traders NV |
Qurate Retail and Flow Traders Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Qurate Retail and Flow Traders
The main advantage of trading using opposite Qurate Retail and Flow Traders positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Qurate Retail position performs unexpectedly, Flow Traders 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 Flow Traders will offset losses from the drop in Flow Traders' long position.| Qurate Retail vs. Samsung Electronics Co | Qurate Retail vs. Samsung Electronics Co | Qurate Retail vs. Hyundai Motor | Qurate Retail vs. Toyota Motor Corp |
| Flow Traders vs. Edita Food Industries | Flow Traders vs. Skandinaviska Enskilda Banken | Flow Traders vs. Prudential Financial | Flow Traders vs. Erste Group Bank |
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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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